Dave Mabe

Slippage Over Time

2026-04-08T15:30:00-04:00

In yesterday's post, I showed how you can compute slippage on a trade-by-trade basis and then sum it up for the entire day.

The next step is to view slippage in aggregate over time.

The ability to use your backtest as a reference is extremely valuable.

Your measure of success goes from "did I make money today?" to "how well did I follow my plan?"

When you have a backtest going back years and a nice, smooth equity curve, the anxiety of any particular trade or day melts away.

The way you get confidence from this point is by gathering proof that the live trades won't be too far off the backtest.

And when you can generate true confidence, you can scale your strategy over time.

Just like any particular trade isn't going to make or break your strategy, the slippage from any particular trading day isn't the full picture.

But start stacking several days together and looking at slippage in aggregate, and it starts to become clear where the real problems are.

Then you can devote resources to things that will move the needle for your strategy.

Here's a slippage TODO list you can use to put this into action:

Generate a list of your live executions by strategy
Run your backtest to generate a list of trades for the days your executions cover
Create a Python script to compare the two, categorizing the slippage into 3 buckets: entry, exit, and missed trades/partial fills

The output should be an easily viewable report showing:

Slippage per trade
Aggregate slippage across all the trades

Once you have this, you can start to address each slippage type.

Tomorrow, I'll discuss how to tackle the most important and most common type of slippage.

-Dave

P.S. Do you wish you had a column library that would tell YOU how to make your strategy profitable? My column library is now included with MabeKit

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Measuring Slippage

2026-04-07T15:30:00-04:00

In the previous email on determining how much slippage is too much for a strategy, I shared a way to pre-plan your slippage limit, so you have a benchmark to compare against.

Now, let's go over measuring slippage from your live trades.

Remember, there are three types of slippage (well, four really, but three are the bad kind):

Entry slippage - you got a worse price than your backtest on your entry order
Exit slippage - you got a worse price than your backtest on your exit order
Missed trades/partial fills - you expected to get X shares, but you only got some percent of X

We need to compute all three of these to get an accurate measure of the shortfall between your live trading and your backtest.

In my daily review, I have some automation that runs a backtest for the strategy and then compares the fill prices with the backtest.

The Trade Client that comes with MabeKit makes this easy by automatically creating a file with your executions by strategy.

Let's say you had one long trade where your ideal entry price was 50.00, but your fill was 50.05.

Your slippage is 50.05 - 50.00 = 0.05 per share multiplied by the number of shares.

Now, let's assume you have another signal, but you got no fill on the trade. How do you compute the slippage there?

Well, it needs to come from the backtest - assuming you got the trade at full size, how much would you have made?

Add that to the missed trades bucket.

Exit slippage is computed in the same way as entry slippage.

Now you have three buckets of slippage.

But there's one important step to compare apples to apples with your backtest.

You need to normalize the slippage to account for any sizing differences with your backtest.

When you increase your size in live trading, you don't want to have to change the sizing in your backtest to reflect it.

All my backtests have a standard, easy-to-compute sizing that stays constant.

And then I normalize my live trading to the backtest sizing for comparison.

Now you should have your total slippage for a given trading day, normalized to a number you can compare to the benchmark from your backtest.

Next time, we'll discuss how to track this over time to prioritize how to address slippage.

-Dave

P.S. "The process of becoming a more systematic trader honestly mirrors the journey of becoming a trader at all—lots of ups and downs, frustration, second-guessing, and moments where you want to quit. And then every once in a while, there’s a real moment of clarity and forward progress. Using the AFL code generator in MabeKit feels like one of those moments." - Mike A.

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Interview with Trent Smalley of DTN/IQFeed

2026-04-06T15:30:00-04:00

In this week's episode of Line Your Own Pockets, we interview Trent Smalley with DTN and IQFeed.

We discuss:

Why it makes sense for traders to pay for market data when brokers offer it for free
Where bad ticks you see in your charts actually come from
What happens to market data before it hits your feed
When you know you're ready to upgrade to a high quality feed

And much more...

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-Dave

P.S. Are you ready to take your trading to the next level? Learn the right way to create your own trading strategies with MabeKit coaching. Here's what a MabeKit trader I'm coaching recently told me: "I wasn't prepared for this level of consistency in new equity highs in curves from my strategies." - Ryan

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How Much Slippage is Too Much?

2026-04-03T15:30:00-04:00

That's the question you should be asking yourself as you create strategies.

Here's how you determine how much is too much.

Let's say in your backtest, your average profit per trade is $100.

Remember, this $100 of average profit assumes ideal execution.

That is, you don't miss any trades, and you get your full size at perfect prices.

Of course, this won't happen in reality, but it serves as the goal to achieve with every trade the strategy makes.

When you sum up all slippage over a period of time and convert it to average slippage per trade across the entire backtest, at what level would the strategy be not worth trading?

Let's say you summed up all slippage, and it accounted for $25 per trade. You're left with $75 average profit per trade.

What would the equity curve look like if every trade had $25 less in profit?

It would look worse - but how much worse?

Now imagine slippage sums up to $50 per trade, on average.

The curve will look even worse.

Continue until you determine your cutoff - what level of slippage you'd need to see such that the strategy wouldn't be worth trading.

Now you have a pre-planned benchmark to compare against when you start trading the strategy live.

Next time I'll discuss measuring slippage in your live trades so you can compare...

-Dave

P.S. WEBINAR ALERT - A few weeks ago, I gave a presentation for SMB Capital on the Bionic Trader webinar titled How to Avoid Curve Fitting. In case you missed that, Interactive Brokers has invited me to give the talk on April 16th at 2pm ET. Registration is below. I hope to see you there:

Estimating Slippage in a Backtest

2026-04-02T15:30:00-04:00

Most systematic traders overcomplicate things by trying to model a slippage estimation for every trade in their backtest.

Here's the thought process:

Since backtesting is theoretical, you can engineer a solution that makes it reflect the reality of live trading.

Some trades will have more slippage than others, so just add some built-in slippage into your backtest based on some "thickness" criteria like volume, average volume, or something else.

Add level one data (L1) to get more "accuracy."

But if L1 data can make it more accurate, then L2 data can make it even better!

I'm sure your overeager LLM will be happy to help you overengineer a backtest that makes all sorts of crazy attempts to reflect live trades.

I think this is a total waste of time.

(Especially as you size up your live trades and now your slippage estimate in your backtest needs to adjust.)

It's ok if your backtest reflects perfect execution, even though your live trading will never measure up.

In fact, I prefer my backtests to simulate ideal executions.

Here's why.

Because it provides an ideal baseline - a goal for my trade execution to shoot for.

Once you give in to the fact that your live trading isn't going to measure up to the backtest, you can think about the problem more clearly.

The question isn't whether your live trading will measure up, but how big the difference will be.

Any attempts to model slippage in your backtest just muddy the waters and make that question harder to answer.

The real question you're trying to answer is:

What level of slippage would be needed to make this strategy unprofitable to trade?

I'll break that down tomorrow...

-Dave

P.S. Wish you could backtest your ideas - without spending months learning to code? Run your first backtest in an afternoon using my Amibroker AFL Course.

All About Slippage

2026-04-01T15:30:00-04:00

Over the next few days, I'll be focusing on one of the most important and misunderstood topics among systematic traders: SLIPPAGE

When I say slippage, this is the definition I'm referring to:

Slippage is the difference between your ideal fills in your backtest and the actual fills you get trading live.

Why is it so important?

That's easy - for many strategies, slippage will be the main reason it doesn't live up to the backtest.

The more you understand about slippage, the more you can prepare and design strategies that are resilient to it.

The first thing to consider is the different types of slippage.

Entry slippage - you got a worse price than your backtest on your entry order
Exit slippage - you got a worse price than your backtest on your exit order
Missed trades/partial fills - you expected to get X shares, but you only got some percent of X
Positive slippage - you get a better price than your backtest (my favorite kind lol), rare and mostly seen on target orders

All of these will wear away at your trading strategy (except the last one!).

It can be frustrating, but this is an unavoidable part of trading that you simply have to get used to.

Over the coming days, I'll address measuring slippage, how to include it (if at all) in a backtest, and the most important thing: what you can actually do about it.

More soon...

-Dave

P.S. Do you wish you had a strategy that actually made money? Create your own in minutes, not months, with MabeKit

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Strategy Creation Workflow Submitted from MabeKit User

2026-03-31T15:30:00-04:00

MabeKit user Aben created an excellent diagram for the entire workflow of creating a systematic trading strategy.

Steps highlighted include:

Getting the initial backtesting infrastructure ready
Optimizing the strategy using the Cruncher
Refining the strategy further (inspecting trades, further backtesting, more crunching)
Paper trading using the MK Trade Client
Transitioning to real capital and scaling up

Here's the diagram:

It's quite good.

Take a look and let me know what you think. Any missing steps?

(BTW, Aben tells me he created this using MindManager software - very cool.)

Thanks for sharing, Aben! With work like this, I'm confident we'll be sharing a success story here soon.

-Dave

P.S. Are you sick of second-guessing yourself every time you click buy or sell? Trade with conviction using MabeKit.

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Using AI Agents for Backtesting Part 3

2026-03-30T15:30:00-04:00

In this week's episode of Line Your Own Pockets, we continue the discussion of using AI agents for strategy creation gruntwork.

Topics discussed:

Delegation skills are important - the more specific, the better
How my approach differs from Michael's regarding Claude use
How to implement "unit tests" for your trading strategy
Developers always want to build - here's why you shouldn't
Starting points for developers

Much more...

I think this was the best one yet on AI.

LISTEN NOW »

-Dave

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"How can I stop holding my losers too long and selling my winners too quickly?"

2026-03-27T15:30:00-04:00

Here's an email I received from Omar T. (name used with permission, edited lightly for clarity):

Omar T:

I seem to hold my losers and sell my winners too quickly. Sometimes I look back and I could have made a lot more profit, or could’ve lost if I held the trade longer.

I just feel like I understand the market and reading price action, but I seem to find myself chasing into a trade.

It’s a hard habit to break. I know I’ll never catch the bottom or top of every trade, but I’d like to have better entry points. So that’s one thing I’m working on changing. I’m so fascinated with the stock market, and I’ve learned a lot during this journey. I’m just trying to keep positive and not give up.

Dave:

This is a classic situation for traders just starting.

You have a decent plan for getting into trades, but then expect some magical intuition to eventually form so you can manage each trade to its optimal conclusion.

When trying to "understand the market and read price action," most traders look at way too much data and try to draw conclusions in real-time.

Add to that the psychology of money and the bouncing P&L on your trading platform, and you have a recipe for mediocrity.

I'm convinced humans are hard-wired to make the least profitable decision when they're in a trade without a well-defined plan.

And a plan is not hoping to "get better at reading price action."

Step back and think about how you could create the confidence to make the right decision during a trade.

It's impossible to formulate a plan that will be optimal for every specific trade you're in.

But you can create a plan that's optimal across similar trades in aggregate.

And you won't care about "reading the tea leaves" to decide how to exit a trade.

Why? Because any individual trade won't matter that much.

Any given trade might look like you completely bungled it, but that's irrelevant.

Confidence comes from knowing you're doing the right thing across a large number of trades.

When you start answering that question, you can see a path to trading with larger and larger size over time.

Without that, you'll never move beyond the cycle of trading a strategy, having a drawdown, getting frustrated, and moving on to another strategy.

Thanks for the question, Omar!

-Dave

P.S. Are you in a drawdown and ready to quit? Join the other traders who reversed their drawdowns and are printing money with MabeKit.

"What if some years in my backtest have lots of trades?"

2026-03-26T15:30:00-04:00

Here's a reader question from Andrew K. (name used with permission, lightly edited for clarity).

Andrew K:

I've created a pullback strategy for swing trading. My main problem is that I keep facing some years where many, many trades occur relative to other years in the backtest. If I allow all trades to get a large sample, a majority of them are during these years.

When I optimize, this leads the filters to focus more on the years with more trades.

Essentially, my strategy now performs really well during these years in comparison to a typical year, which is not what I want.

I've experimented with maxing out the number of trades to allow a little more than the typical year, but I'm not sure how I feel about that, so I wanted a second opinion.

Dave:

This is a common scenario, especially with swing trading. And yet another reason day trading is superior (and easier).

With swing trading, you're often going to need to expand your backtest window over a large period of time.

And by doing that, you're going to have to include periods of unique market action.

For example, the COVID period in 2020.

When you backtest and optimize on that period, you're optimizing for something not likely to happen again in our lifetimes. (But if COVID happens again, your trading strategy will be ready lol!)

Here's the thing:

Your strategy should be based on a signal that's relatively unusual during relatively normal market periods.

If your strategy requires a unique market situation to work, there's a good chance the unique market situation won't occur again. Maybe ever.

Here are some next steps to think about for this strategy:

When optimizing, focus on trades per day and how evenly distributed the trades are
Add more columns - this will make it easier to incorporate trades per day in your analysis
Try excluding one of the big trade years and optimize - some suggestions can suggest a better starting point you can use to create a strategy where the trades are better distributed

I think the entire process gets easier when you're day trading - for plenty of strategies, you can start your backtest on 2021-01-01 and avoid COVID entirely.

That's much harder with swing trading.

Nice work, Andrew - I'm looking forward to hearing how this works for your strategy.

-Dave

P.S. Amibroker users: are you trying to use ChatGPT to create a backtest only to discover how bad the LLMs are at coding Amibroker's language? You're not alone! You need my Amibroker AFL Course. It comes with a demo strategy that serves as the perfect starting point for any strategy you want to create.

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Success Story from Glenn B. and a Question

2026-03-25T15:30:00-04:00

Here's an update from MabeKit user Glenn B., and a question (name used with permission, lightly edited for clarity)

Glenn B.

I've recently completed my first model, thanks to MabeKit.

Below are my first successful strategy, which probably has some mistakes, but the insights from this process are immeasurable!

Crunched 3 times:

To be honest, I'm MORE happy about the process I've developed to build a new strategy than I am about this particular one.

With reduced self-inflicted coding bottlenecks, I'm really focusing on the data and the bigger picture.

My time is spent more on questions like:

What does the data say about timed exits?
What does the data say about risk management?
What can't my data tell me?
How can I validate the results?
etc...

All my preconceived notions have been abandoned, and I'm feeling pretty hyped about my new perspective!

My main question: in your experience, what percentage of completed models will pass paper/live trading?

Dave:

Nice work, Glenn! You're right: the power here isn't necessarily in any one particular strategy, but in a generic process for building reliable strategies.

And your mindset at this particular point in the process is ideal!

Most traders at this point feel like the work is done - the equity curve looks good, and it's off to the races.

But a healthy dose of skepticism at this point will take you a long way.

The next phase is where the real learning begins.

The moment you go live, even at a minuscule size, you are getting feedback about your strategy from the best traders in the world in real-time.

How can I validate the results?

This is the right question to ask yourself.

The quicker you can validate your results, the quicker your path to confidence with the strategy.

This is one reason why backtesting is so powerful.

Think about discretionary trading - it might take you months or years to get confident enough in a strategy to trade it responsibly with large size.

That's because there is no way to validate the results of a discretionary strategy quickly.

But back to your question. First, there are no "completed" models - there's always some way to improve them.

And there is no pass/fail test for live trading, there's just varying confidence in the strategy over time.

The real question to ask yourself: what questions would I need to answer to trade this strategy with bigger size?

More on this topic in the coming days...

Congrats, Glenn, and thanks for sharing with the list!

-Dave

P.S. Do you wish you had a strategy that actually made money? Create your own in minutes, not months with MabeKit

Success Story from Chad - 77R in a Month

2026-03-24T15:30:00-04:00

I'm receiving more and more success stories from traders who've started down the systematic route, but more importantly, have started using columns in their backtests.

This one is from Chad (name used with permission, lightly edited for readability)

Chad:

My first column-based strategy has been running for a month now - so far, so good. It peaked at 77R and is in a slight drawdown. I have so many ideas to improve things.

I want to experiment with limiting the number of open trades. It opened 50 trades in a short period (after a Trump tweet), and all I could think was that if I were trading with large size, that would really scare me.

Thanks for sharing your concepts and ideas!

Dave:

77R in a month - I love it!

One of the metrics I study closely when optimizing a strategy like this is trades per day.

I want that number to be as large as I can, but also, importantly, I want the trades to be spread out.

That is, I'm careful to make sure there aren't large clumps of trades on a small number of days.

Of course, you can't control the fact there could be days with more trades in your system than occur on any single day in your backtest.

If you want to reduce the number of trades, I would go back to the backtest and use one more pass through the Cruncher to find a way to:

Reduce the trades per day (since you have a lot of room to play with)
Increase the profit per trade
Create a smoother equity curve

With the right columns in your backtest, there's no doubt this is possible.

And with this new version of your strategy, you'll have eliminated an obstacle in your path to confidence for this strategy.

Nice work, Chad!

-Dave

P.S. Do you wish you had a column library that would tell YOU how to make your strategy profitable? My column library is now included with MabeKit

Using AI Agents for Trading Strategies Part 2

2026-03-23T15:30:00-04:00

In this week's episode of Line Your Own Pockets, we continue last week's discussion on using Claude and OpenClaw to automate strategy creation.

We touch on:

How to get AI to do the grunt work so you can be the CEO of your trading
Why Michael switched from OpenClaw to Claude Code
Teaching Claude to automate Amibroker (hint: point it here)
How giving Claude Prop Firm constraints helped focus its work
Auditing its work is critically important - the more you understand, the better

Much more, including the next steps of using the Cruncher in this process...

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-Dave

P.S. Are you struggling with writing AFL code for backtests in Amibroker? Generate working backtests in seconds with MabeKit.

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"The Backtest Filter I'm Applying Doesn't Get Rid of All the Trades. Why?

2026-03-20T15:30:00-04:00

Here's a question from Brad (name used with permission, lightly edited for clarity).

Brad:

I recently purchased your AFL course and template and have been working with it extensively. It has been an excellent foundation for building strategies and learning AmiBroker.

I am currently working with a smaller database of approximately 1.5 to 2 years of data to learn proper backtesting techniques more efficiently. I have been using the strategy in your template and adding my own columns over time.

My process involves exporting the results from AmiBroker into Excel, applying filters to the columns, and identifying results that show potential. However, I have encountered an issue: when I apply those same filters within the AmiBroker backtester and re-run the test, I get completely different and almost consistently worse results.

I have reviewed my database settings and code, but I cannot find the source of the discrepancy. Are there some specific settings you know of to check or concepts I might be overlooking that would cause such a difference between the exported data and the backtester results?

Dave:

I can understand your frustration because I've been there!

I can't see Brad's code, but I'm reasonably certain he's running into what I call the "peek-a-boo" problem.

I recently gave a talk on SMB Capital's Bionic Trader show on this exact topic, so it's fresh in my mind.

The issue is that unless your code is set up to handle this, you're likely just postponing trades rather than filtering them from your backtest.

Take this hypothetical example. Your strategy's signal is when a stock reaches a new high. You go long.

You run the backtest and one of your columns is Volume Today.

In your Excel analysis, it tells you that a minimum value of, say, 500k will improve your strategy by removing 1/3 of the trades.

You add the filter and run the backtest, but find it did NOT remove 1/3 of the trades. Why?

Well, think about your signal and the Volume Today filter.

New highs can occur multiple times per day for a single symbol.

And the Volume Today continues to increase throughout the trading day.

The earlier trade is gone (when the Volume Today was less than 500k), but you've replaced it with a trade in the same symbol later in the day when that Volume Today minimum is finally met.

How do you handle this?

You should handle this like the MabeKit AFL Generator handles this, by having a way to invalidate the symbol for the remainder of the trading day when a signal is found that DOESN'T match your filter set.

Here's what it looks like in the code that the generator produces:

Invalid = VolumeToday < 500000;

This makes the backtest filter out the earlier trade AND put it on a list that knows to skip any futures signals that might occur for that symbol for the remainder of the day.

More on this topic in the coming days - it's an important topic to understand!

Great question, Brad.

-Dave

P.S. Are you struggling with writing AFL code for backtests in Amibroker? Generate working backtests in seconds with MabeKit.

To Infinity and... Beware Infinite Values

2026-03-19T15:30:00-04:00

One phase traders go through is learning just how important position sizing is.

The same strategy can be dramatically different depending on the sizing approach used. (Good example here).

When you size positions based on your risk (distance to the stop) and then measure performance by risk, it can unlock an entirely new dimension of strategies and ideas.

But be very careful - it's easy to let outliers sneak in a backtest that have inordinately large sizes.

If you're sizing based on distance to your stop, but your stop is really close to your entry, then it's easy to get infinite sizing.

Here's an example.

Let's say you want to risk a certain amount with each trade, say, $100.

In your code, you could size positions like this:

RISK = 100; entry_price = 50.10; stop_price = 50.00; distance_to_stop = entry_price - stop_price; shares = RISK / distance_to_stop;

In this example, shares is 100 / 0.10 = 1000.

But let's say your stop is closer. Say it's 50.09.

Now your share size is 100 / 0.01 = 10,000.

If you're not careful, this number can get way larger very quickly.

When you go to optimize in the Cruncher, the larger share sizes will naturally weigh more heavily on your analysis.

If you have large outliers, they can make a dramatic difference - even just a trade or two can skew things a lot.

It's helpful to really understand what's going on in your code and put safeguards in place to avoid this, not only when you make trades, but much earlier when you are optimizing.

In the example above, the best approach is to use a floor for the stop_distance so you can control how small that can get.

You should also place a ceiling for your share size in case your code does something you didn't imagine it could do.

-Dave

P.S. Are you sick of second-guessing yourself every time you click buy or sell? Trade with conviction using MabeKit.

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"Where should I go next with this trading strategy?"

2026-03-18T15:30:00-04:00

Here's a question about a futures strategy from Arjun (name used with permission, lightly edited for clarity).

Arjun:

I am trying to trade futures now (/NQ and /ES mainly). I bought Amibroker 7, and I am importing data via the IB connection. I have 6 months of 1 min data in my backtesting database. (I will subscribe to IQ to get at least 10 years of minute data.)

I have two strategies I'm trying to backtest:

one is on 500 tick level
another uses 3-minute bar data

I am getting some results like 20-30%, with 40/60 win rate and 1.45 profit factor with NQ, ES, and CL, but the drawdowns are not ideal (max 10% drawdown).

I have been simtesting the strategy. I am not sure where to go from here.

Is more data a requirement to say these numbers are acceptable?
Should I do more strategy parameters optimization?
Should I add more attributes to better the strategy?

Dave:

Great questions and nice work getting to this point with your strategies.

The real question here is what would give you more confidence that the strategy will continue to work into the future?

If you had more confidence, then you could create a plan to trade it with increasing size over time.

He doesn't mention how many trades there are in each system, but I can infer that there are not several thousand simply because of the instruments traded and the time period.

Because you're applying this to just a few instruments, I would focus on getting more data in your backtest.

The nice thing about that is you've already done most of the work. Now it's just a matter of getting more data into a backtesting database and running the same code on that instead.

Having more data for your backtest will allow:

More confidence in the strategy itself since you'll have a much broader perspective
Makes more columns/parameters feasible
Reduces the pressure to have to re-optimize the strategy frequently

That last one is important - your strategy will be a lot more robust.

As I often tell futures traders, if you've made it this far with a strategy trading just a single instrument, you have the potential to create easier and more plentiful trading edges by applying your ideas to US equities.

That is, you're doing it the hard way, and the fact that you've made it this far is a great sign!

Thanks for sharing with the group, Arjun.

-Dave

P.S. Are you ready to take your trading to the next level? Learn the right way to create your own trading strategies with MabeKit coaching. Here's what a MabeKit trader I'm coaching recently told me:

"I wasn't prepared for this level of consistency in new equity highs in curves from my strategies." - Ryan

"Have you considered systematically trading the prediction markets?"

2026-03-17T15:30:00-04:00

Here's a question from Paul (name used with permission, edited lightly for clarity):

Paul:

I'm interested in applying automated AI systems to the nascent but growing prediction markets like Polymarket. Have you considered applying your trading mindset and systems to creating automated trading bots in this arena? I do believe there is enough early inefficiency there that it could be a bit of a gold rush for the next year or even several years, for the right systems.

Dave:

I love prediction markets, and I think we should have allowed them a long time ago.

As economist Alex Tabarrak says, "Betting is a tax on bullsh*t."

I also think it's very likely that there is some trading edge in these new markets.

In fact, I have made some select bets in recent presidential elections that have turned out well.

But there's one main reason I'm not focusing on prediction markets right now.

It comes down to a phrase you've probably heard me say many times.

What's the path to confidence with a strategy that trades the prediction markets?

There's a ceiling to how much confidence I feel like I can achieve with a strategy that doesn't have a lot of historical data to backtest on.

One of the first questions I ask traders I coach is "Are you trading your strategy with full size? And if not, why not?"

It's easy to trade stocks (or prediction markets) with relatively trivial size.

But to trade with meaningful size, you need to have a path to confidence.

The lack of historical data for prediction markets is the roadblock standing in the way of that.

Creating your own path to confidence is just easier in trading financial instruments, and specifically U.S. equities.

Great question, Paul, and thanks for sharing with the group.

-Dave

P.S. Do you wish you had more confidence in your trading, so you can trade with bigger size? Create your own path to confidence with MabeKit.

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Using AI Agents to Backtest Strategy Ideas

2026-03-16T15:30:00-04:00

In this week's episode of Line Your Own Pockets, we discuss Michael's project for having OpenClaw create and run backtests from his list of research ideas for trading strategies.

His agents have created over 200 backtests
How they've primed the backtests to be used in the Strategy Cruncher
SOPs (Standard Operating Procedures) have paved the way for this workflow
AI as a research assistant/intern for your trading business

And much more...

If you want to learn how to use AI in your trading business, don't miss this one!

LISTEN NOW »

-Dave

P.S. Do you wish you had a strategy that actually made money? Create your own in minutes, not months with MabeKit

"Next steps for these strategies?"

2026-03-13T15:30:00-04:00

Here's a question from Brent S. on two strategies he sent for review. (Name used with permission, lightly edited for clarity.)

Brent S:

I have spent the last month learning .afl and have pulled together two starter strategies, probably very common starters. I started with the AFL template in your course for both. The first is an EMA/EMA crossover. The second is an EMA/VWAP crossover that I used ChatGPT to add some additional filters to, which I modified some myself in the end, but I am not sure how helpful the additional filters actually are.

I can see the strategy results in their respective analyses screens and on the charts look promising, but I'm very skeptical. Could you provide any input on what I would do from here? Optimize? Start over?

Dave:

Nice work creating these strategies - a lot of traders don't get this far.

Here's what I see when I compare the two strategies:

The EMA strategy looks a lot stronger, but there are almost twice as many trades in the EMA one, so the equity curve can be slightly deceiving.

I ran both of these strategies through the Cruncher, and here's what I found:

For the VWAP strategy, applying a rule for Yesterday Dojiness (definition here):

Applying that one rule would improve the strategy quite a bit by removing several losing trades from the system.

For the EMA strategy, things look even better when you add a rule based on Gap Percent:

This is saying that stocks that are gapping up perform significantly better than stocks that are opening flat or gapping down.

Note that this analysis only includes the columns that come with the sample strategy with the AFL course.

When you add the full MabeKit column library to your strategy, there will be many ways to improve the strategy.

Here's what I would suggest for next steps:

Now that you know these columns are highly predictive for the strategy, go back and create a new starting point by applying the rules mentioned above, but relaxing some other rules in your original versions.

That should create a starting point with even more trades with a higher average profit per trade.

See how your analysis ends up with the new versions and then compare them to your originals.

Nice progress with your strategy and AFL skills, Brent! Thanks for sharing with the group.

-Dave

P.S. Think you have trading skill but nothing concrete to test? Start with the proven backtest included in my Amibroker AFL Course and make it your own, just like Brent did.

Automate an Amibroker Backtest

2026-03-12T15:30:00-04:00

One of the many nice things about Amibroker is its developer-friendly attitude.

A great example of that is the fact that you can automate backtests (or explorations) from a scripting interface.

This allows you to create scheduled tasks to run backtests or open several analysis windows exactly as you'd like each day.

Here's some Python code that does the following:

Connects to an already started Amibroker instance
Opens an APX file (an Analysis window you've saved previously)
Runs a backtest (same as clicking the Backtest button manually in the program)
Saves the results to a CSV file
Closes the Analysis window

To simply open the APX file instead of running a backtest, comment out the line with the call to Run and the remaining lines in that function.

import argparse
import sys
import time

import win32com.client

BACKTEST_ACTION = 2

def main():
    parser = argparse.ArgumentParser(description="Run AmiBroker backtest and export CSV")
    parser.add_argument("apx_file", help="Path to .apx analysis project file")
    parser.add_argument("--output", "-o", help="Output CSV path (default: same name as APX)")
    args = parser.parse_args()

    from pathlib import Path

    apx_path = Path(args.apx_file).resolve()
    if not apx_path.exists():
        print(f"ERROR: APX file not found: {apx_path}", file=sys.stderr)
        sys.exit(1)

    output = args.output or str(apx_path.with_suffix(".csv"))

    ami = win32com.client.Dispatch("Broker.Application")
    analysis = ami.AnalysisDocs.Open(str(apx_path))

    analysis.Run(BACKTEST_ACTION)
    while analysis.IsBusy:
        time.sleep(1.0)

    analysis.Export(output)
    analysis.Close()

    print(f"Results saved to: {output}")


if __name__ == "__main__":
    main()

For information on all functions available via this interface, check out the documentation.

-Dave

P.S. Why is every other trader printing money while you’re stuck? Close the gap with MabeKit.

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Using a Smaller Amibroker Database for Efficiency

2026-03-11T15:30:00-04:00

Following up on yesterday's email on how to split up data across multiple databases, here's another reason you might want to make your backtesting database smaller.

One quirk about Amibroker - even when you use the From-To dates in the Range field for a backtest, it still parses through all bars in the entire database.

(There's a good technical reason for this, I'm sure.)

This means that even if you specify just a single day for your backtest, it will take almost as long as if you specified All quotes in the Range field.

So if you have 25 years of minute bars in your database but only backtest on 10 years, you're essentially wasting resources and could reduce the time your backtest takes.

Once you have the data, it's trivial to create another database with the optimal number of bars.

Remember, you should always create a new database rather than change the number of bars in an existing database in Amibroker.

-Dave

Get Instant Access to MabeKit

"How can I split data across multiple Amibroker databases?"

2026-03-10T15:30:00-04:00

Here's a question from Jason D. (name used with permission, edited lightly for clarity):

Jason D.

After obtaining the full 24 years of minute bar data, what is the recommended way to parse or divide it into the five separate databases (each containing about 5 years of data)? Is there a specific tool inside of Amibroker to use?

Dave:

By default, I recommend putting all your data into a single backtesting database in Amibroker.

But there are reasons you might want to split it across multiple databases.

For example, your computer doesn't have enough resources to run a large backtest.

In this case, you could create separate databases for X year segments (say, every 5 years).

You could then choose the database to run your backtest on and generate a CSV file per database, then merge the results into a single CSV file.

You could even create a Python script to run each Amibroker backtest programmatically through the Amibroker COM interface.

There are command-line parameters for Amibroker to open a specific database:

C:\Program Files\AmiBroker>broker /database "C:\path\to\database"

Another reason is for pure efficiency purposes - I'll explore this tomorrow.

Thanks for the question, Jason!

-Dave

P.S. Do you wish you had a column library that would tell YOU how to make your strategy profitable? My column library is now included with MabeKit.

Get Instant Access to MabeKit

Strategies for Small Accounts

2026-03-09T15:30:00-04:00

In this week's episode of Line Your Own Pockets, we continue the discussion about trading small accounts.

We cover:

Making mistakes early when they're relatively cheap
Focus on scaling wide versus scaling up
Learn R-multiples - it normalizes your performance as your account grows
Become the best in the world at a very specific strategy (it's not as hard as you think!)

And much more...

Sharing is Caring

Do you know traders who will benefit from this topic? Share this episode with them.

-Dave

P.S. Does it feel like your strategy works for everyone but you? Make it work for your data with MabeKit.

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Guest Appearance on Desire to Trade

2026-03-06T15:30:00-05:00

Ettienne had me on the Desire to Trade podcast to talk about systematic trading and how backtesting is a trading superpower.

LISTEN NOW

WATCH NOW

Here are the show notes:

[00:00] Introduction
[00:37] Who is Dave Mabe?
[01:06] Fully automated trading vs manual execution
[01:40] How Dave started trading
[04:04] The problem with learning from intuition-based traders
[05:50] Can you really make money with discretionary trading?
[06:45] First automated strategy: success or failure?
[09:28] Do algo traders struggle with emotions too?
[11:09] Is coding required for automated trading in 2026?
[12:13] Why backtests look great but live trading fails
[15:48] How much variance between backtest and live is acceptable?
[16:45] What separates traders who quit from those who last 20 years
[19:51] Generating new trading strategies consistently
[23:30] Is there a limit to how many strategies you can run?
[24:46] Where to find Dave Mabe and his free backtesting course

Sharing is caring!

If you enjoyed this episode, please consider sharing it with a few friends who might find it useful. Thanks!

-Dave

P.S. Afraid to size up because you don’t trust your edge? Build confidence to trade your strategy with bigger size with MabeKit. Get Instant Access

"Can I use this volume discrepancy to create a profitable strategy?"

2026-03-05T15:30:00-05:00

Robert B. asks a great follow up question to my post from a few days ago describing the volume discrepancy you see across data providers (name used with permission):

Robert B.:

To follow up on Don's question: I wonder what sort of opportunities there might be in comparing the differences between those volume figures. Could there be a strategy that triggers and profits when there is a greater than normal difference between them? How would one reliably test for that?

Dave:

I like the way you're thinking, Robert!

At first, I was pessimistic about this, but the more I think about it, I can imagine a situation where it could be predictive.

Here's how I would tackle this.

You'd need a feed for both volume counts, so you can include that in a backtest.

There are ways to include this in Amibroker, but it's for advanced users only.

A better way to do it is to merge the data into a backtest CSV file as another column.

So you'd have two volume columns, one that includes the odd lots and sub-100 share trades, and one that doesn't.

Then add another column as a ratio of these two volume columns (call it volume_discrepancy_ratio or something).

Now you've got another column that you can optimize on in your column library.

For each of your strategies, run it through the Strategy Cruncher and see how this column affects the strategy.

Different values for this ratio could measure the breadth of participation in a move.

Thanks for the idea, Robert, and for sharing it with the group.

(Robert is trying to broaden his network and asked that I share his LinkedIn - feel free to connect with him.)

-Dave

P.S. Are you in a drawdown and ready to quit? Join the other traders who reversed their drawdowns and are printing money with MabeKit. Get Instant Access

"Is it worth upgrading to Amibroker 7.0?"

2026-03-04T15:30:00-05:00

Several traders have asked me about Amibroker 7.0 and whether it's worth upgrading to it.

The reliability of Amibroker over the years has been excellent, and I love the emphasis on backwards compatibility.

So normally, I'd say upgrading is worth it, but not an immediate priority.

But there is a specific function in Amibroker 7.0 that makes real-time trading much easier.

It's called fappend.

In previous versions, you could append to a local file from Amibroker without much trouble.

But the explorations are multi-threaded, which means every once in a while, your exploration will break when two threads try to append to a local file at the same time.

This is relatively rare, but your real-time trading gets interrupted when it happens, so it's a big deal.

Before 7.0, there was a workaround for this to make the file appending thread-safe, but it required some ugly code to get it to work.

With 7.0, the new fappend function is thread-safe and built-in. No more ugly workarounds.

When I saw this in the Release Notes, I knew this one lowly function would make any hassle of upgrading to 7.0 worth it.

-Dave

Get instant access to the Amibroker AFL Course

Guest Appearance on Chat with Traders

2026-03-03T15:30:00-05:00

Ian and Tessa had me on the Chat with Traders podcast to talk about my background and my transition to backtesting and automating my trades.

LISTEN NOW »

Here are the show notes:

How Dave got introduced to markets: From early exposure to investing through his family to actively seeking more control over his capital and moving from swing trading into day trading.
Why rules matter: The transition from discretionary decisions to systematic frameworks — and why trading without a process is a fast path to inconsistency.
Backtesting as a “superpower”: What backtesting really does for strategy development and confidence in your edge.
Reconciling backtests with real life: Practical realities of execution, slippage, and market structure — and how to build a feedback loop so your live results get closer to your simulations.
Drawdowns and mindset: How to handle periods where a strategy doesn’t behave as expected, and why many traders quit in drawdowns rather than at all-time highs.
Scaling a trading business: The difference between scaling size versus scaling breadth — and why uncorrelated strategies matter.
Practical first step for systematic traders: How to start adding structure to your trading with backtesting, even if you’re not a programmer.

Sharing is caring!

If you enjoyed this episode, please consider sharing it with a few friends who might find it useful. Thanks!

-Dave

P.S. Afraid to size up because you don’t trust your edge? Build confidence to trade your strategy with bigger size with MabeKit. Get Instant Access

How to Trade with a Small Account

2026-03-02T15:30:00-05:00

In this week's episode of Line Your Own Pockets, we discuss trading with a small account.

Topics discussed:

Don't wait until you have "enough" money to start learning
How trading with a small account is an advantage
Funding options: an overview of the prop trading landscape
No matter how big your account is, your trading strategy is paramount - focus on that
Lessons learned at this stage will be valuable to your trading forever

And much more... including my rant about a trading mistake I made just before we recorded this.

LISTEN NOW »

-Dave

P.S. Think you have trading skill but nothing concrete to test? Start with the proven backtest included in my Amibroker AFL Course and make it your own. Get Instant Access

How to Minimize the Effects of Corporate Actions

2026-02-27T15:30:00-05:00

Yesterday, I answered a question about handling symbol changes.

This falls into the broader category of what I call "requiring perfect data versus actually making money."

You could spend a lot of time spinning your wheels architecting the perfect workflow that handles all the edge cases.

But a much easier approach is to design your trading strategies in a way that reduces the importance of corporate actions.

You won't eliminate their effect, but you don't need to.

Here's how you can make trading strategies where the effect of corporate actions is like a fart in a hurricane - they just won't matter that much.

Day Trade

The boundary for most corporate actions is overnight. If you're not holding overnight, then you minimize the effect dramatically. Even holding a trade overnight in your backtest makes it susceptible to distortion.

Use Shorter Term Filters

Similar to holding overnight, the longer the timeframe your filters are in, the more corporate actions will affect your strategy. For example, take two rules that you might apply to a strategy:

The stock must be X ATRs above the 50-day moving average
The stock must be above yesterday's high by a certain amount

The first one needs more accurate data and is more subject to distortion.

Add More Trades

One of the main metrics I look at is the number of trades per day in a strategy. Ideally, that number is as high as possible.

The overwhelming benefit of this approach is more total profit, but a great secondary benefit is reducing the importance of any single trade.

There's strength in numbers. Importantly, using more trades provides a more reliable path to confidence.

Do you want to be statistically perfect, or do you want to make money?

-Dave

P.S. Do you wish you had a column library that would tell YOU how to make your strategy profitable? My column library is now included with MabeKit.

Here's what one trader said about it:

"Access to the MabeKit library has been a game-changer for me. More columns, plus faster optimization has meaningfully accelerated how I develop and validate strategies." - Nash

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"How should I handle symbol changes?"

2026-02-26T15:30:00-05:00

Here's a question from Nathan A. (name used with permission):

Nathan A:

I've been building a 10-year U.S. equities database (daily + intraday data, listed, delisted, and OTC) for intraday and swing trading, and I’ve run into challenges around how best to handle symbol changes.

Currently, I maintain a master ticker file and assign a persistent "instrument_id" to symbols that represent the same underlying stock. I use share-class FIGI and delisting dates to link symbols, and all of my backtesting references the "instrument_id" rather than the raw ticker symbol. While this works in theory, I’ve found it becomes much more complex in practice.

How do you think about this problem, and how did you and the team approach it at Trade-Ideas?

Dave:

This is a great question because it's something traders with a technical background have a difficult time wrapping their heads around.

It seems like there should be a perfect solution that handles all the edge cases - if you just spent more time tracking down the logic for them - THEN you'll have your backtesting setup just right.

But then another bizarre edge case comes along that breaks it.

It's messy, and there are weird judgment calls you end up having to make.

When you go down this rabbit hole, you'll learn some mildly interesting things about corporate actions, but I've found it's largely a waste of time for traders.

Rather than trying to over-engineer the perfect solution, a better approach is to design your trading strategies so that the effect of corporate actions and symbol changes is minimized.

Any guesses about what this might involve?

More tomorrow on this.

Thanks for the question, Nathan!

-Dave

P.S. Wish you could backtest your ideas - without spending months learning to code? Run your first backtest in an afternoon using my Amibroker AFL Course.

Workarounds for a Data Feed Outage

2026-02-25T15:30:00-05:00

Data feeds go down sometimes.

That happened a couple of days ago with IQFeed, a popular data feed used with Amibroker.

Here are some workarounds for this situation.

eSignal

eSignal is a similar data feed to IQFeed. I used them for many years before switching to IQFeed.

There's a plugin for Amibroker that's essentially identical for real-time data.

When I switched from eSignal, I kept both for a while for redundancy, but since IQFeed was reliable, I canceled it.

IBKR

There's an Amibroker plugin for the Interactive Brokers data service that comes with your account there.

It's much more limited (30 day backfill only) and less reliable, so I've never really used it for any extended period, but it works.

Massive (Polygon)

There is no Amibroker plugin for Massive (Polygon), but you could create something that would work in a pinch.

You could use their REST API to retrieve minute bars for your small list of symbols you need real-time data for, create a CSV file with the update, then import the data manually into your real-time database in Amibroker.

It's even possible to automate this entire process using Amibroker's OLE/COM interface.

I've used this type of process for a similar purpose, and it works surprisingly well.

The nice thing about outages is it forces you to get creative and weigh the costs/benefits of alternatives.

-Dave

P.S. Are you sick of second-guessing yourself every time you click buy or sell? Trade with conviction using MabeKit.

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Your Real-Time Data Source Goes Down - Now What?

2026-02-24T15:30:00-05:00

Yesterday, the IQFeed had a significant outage for an extended period.

This is a pretty rare occurrence - in fact, I don't remember the last time this happened.

When I asked my contact there about it, here's how he responded:

One of the Chicago data centers had a power outage coupled with an internet connectivity issue. Haven't seen that in a long time but it’s being worked on and we should know soon.

Things appear to be back to normal now, but they still haven't updated their system status page as of the time I'm composing this:

Outages are a thing, and you can't pretend they won't happen.

It's tempting to get mad at the provider, but situations like these are a reminder that nobody cares more about your trading than you do.

Ultimately, you are the CEO of your trading, and there's no one to escalate to.

And, therefore, it's your responsibility to have a plan when things inevitably break.

The right way to think about this incident was that your trading business had an outage.

Just as an outage at any firm is a valuable learning opportunity, so too are these. Use them as such.

Here's a list of things to do to turn outages into positive ways to get better:

When did you discover the issue? Could you have known earlier? How?
Can you create automated alerting to let you know when this occurs next time?
What backups could you switchover to during the next outage?

As frustrating as situations like this can be, it's much better to treat them as the world forcing you to think about how you can get better.

My daughter works for Google, and they have an excellent way to think about outages.

Every outage at Google is "no-fault" - that is, no particular person "caused" the outage.

The system caused the outage.

This encourages a productive, all-hands-on-deck response to improve the overall system, rather than assigning blame.

Apply this same attitude to your own trading business.

Tomorrow, I'll review several workarounds for the data feed outage from yesterday.

-Dave

P.S. Are you in a drawdown and ready to quit? Join the other traders who reversed their drawdowns and are printing money with MabeKit. Get Instant Access

Curve Fitting is Easy to Avoid

2026-02-23T15:30:00-05:00

In this week's episode of Line Your Own Pockets, we tackle curve fitting.

If you've ever wondered if you're curve fitting with your trading strategy, this episode is for you.

We discuss:

Curve fitting is a continuum, not a binary yes/no condition
Every strategy has a little bit of curve fitting
Let's say you wanted to maximize curve fitting. What would you do?
Easy ways to avoid curve fitting

And much more...

LISTEN NOW »

Sharing is caring

Do you know traders who will benefit from this topic? Share this episode with them.

-Dave

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Sizing Your Real-Time Amibroker Database

2026-02-20T15:30:00-05:00

Several traders replied to yesterday's success story about Mike and his blazing-fast real-time Amibroker database.

Mike sized his database with fewer bars than other traders might use, and there's a good reason for that.

How do you know how many bars are enough for your real-time database?

The answer is simple.

There should be just enough bars to calculate the "longest term" filter across all your strategies.

For example, let's say you run the Cruncher on your strategy and find this suggestion based on the Change from 10 Day SMA MabeKit column that you decide to apply:

If this were the longest filter across your strategy, then you would need as many bars as required to have 10 days in your database per symbol.

But remember, plenty of symbols trade in the pre- and post-market, so you'll need to account for that.

There can be up to 960 one-minute bars (i.e., the number of minutes between the pre-market open of 4am and the post-market close of 8pm).

So you'll need at least 960 * 10 days = 9600 bars to calculate that filter properly.

If there aren't enough bars to calculate, filter values will appear as blanks, so it will be easy to spot if you need to include more bars.

Speaking of database sizes, it's important to note that although Amibroker allows you to change the database size after it's been created, you shouldn't!

Always create a new database if you need to change the number of bars.

Stay tuned for more on this topic soon.

-Dave

P.S. Have you ever made an order entry mistake that cost you money? Imagine never making a costly mistake again. Eliminate your trading mistakes with MabeKit.

"The MabeKit Trade Client was a game-changer for my trading."

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Amibroker Performance Success Story

2026-02-19T15:30:00-05:00

New Amibroker users quickly learn there's a big difference between running a backtest and generating trade signals in real-time.

The right way to do this is to create two databases: one for backtesting and one for trading live.

MabeKit user Mike A. wrote me to share the performance numbers when he created a separate database for live trading and tuned it based on my recommendation (name used with permission, edited lightly for clarity):

Mike A.

Wanted to share a quick win based on your advice. My backtesting database was set to roughly a million 1-minute bars, and it was crushing performance — DAS slowed down, charts loaded slowly, and it basically made real-time trading unusable. Explorations were so slow that I couldn’t even get a clean timing on them.

I switched to a 1,200-bar (~25 trading days) database, and it’s night and day. On about 130 symbols, I can run the three explorations I’m using in under 15 seconds, and the rest of the system stays snappy.

Dave:

Nice work, Mike!

This underscores just how important it is to keep two separate databases.

Profitable trading signals are worthless if you can't generate them in time to take the trade.

In fact, they're worse than worthless because of the frustration they'll cause.

It doesn't really matter how long a backtest takes (within reason), but generating signals in real-time is what puts food on the table.

Thanks for sharing these performance numbers with the group.

-Dave

P.S. Are you struggling with writing AFL code for backtests in Amibroker? Generate working backtests in seconds with MabeKit. Get Instant Access

Debugging Real-Time Signals in Amibroker After Hours

2026-02-18T15:30:00-05:00

In Amibroker, sometimes you want to simulate real-time trading after hours.

Let's say you've created a strategy using the MabeKit AFL generator.

The code includes a section used for real-time trading through the Trade Client.

But your strategy might not trade very often, so you could end up twiddling your thumbs waiting for a signal for hours or even days.

And when the signal comes, you might find an error in your process.

You quickly fix it, but then you're playing the waiting game again for the next signal to arrive.

Here's a nice way to simulate a signal as if it occurred "now", no matter when "now" is.

This way, you can test the entire real-time trading workflow on demand, rather than waiting around for a real signal to be generated.

This video shows how it's done - by temporarily deleting bars from your database. (And then how to restore them.)

WATCH NOW »

-Dave

Get instant access to the Amibroker AFL Course

Starting Too Wide is a Mistake

2026-02-17T15:30:00-05:00

There is such a thing as starting with too many trades.

When traders start using the Strategy Cruncher with MabeKit, they sometimes go overboard by using a starting point for a strategy that is too wide.

You can understand the thought process - just make your initial criteria REALLY wide - with no assumptions - and let the Cruncher tell you what's important.

The problem with this approach is that loosening the criteria weakens your signal.

And the signal is the real impetus for the trade.

Make your signal too weak, and you don't have a signal at all.

So your starting point has way too much noise.

A good way to check this is to review the charts from your starting point.

And it usually doesn't take going through thousands of charts to see how strong or weak the signal is.

Systematic traders often get too comfortable immersed in the data, ignoring the lessons you can learn from doing chart reviews.

You don't have to become a discretionary trader to learn from charts.

Make it a habit to routinely review charts from your backtests (Amibroker makes this easy).

You'll almost always learn something that a spreadsheet alone is hiding from you.

-Dave

P.S. Are you struggling with writing AFL code for backtests in Amibroker? Generate working backtests automatically in seconds with MabeKit. Here's a video showing how this works.

How To Build Your Column Library

2026-02-16T15:30:00-05:00

On this week's episode of Line Your Own Pockets, Michael and I discuss how to think about improving your column library over time.

We discuss:

How your column library is like a shared software library: build once, reuse everywhere
Continuous variables are better than binary variables (e.g. Above/below a moving average)
The MACDV case study - MACD normalized by ATR
How intra-trade columns allow testing multiple concepts with a single backtest

And much more...

LISTEN NOW »

-Dave

P.S. Do you wish you had a column library that would tell YOU how to make your strategy profitable? My column library is now included with MabeKit

"Should I automate and go live with this strategy?"

2026-02-13T15:30:00-05:00

Here's a question from Randy L. about his backtested strategy (name used with permission, lightly edited for clarity).

Randy L:

I've developed this strategy that I trade, and I've made a TradingView indicator for it. I've been running it through some backtests, taking every signal that it generates. I'm getting some really impressive final results, but I'm wondering about my profit factor, and if this strategy could really be profitable if I started automating and taking every trade? I've attached a screenshot of the back test:

Dave:

First off, let's focus on the positives.

I like that you're starting from a strategy related to something you already trade and are familiar with.

Starting from a universe that you've had experience with is a good idea, plus it's completely additive to what you're already trading.

That's a tricky needle to thread!

There are lots of trades here, which indicates many paths for improving the strategy over time.

Reading the fine print, though, I think this strategy could use some work before going live.

It says "Fees/Slippage: $0", so some portion of these profits will disappear to commissions, missed trades, and slippage.

That's going to eat into the Profit Factor, maybe even bringing it below 1.

I like that you've broken the strategy down by different risk levels.

Notice that the higher the risk level, the higher the profit factor, but the lower the win rate.

Strategies with win rates below 30% are psychologically difficult to trade since you're guaranteed to have streaks of several losing trades in a row.

Next Steps for this Strategy

While probably not tradeable as-is, there's definitely some potential here because there are so many trades.

The fact that you're using TradingView, which gets my designation of the most overrated backtester on the planet, means you can improve this strategy significantly with a different backtester like Amibroker.

Here's what I would do from this point:

Convert the backtest to Amibroker and add the MabeKit columns to it
Run an optimization using the Strategy Cruncher

There's no reason you won't find several ways to improve the strategy's profitability significantly in ways you don't realize.

You can apply the improvements directly in TradingView by converting them to PineScript, or use Amibroker natively to send the trades.

Because you're using TradingView, this must be applied to a single or small basket of instruments.

The next step I would take is to apply the idea to the entire US equities market.

You'll find significantly more trades, and you'll be able to create a much stronger signal for the strategy, thereby having an easier path to a significant trading edge.

Thanks for the question, Randy, and for sharing with the group.

-Dave

P.S. Do you wish you had a column library that would tell YOU how to make your strategy profitable? My column library is now included with MabeKit. Get Instant Access

Does Choosing a Round Number Improve Your Strategy?

2026-02-12T15:30:00-05:00

Here's a question I see over and over from traders.

It most recently came up during my guest appearance on SMB Capital's Bionic Trader webinar last month.

I was showing a report from the Strategy Cruncher for a short strategy I trade.

The Cruncher detects optimal filter values to apply to your strategy to make it more profitable.

Often, those numbers are quite precise.

This precision bothers some traders.

Here's a video where I explain the issue and why "cleverly" choosing a round number instead of the optimal one makes no sense.

WATCH NOW »

-Dave

P.S. Are you struggling with writing AFL code for backtests in Amibroker? Generate working backtests in seconds with MabeKit.

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Sidewalks and Trading

2026-02-11T15:30:00-05:00

Mike Munger, an economist at Duke University, offers this thought experiment.

Let's say you're designing and building a university.

You've created the plans for all the beautiful, prestigious-looking buildings.

You know where the grassy quads are going to go.

You've got plans for the dormitories.

It's going to be awesome.

One of the last things you might consider is: where are the sidewalks going to go?

You could consult some engineers to figure out where they should go.

You could create a committee of professors and students to have a bunch of meetings to come up with a plan.

But Munger suggests there's a much easier and simpler way to decide.

Go ahead and build the university buildings and plant grass in all the quads between the buildings.

And build no sidewalks initially.

Then open the university and wait two years.

At that point, build sidewalks where all the brown paths in the grass have formed from people walking.

I love this thought experiment because the solution is so simple, while most of our instincts are to over-engineer a "perfect" solution before breaking any ground at all.

Many technically minded traders do the same thing with their trading strategies and backtests.

How are you over-engineering your backtest, trying to make it perfect before putting any money at risk?

Here's the thing:

There's always something you COULD do to make your backtest "better."

But oftentimes you're better off waiting and making those decisions based on real, live market action.

Think of going live not as the end game, but as an opportunity for the smartest traders in the world to give you feedback on your strategy in real time.

-Dave

P.S. Do you wish you had a column library that would tell YOU how to make your strategy profitable? My column library is now included with MabeKit. Get Instant Access

"Should I include delisted stocks in my backtests?"

2026-02-10T15:30:00-05:00

Here's a question from Helena (name used with permission):

Helena:

Do you include delisted stocks in your backtesting?

Dave:

Great question, and you might be surprised by my answer.

No, I don't bother.

I can hear some traders being horrified by this, but here's why.

I'm day trading, which, in addition to having more profit potential than holding overnight, allows you not to worry about delisted symbols.

Think about it: delisted symbols are companies that, for the most part, went out of business.

The way that would be more likely to affect your backtest is if:

Your strategy holds trades for several days
It has a relatively small number of trades, so an outlier could more easily affect the results
Your strategy goes long, and it holds overnight

So many issues with data like this resolve themselves with day trading and starting with many trades.

This is one of those issues I see some traders get stuck with - trying to create the perfect conditions for their backtest.

Do you want to be statistically perfect or do you want to make money?

Thanks for the question and for sharing with the group, Helena!

-Dave

P.S. Have you ever made an order entry mistake that cost you money? Imagine never making a costly mistake again. Eliminate your trading mistakes with MabeKit.

Qualities that Predict a Profitable Trader

2026-02-09T15:30:00-05:00

In this week's episode of Line Your Own Pockets, we discuss the qualities of profitable traders.

This topic came from a talk I gave at SMB Capital's Bionic Trader webinar, where I highlighted the inflection points in my trading career.

Topics discussed:

Profitable traders don't follow the crowd - or any particular trading guru
Healthy attitude towards trading and risk
Making great trades is the goal - ironically, the money is almost secondary
Day trading is key (don't believe me? Just do the math)
Automation is a massive trading edge

Much more...

LISTEN NOW »

-Dave

P.S. Are you in a drawdown and ready to quit? Join the other traders who reversed their drawdowns and are printing money with MabeKit.

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"Can you write one version of code for backtesting and live?"

2026-02-06T15:30:00-05:00

Here's a question from Ivan M. (name used with permission).

Ivan M:

Is it possible to write code for the strategy and run exactly the same code on a live account (to minimize risk of errors)?

Dave:

Yes, this is absolutely possible and highly recommended.

A very good programmer gave me a valuable lesson early in my career:

If you find yourself cutting and pasting code, you're doing something wrong.

The next time you feel the urge to copy and paste in your code, think about how you can do it differently.

Can you create a library that gets shared across several projects?

It's a little more work in the immediate term, but the payoff later is substantial.

This is the fundamental reason I use the term "library" for the backtest columns in MabeKit.

While it might not seem like a huge pain to copy and paste code for a single trading strategy, this process gets exponentially harder as you add more strategies.

And the same goes for backtesting and live trading code.

Most platforms make this possible.

Your instincts are correct here, Ivan. Thanks for the question and for sharing with the group.

-Dave

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Why are you not using GitHub?

2026-02-05T15:30:00-05:00

In this month's guest appearance on SMB Capital's Bionic Trader with Garrett Drinon, I gave a presentation on using LLMs (ChatGPT, Claude, etc) to create code for trading strategies.

They've invited me to be a regular guest on the show, so this was my fourth or fifth appearance.

There are always lots of great questions from attendees.

One topic that came up on Tuesday's webinar was traders using GitHub as their code repository.

Hardly anyone said they use it.

I'm always surprised that so few traders use GitHub for their code.

And of the traders I've worked with that do use it, not a single one was using it to its full potential.

If you're not using GitHub for your systematic trading, I'm interested to understand why.

Hit reply and let me know.

-Dave

P.S. If you missed the Bionic webinar, Interactive Brokers has invited me to give a webinar on the same topic on February 12th titled Consider LLMs to Create a Trading Strategy Without Going in Circles. You can sign up here to attend:

SIGNUP FOR THE WEBINAR »

"How can I create a strategy from this chart in ORCL?"

2026-02-04T15:30:00-05:00

DazeTrader asks a good question on X.

DazeTrader:

Can Trade-Ideas scan for intraday consolidation patterns? For example, $ORCL on 2/2 when the price was consolidating just above $168, then it broke down fast.

Dave:

It always seems like you can create a strategy by looking at a stock chart, but it's much harder than it seems.

Here's the chart:

The purple line is the breakdown that occurred at 1:15pm ET or so.

This is a great situation to use the Stocks Like This tool, which is free to use without a Trade-Ideas subscription.

Here are my thoughts on a strategy for this move:

Most traders try to use a signal before the move, but you'll likely end up with a lot of noise in your backtest
Try using a signal after the move has started
A signal alone will yield too many trades, so the filters you use to define your universe are critical

Potential filters here to define your universe for a backtest:

The open is in the high end of the premarket range
Several green bars in a row in the premarket (how many ATRs is that move?)
After the open, the range consolidates for hours, all the way up to the 1:15pm move
Opening range > range of last hour > range of last few minutes

Maybe the 1:15pm move is a red herring - what if you shorted the big move up in the premarket?

Here's a video I put together with some more thoughts on this:

WATCH NOW »

-Dave

P.S. This is a perfect situation to use the AFL code generator in MabeKit to create a strategy without writing a single line of code.

Here's what one trader says about it:

"The process of becoming a more systematic trader honestly mirrors the journey of becoming a trader at all—lots of ups and downs, frustration, second-guessing, and moments where you want to quit. And then every once in a while, there’s a real moment of clarity and forward progress. Using the AFL code generator in MabeKit feels like one of those moments." - Mike A.

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My Favorite Hidden Feature in Trade-Ideas

2026-02-03T15:30:00-05:00

I developed many features at Trade-Ideas during my tenure as CTO.

But this one stands out as my favorite.

One of the traders I'm currently coaching needed an efficient way to look at the previous day's history in an alert window, so I showed him this feature, which automates this.

It's not enabled by default - you have to turn it on in the Options window.

Once you enable it, you can turn on "Alert Logging" in any Top List or Alert window in the program.

This creates a CSV file with the contents of the window in your TradeIdeasPro directory on your computer.

It uses the date in the filename, so you get a new file each day.

This lets you automatically archive the window without lifting a finger.

There's no limit to the interesting things you can do with the data in this archive.

Here's a video I put together, explaining the feature and showing a Python script I created to produce a nice chart from the data in the CSV file.

WATCH NOW »

-Dave

P.S. Are you struggling with writing AFL code for backtests in Amibroker? Generate working backtests in seconds with MabeKit.

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Should You Use Python for Backtesting?

2026-02-02T15:30:00-05:00

In this week's episode of Line Your Own Pockets, I argue that most traders should NOT use Python for backtesting.

If you're a software developer, this might come as a surprise.

I see many traders with development experience choosing Python for backtesting without giving it much thought.

I've worked with several traders to switch from Python to Amibroker and every one of them is happy they did (and their equity curves clearly show it).

We discuss:

Python is a great general-purpose language, but that's what makes it a bad choice for backtesting
Iterating on your strategies is the critical piece - anything that makes that more complex will make things more difficult
In a world of LLMs, the argument for using Python for everything makes less sense
Choose your tools based on profit potential, not because "I like Python and am good at it."

Much more...

LISTEN NOW »

Sharing is caring

Do you know traders who will benefit from this topic? Share this episode with them.

-Dave

P.S. Think you have trading skill but nothing concrete to test? Start with the proven backtest included in my Amibroker AFL Course and make it your own.

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"How should I handle outliers in my backtest?"

2026-01-30T15:30:00-05:00

Several traders replied to my email yesterday about handling bad data, asking about how to handle outliers that aren't the result of bad data.

Outliers are something that should keep you up at night a little.

Here are some quick thoughts on outliers:

Make sure they are true outliers and not just bad data
Are the outliers all in your direction? (i.e. highly profitable trades) If so, that's better.
If they're all in your direction, is there still a chance of big losing outliers that haven't appeared yet? Or is there something fundamental about your strategy that avoids them? (Which is good!)
If there are big losing outliers, then it's time to pause and give it more thought. Is there a way to limit them?

These are important questions because they're often the reason you have trouble using larger size with your strategy.

One of the first questions I ask a new trader I coach is:

Are you trading your strategy with full size? If not, why not?

There are usually good, healthy reasons why they're not.

Sometimes the reason is fear of the potential for a large losing trade - an outlier.

So understanding outliers and gathering more data about them can unlock a path to confidence - and trading with larger size.

Look for more on this topic in the coming days...

-Dave

P.S. Do you wish you had a column library that would tell YOU how to make your strategy profitable? My column library is now included with MabeKit.

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Handling Bad Data in an Amibroker Backtest

2026-01-29T15:30:00-05:00

Here's an unfortunately common situation when backtesting across all symbols.

See this daily chart of ALT from September 2010:

This is classic bad data coming from the data feed.

You'll see similar wonkiness from all providers.

OK, so this is a pretty obscure stock with very little volume during this period - who cares?

Well, bad data like this has a habit of coming up in backtests in the form of trades.

Often they show up as outliers - either a crazy large winning or losing profit.

When optimizing a strategy, this is a big problem because they skew your process when you include them in your backtest.

Excluding them is really important.

I created a video showing how to identify and confirm that the data is bad and exclude it using Amibroker.

WATCH NOW »

-Dave

P.S. Wish you could backtest your ideas - without spending months learning to code? Run your first backtest in an afternoon using my Amibroker AFL Course.

Get Instant Access to the Amibroker Course »

How to Customize Order Fields in IBKR's TWS

2026-01-28T15:30:00-05:00

The biggest turning point in my trading - bar none - was when I started automating all my trades.

I had good years before that, but nothing like the years after implementing automation.

I see the same pattern with the traders I coach.

But even with implementing automation (like the Trade Client included with MabeKit), you still want to customize your views in the platforms where the trades end up.

The default view in Trader Workstation is missing some important fields, and I'm always surprised to see traders not customizing this view.

Here are the fields I've added to my Orders Grid in Interactive Brokers' TWS:

Submit Time - the time an order was submitted
Start Time - the critical field for Timed Exit orders
End Time - controls how long your entry order is active before automatically canceling if unfilled
OCA Group - a string that groups your exit orders together (OCA = one cancels all)
Order Reference - a string you can customize from the sending application. The Trade Client uses the Strategy Name for this field
Fill Price - the average fill price of that particular order (blank if not filled)

This gives you the perfect view to verify your orders were entered properly and a quick way to adjust them if you need to.

To add fields in Trader Workstation in the Orders Grid, right-click on a header, go to Insert column before, and choose the column you want from the extensive list.

Here's an image I sent to a trader using the MabeKit Trade Client showing how to add the Start Time field:

Adding these fields, plus any others convenient for you, will make your Orders grid far more useful and save you a lot of mouse clicks if you have to change an order.

-Dave

P.S. Have you ever made an order entry mistake that cost you money? Imagine never making a costly mistake again. Eliminate your trading mistakes with MabeKit.

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"What is the bare minimum win rate for a profitable strategy?"

2026-01-27T15:30:00-05:00

Here's a question from Marco C. (name used with permission, lightly edited for clarity)

Marco C.

What are the bare minimum critical aspects that make a trading system good enough for trading?

from my ignorance and limited experience

Reliably detect real strength and weakness of the market in real-time
Reliably select tradable assets with sufficient volatility and abundant liquidity
Responsible money management

The first point implies that a system that provides a win/loss ratio lower than 3/7 (43%) (being conservative) doesn't meet the eligibility criteria. This alone discards most of the teaching and advice regurgitated/glorified in the trading world.

Will successful backtesting provide confirmation for point 1?

Dave:

Win rate is overrated.

It's a common misconception among traders that win rate is an important metric.

Win rate is important, but it's the least important metric for your trading strategy.

I was reviewing my historical trading results from the early to mid-2010s recently.

During my most profitable years during that period, my win rate was between 36 and 38%.

(I've worked with profitable traders with even lower win rates.)

In the years with below average profit, I actually had a higher win rate.

So what should you look at to determine the strength of your strategy?

By far the most important metric is the equity curve.

You can create strategies with a variety of win rates, profit factors, etc, but have a smooth equity curve.

If you're thinking about win rate too much, you're making a mistake.

Do you want to be right, or do you want to make money? (Those are often in conflict.)

Good question, Macro, and thanks for sharing with the list.

-Dave

P.S. Are you in a drawdown and ready to quit? Join the other traders who reversed their drawdowns and are printing money with MabeKit.

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Amibroker: The Adventure Continues

2026-01-26T15:30:00-05:00

In this week's episode of Line Your Own Pockets, we discuss Michael's progress with Amibroker and his day trading strategies.

Topics include:

~~Batteries~~ Data Not Included - the best way to get data into Amibroker
The code that adds custom columns in Amibroker is resource-intensive
Quirks with databases in Amibroker
Your computer hardware matters with Amibroker (get more RAM)

Much more...

LISTEN NOW »

-Dave

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"Here's How I Prioritize Strategy Ideas"

2026-01-23T15:30:00-05:00

Reader Mike M. replied to my post on using the ICE method for prioritizing strategy ideas. (Name used with permission, lightly edited for clarity.)

Mike M.

Here's how I prioritize candidate ideas for trading strategies:

Weigh a lot of different factors and prioritize based on that.

Does the candidate idea fit well into the current market regime?
Is there potential for uncorrelation with current active strategies? Maybe if it’s different than current strategies. But not necessarily. And what level of uncorrelation?
Level of confidence in the idea.
How quickly can I expect to prove whether the idea is worth pursuing?
Do I know other people who are using the idea similarly and having success with it?
Would it actually be tradeable with the resources I have? I certainly wouldn’t try to compete as a market maker against HFT firms.

Dave:

A great list and mindset. I love this.

These all could fall neatly into the Impact, Confidence, and Ease categories using the scoring method.

I especially like the last three in the list.

Thinking that through before deciding to work on a strategy could save a lot of wasted time.

If you haven't looked closely at the ICE method, you should - several traders have told me they have implemented the scoring method and found it quite valuable.

Here's the podcast episode where I discuss the method in detail.

Thanks for sharing with the group, Mike M!

-Dave

P.S. I've been receiving more and more excellent questions from traders. I can't answer all of them here on the list, so I've started answering some on my YouTube channel. If you like the Q&A, please like and subscribe.

"Volume Discrepancies in Different Platforms - Why?"

2026-01-22T15:30:00-05:00

Here's a question about volume data from Don L. (name used with permission, edited lightly for clarity).

Don L.

I've been comparing the volume data in Amibroker w/ IQFeed and in my charting software (I use TradingView and Thinkorswim) and see quite a disparity in the daily volume. For instance, I was looking at today's biggest % Nasdaq gainers (like ELAB and ALMS) and comparing the charts in Amibroker and my charting software. ALMS in Amibroker was showing a significant difference in volume compared to TradingView.

Is this a limitation in my setup configuration? Ideally, I want to make sure I'm not missing potential opportunities.

Dave:

Very astute observation, Don.

You've identified one of the annoying things about datafeeds and platforms.

There's no standard way volume is counted across the industry.

It is a bit jarring for traders when you stumble upon this, but once you understand what's going on, it's not cause for concern.

Here's what's happening.

Traditionally, odd lots and sub-100 share trades were relatively rare and thought to be made by unsophisticated investors.

So many platforms simply excluded them in their volume counts.

As commission prices went down over time, it started making sense for big players to break up large trades into lots of smaller trades for the purposes of efficiency (and other reasons).

Add fractional share trading on top of this, plus a wave of additional investors participating in the markets now, and sub-100 share trades account for an increasing portion of the volume in stocks.

Because of their increased importance, it no longer makes sense to exclude them for volume calculations.

But several platforms have been around forever and have been counting volume in the traditional way.

So now you have basically two ways to count volume.

So what does that mean for traders?

As long as you understand what's going on and your platform is consistent, then it shouldn't be a problem.

The only issue might be if you decide to filter on raw volume in your backtesting platform and then apply that filter in real time when the platforms use different volume calculations.

In that situation, choose a filter/column that's normalized (like Relative Volume), and you should be fine.

Great question, Don - thanks for sharing with the list.

-Dave

P.S. Are you struggling with writing AFL code for backtests in Amibroker? Generate working backtests in seconds with MabeKit.

Here's what one trader said about the MabeKit AFL Code Generator:

"As someone who’s really not a natural coder, I’ve spent a lot of time feeling frustrated and tangled up in spaghetti logic—especially when trying to brute-force things with ChatGPT. The MabeKit AFL generator is a real breakthrough. Every once in a while in trading, there’s a real moment of clarity and forward progress. The AFL code generator feels like one of those moments. I was able to build two strategies end-to-end and get them running in AmiBroker." - Mike A.

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"How Should I Backtest This Volume Spike Strategy?"

2026-01-21T15:30:00-05:00

Here's a reader question from Wesley (name used with permission, lightly edited for clarity).

Wesley:

I've made a pine script in TradingView that gives me alerts if certain stocks produce a volume spike of 2x average volume (based on the volume MA 20 and on the 2m chart). That is so often "ending" volume or a breakout candle. Now I'm testing how often it really leads to a reversal or breakout if it happens around yesterday's high or low. Do you have any tips on how to approach this to get the best results from the backtest? This is the first time I'm doing this.

Also, how do you automate this with Excel? I'm doing everything manually.

Dave:

First of all, you'll tie yourself in knots trying to do this in TradingView.

The big problem with TradingView is that you can only backtest one symbol at a time, but even more importantly, you can't add custom columns to a backtest.

Because of that, you'll be stuck in backtest world with TradingView, never really making much progress.

Applying an idea like this to the entire US equities market will allow you to come up with a strong signal, since there are so many tradeable equities where this event occurs every day.

When you try to apply this to a signal instrument like a futures contract, you necessarily have to weaken the signal significantly to generate enough trades for the strategy to even make sense.

Here's how I would approach this in Amibroker.

I'd create a backtest that goes long on every volume spike. (Your definition of volume spike will likely need to be a lot tighter, i.e. stronger, otherwise you'll get too much noise in your backtest.)

Apply the MabeKit column library and run the backtest.

Run this through the Cruncher and it will tell you how to improve the strategy on the long side.

However, and this is key, as you iterate and apply rules from the Cruncher to your strategy on the long side, take note of the sets of trades you're removing.

They'll be strongly negative on the long side, which you'd naturally be removing from your long strategy.

But particularly poor long trades are a great source for creating an opposite strategy on the short side.

So not only will the Cruncher show you the way for a long strategy here, but it will tell you how to generate a short strategy at the same time.

I'd look for a natural way to split these trades into long and short strategies based on the rules suggested by the Cruncher.

So you start with one basic concept, but you end up with two distinct strategies from it.

Great question, Wesley, and thanks for sharing with the list.

-Dave

P.S. Do you wish you had a column library that would tell YOU how to make your strategy profitable? My column library is now included with MabeKit. Get Instant Access »

"Why Use a Scanner for the Daily Review?"

2026-01-20T15:30:00-05:00

Here's a question from long-time list member, Marek. (Name used with permission)

Marek:

As a systematic trader, you are doing the daily review of a strategy's live trades vs backtest and looking at the charts to get ideas. Why then would you use additional scanners to check the movers?

Is it for additional ideas or to get the feel for the market regime?

Dave:

The daily review I do at the end of the trading day is sacred for me.

You're right, I'm mainly analyzing live trades versus the backtest.

As I do that, I'm asking myself questions like:

Did I miss any trades, and if so, why? (This is important even when you miss losing trades.)
How much profit was lost due to slippage and partial fills?
What trades were just outside my rules? (Is there some way that would make sense to include them in my strategy?)

This part of the review is the most important since it involves scaling an already working strategy - and therefore the potential gains are more concrete.

The second part of the review is equally important in the long run, but more vague in the short term.

I'm looking for symbols that moved that I haven't captured in one of my existing strategies.

And brainstorming ways to create new strategies that give me coverage of that move.

The questions to ask yourself here are:

How unusual is this move?
If it's rare, can the parameters be relaxed to find more related unusual moves?
If you HAD to participate in that move, how would you have done it?

In this phase, I'm looking for ways to create a new backtest that I can feed to the Strategy Cruncher to give me a completely new trading edge.

The second phase is where scanners come in handy by presenting you with a steady stream of potential trades/ideas.

The daily review might seem like a lot, but the more you do it, the quicker and better you'll get at it.

It's the one non-negotiable thing I do every trading day.

Thanks for the question, Marek!

-Dave

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How Discretionary Traders Can Add Automated Strategies

2026-01-19T15:30:00-05:00

In this week's episode of Line Your Own Pockets, we discuss how discretionary traders are equipped with the ability to create automated strategies. Still, they often struggle to clearly see the path.

We go over:

How "visual" backtesting is not real backtesting
Discretionary traders try to replace what they're doing with automation - but that's wrong
How to create a completely new strategy from the ground up to be automated
How to build your "idea noticing" muscle

Much more...

LISTEN NOW »

-Dave

P.S. Are you in a drawdown and ready to quit? Join the other traders who reversed their drawdowns and are printing money with MabeKit. Get Instant Access

"How does backtesting work when market regimes constantly change?"

2026-01-16T15:30:00-05:00

Here's a great question from backtesting skeptic, Jan (name used with permission, lightly edited for clarity).

Jan:

I am a bit skeptical about backtesting because, by its very nature, it always measures the past, which will, no matter what, be different from the future (or present). For example, is there a difference between testing stocks in a bullish environment (or before Trump was elected) compared to today, where the context is significantly different? How does backtesting take that into account?

Dave:

Sure, the world is constantly changing - and that includes the markets.

But that doesn't imply that everything is changing and therefore completely unpredictable.

As I'm typing this, I'm looking out my window in my office at the horizon where the sun is getting ready to rise.

I can't guarantee with 100% certainty that the sun will rise, but I would bet a lot of money on a prediction that it will.

While many things in the market change and are impossible to predict, there are plenty of patterns that do consistently repeat.

Sure, you can backtest patterns that don't repeat, but that's the whole point of backtesting:

To help you find the patterns that repeat in a consistent enough way to profit from.

Backtesting is a superpower precisely because it's a way to detect the patterns that are consistent across time.

And when you find a pattern that's consistent across market regime changes, that creates a lot of confidence in your strategy.

Notice I always use the word confidence and not certainty.

You'll never be 100% certain that a strategy will continue working (this is why you don't risk your entire account with every trade).

But you don't need to be certain to make money in the markets - you just need to have an edge.

And your edge doesn't have to be incredibly strong to make money.

Even a subtle trading edge, if it's consistent, can be very profitable. (In fact, I'd say I prefer this kind of strategy.)

Great question, Jan. I like your skeptical stance - that mindset should serve you well in your trading!

-Dave

P.S. Wish you could backtest your ideas - without spending months learning to code? Run your first backtest in an afternoon using my Amibroker AFL Course. Get Instant Access

"But There's More Leverage in Futures!"

2026-01-15T15:30:00-05:00

Several readers responded to my post on why trading stocks is easier than trading futures, pointing out that there's more leverage when trading futures compared to stocks.

This is true, but it ignores a very important point.

For the vast majority of traders - even those with small accounts - the limiting factor is not buying power.

There's no point in having lots of leverage if you're never going to be able to take advantage of it.

The binding constraint for most traders is creating a strategy that can scale at all.

Most traders never get to the point of confidence to be able to truly take advantage of the leverage, even with trading stocks.

And creating a strategy that can scale is far easier with stocks than with futures for the reasons I outlined in the original post.

Thanks for the responses.

-Dave

P.S. Do you wish you had a strategy that actually made money? Create your own in minutes, not months with MabeKit. Get Instant Access

Which Version of Amibroker?

2026-01-14T15:30:00-05:00

Several traders who want to get started with Amibroker ask me which version they should get.

It comes up enough that I thought I'd answer it here.

My suggestion is to get the Professional Edition. There are several reasons why this version is far superior to the Standard Edition.

Automatic MFE/MAE calculations in a backtest (great for figuring out optimal stop loss levels)
Multi-threaded analysis window
64-bit version (important for backtesting lots of symbols)
Wait for backfill in analysis windows (crucial for real-time trading)

There's no contest, really.

What about Amibroker Ultimate?

This includes the Professional Edition, plus the AmiQuote data downloader and the AFL Code Wizard.

The AmiQuote tool downloads free daily data from internet sources. Any trader on the list will quickly want to use something more reliable than this.

I haven't talked to a trader yet who relies heavily on the AFL Code Wizard, so I don't believe that's necessary.

Conclusion: just get the Professional Edition.

-Dave

P.S. Think you have trading skill but nothing concrete to test? Start with the proven backtest included in my Amibroker AFL Course and make it your own. Get Instant Access

Guest Appearance on the SMB Podcast and Upcoming IBKR Webinar

2026-01-13T15:30:00-05:00

Garrett and Tim (long-time list members) had me on the SMB Podcast several days ago to talk about backtesting, automated trading, and a wide range of topics.

LISTEN NOW »

Here are the show notes:

In this episode of the Trading Floor podcast, we dive into the essential process that every trader must understand to avoid failure in their trading strategy. Host Garrett and co-host Tim engage with expert Dave Mabe, who emphasizes the importance of backtesting and developing a solid strategy. Viewers will learn the significance of taking ownership of their trading, optimizing strategies through data analysis, and the art of skipping bad trades, making this video a must-watch for active and day traders looking to enhance their execution and decision-making skills.

00:00 Why Most Traders Get the Same Results (and Why Some Don’t)
02:10 Dave Mabe’s Journey: From Discretionary to Fully Systematic
05:00 Strategies Don’t Need to Be Unique to Be Profitable
08:45 Optimization Is the Real Edge
11:20 Why You Must Build Your Own Strategy
13:45 How Dave Finds New Strategy Ideas
16:00 Turning Losing Trades into New Strategies
18:00 Backtesting as a Truth Serum
22:15 Why Your First Backtest Should Cast a Wide Net
27:00 Can You Cast the Net Too Wide?
31:00 Strong Signals vs Wide Exploration
37:40 The Power of a Column (Indicator) Library
44:05 If You Could Only Use 3 Indicators Forever
59:00 Profit Targets, Partial Profits, and What the Data Says
01:12:10 The Billboard Message Every Trader Needs to Hear

Thanks, Garrett and Tim - that was a lot of fun.

Sharing is caring!

If you enjoyed this episode, please consider sharing it with a few friends who might find it useful. Thanks!

-Dave

P.S. Interactive Brokers is having me on another webinar this Thursday at 2pm ET. The title is Create Your Own Trading Strategy without Curve Fitting. Note that even if you aren't able to attend, you'll be able to view a recording afterwards if you register:

Next Steps with Amibroker

2026-01-12T15:30:00-05:00

On this week's episode of Line Your Own Pockets, I continue helping Michael create a first backtest in Amibroker.

You might think "backtesting is backtesting," but we cover many of the differences between RealTest and Amibroker, as well as their implications.

We discuss:

What makes AI so bad at generating good AFL code for a backtest in Amibroker
The better you get at understanding how AFL works, the better your use of AI gets
How a column library makes all the difference in creating P&L
Quick backtests can promote bad habits

And much more...

I also mentioned the new MabeKit AFL Generator tool.

LISTEN NOW »

-Dave

P.S.

Amibroker users: are you trying to use ChatGPT to create a backtest only to discover how bad the LLMs are at coding Amibroker's language? You're not alone! You need my Amibroker AFL Course. It comes with a demo strategy that serves as the perfect starting point for any strategy you want to create.

Get instant access to the Amibroker AFL Course

Automating My Way to Financial Freedom - Quant Room Podcast

2026-01-09T15:30:00-05:00

Marcus C. had me on the Quant Room podcast a few days ago to talk about systematic trading.

We touched on the following topics:

Parallels between athletics and trading
The importance of reinventing yourself as a trader
My time creating StockTickr, the first online trading journal that I sold to Trade-Ideas
The value of normalized columns in a backtest
Handling slippage in live trading

And much more.

CHECK OUT THE EPISODE NOW »

Sharing is caring!

If you enjoyed this episode, please consider sharing it with a few friends who might find it useful. Thanks!

-Dave

P.S. Are you in a drawdown and ready to quit? Join the other traders who reversed their drawdowns and are printing money with MabeKit.

"Can I Do Sector Relative Strength Calculations in Trade-Ideas?"

2026-01-08T15:30:00-05:00

Here's a reader question from MabeKit subscriber, Jeremy Q. (name used with permission, question lightly edited for clarity).

Jeremy Q:

Is it possible to build a very specific sector relative strength Top List in Trade-Ideas? Custom baskets of stock, robotics, photonics, fiber, satellite, etc.

Average the RVOL, %change from Open, etc, and then rank them?

I'm using Gemini to do a version in Python now, but I have Trade-Ideas and I thought you might have an easier solution.

Dave:

Yes, Trade-Ideas has a nice way to do this based on one of my favorite features I added to the program over a decade ago.

On both the alert and top list windows in Trade-Ideas, there's a setting you can turn on called CSV Logging.

In the main TI window, go to Tools, Options and check the box for Display the CSVLogger tool. See image below:

Once enabled, you'll now see an Alert Logging option at the bottom of the context menu on all your alert and top list windows:

Check the Alert Logging box in a window, and it will write a CSV file to the TradeIdeasPro directory every time there's an update to the window.

Now, you can set up top list windows for whatever sector you want to track, along with thresholds for each.

Then you can process these CSV files and do interesting things with them.

For example, you could have a Python script parse them and compare stats across sectors.

An even simpler idea might be to create a single top list that spans all sectors, add the sector as a column, and use a minimum value of 3 for relative volume.

Now you can parse a single CSV file and group by sector to show sectors with the largest number of symbols trading significantly above their relative volume.

There are lots of creative things you can do with the real-time CSV output if you put your mind to it.

This unlimited flexibility is why I love this feature so much.

Thanks for sharing with the group, Jeremy!

(BTW, I'm pretty sure this one feature has created more P&L for traders than any other feature I added to Trade-Ideas - by a large margin. But that's a story for another day.)

-Dave

P.S. Wish you could backtest your ideas - without spending months learning to code? Run your first backtest in an afternoon using my Amibroker AFL Course. Get Instant Access Now

"Should I Use An Online Course To Learn Python?"

2026-01-07T15:30:00-05:00

Here's a reader question from Lindee (name used with permission, lightly edited for clarity):

Lindee:

I signed up for PyCharm but have not made any headway.

Instead, as a beginner to get any kind of traction, do you recommend one of the games like Codify or Codefinity for learning Python? I could add it to my Duolingo practice, where I have maintained a long streak.

Dave:

I've seen these online courses for learning programming, and I've never really paid them much attention.

The issue is one of motivation.

How can you really get motivated to learn something when the tasks in these courses are, by definition, arbitrary and pointless?

The benefit at the end is vague and unclear.

You'll almost always run out of steam when attempting them, and you won't retain much knowledge.

A far better approach is to pick some aspect of your trading workflow that could benefit from automation.

And challenge yourself to automate it and work it into your process.

The real benefit here is that from the moment you put it in place, your life improves.

Your trading gets a little bit better (sometimes a LOT better).

You can feel the improvement in your workflow every day from then on.

The "learning Python" part is secondary.

Once you do this, you'll start noticing other ways to make your process better.

Do this enough, and it will be impossible NOT to improve your P&L.

Thanks for the question, Lindee!

-Dave

P.S.

Does it feel like your strategy works for everyone but you?

Make your strategy profitable with MabeKit. Get Started Now

Next Steps When You've Had Discretionary Success

2026-01-06T15:30:00-05:00

So you've had success by manually trading a strategy.

However, you know that a systematic approach will be more robust and sustainable in the long run.

And a lot less stressful during the trading day because you'll be following a script versus making decisions - a subtle but crucial difference.

I see lots of traders in this situation, and I've helped many make this transition.

But where's the best place to start?

There are two approaches to take here, and one of them is significantly harder.

First, the hard way: completely replace your current manual strategy with an automated version.

This is much harder than it seems for a variety of reasons.

It's often hard to completely recreate all your discretionary rules in code for a backtest
If you are able to recreate it, you'll have a distinct cutover point where you go from 100% manual to 100% automated - the step always takes longer than you imagine
Transitioning from a known quantity to a fundamentally different approach is hard

All these things are magnified when you're producing a steady P&L from your manual strategy.

There's going to be pressure for you to make it work at the cutover point.

Setting an artificial deadline for yourself in trading is almost always a bad idea.

A much better approach is to continue trading your manual strategy (it's producing nice profits - don't change it yet) and create a tangential strategy designed from the beginning to be automated.

There's no need to rip out something that's working.

Your automated approach can operate independently and in parallel to your working manual strategy.

It will be a lot less stressful, and you'll have a much better chance of success.

A benefit of this approach is that you'll have an excellent way to gauge your automated strategy by comparing it to your familiar manual strategy.

But the best part is that the automated strategy ends up being completely additive to your trading business and your P&L.

And then you'll be in a much better position to make changes to your manual strategy.

-Dave

P.S. Do you wish you had a strategy that actually made money? Create your own in minutes, not months with MabeKit.

Get Instant Access

Getting Started with Amibroker

2026-01-05T15:30:00-05:00

In this week's episode of Line Your Own Pockets, I offer advice and feedback to Michael, who is learning to use Amibroker for the first time.

He's coming from RealTest, so we go over the similarities and differences between the two platforms.

We discuss:

How RealTest is great for daily data, but hits a wall for most intraday trading strategies
Amibroker is not just a backtester; it’s a full charting, analysis, and execution environment.
Backfilling with IQFeed versus Polygon (there is really no contest)
Best practices for databases in Amibroker
How using the template that comes with my AFL course is crucial for using LLMs (see P.S. below)

Much more...

If you're thinking about using Amibroker, you don't want to miss this episode.

LISTEN NOW »

-Dave

Get instant access to the Amibroker AFL Course

"Can I Backtest a Scalping Strategy in Amibroker?"

2026-01-02T15:30:00-05:00

List member Kacper sent in this question about a scalping strategy that works well for him. He's curious if you can backtest this strategy using Amibroker.

Kacper:

My strategy is a very short-term scalping strategy, usually biased towards the long side. I'm a momentum trader, so I'm in and out in approximately 10 seconds, sometimes longer, sometimes shorter.

Is it possible to backtest and also automate such fast scalping trades using Amibroker?

Dave:

I don't have much experience backtesting a strategy on such a small timeframe in Amibroker, but it should work.

I just set up a new database in Amibroker with 1 million 1-second bars using IQFeed as the data source.

I added the SPY to the database and backfilled, and I get data going back to 11/5 (almost 2 months).

Here's a screenshot showing the Quote Editor in Amibroker that shows what's in the database for a particular symbol:

Here are the options for the database size in Amibroker:

I'd be careful using a timeframe this small, though. Any issues with small timeframes are going to be magnified here, so keep that in mind.

Thanks for the question and for sharing with the list, Kacper!

Next time, I'll share a plan for a common scenario: discretionary traders who've had some success and want to start backtesting.

-Dave

P.S. Afraid to size up because you don’t trust your edge? Build confidence to trade your strategy with bigger size with MabeKit.

Get Instant Access

Changes to Your Routine for 2026

2026-01-01T15:30:00-05:00

"Routine, in an intelligent man, is a sign of ambition." - W. H. Auden

Your trading habits directly translate into results.

Professional chefs don't need to be reminded to sharpen their knives.

If your 2025 results weren't as good as you hoped, how will 2026 be different?

What's your concrete plan to sharpen your trading knives in the new year?

Are you using a butter knife without realizing it?

Your process and tools are everything.

One of the biggest turning points for traders is when they stop trying to copy what someone else is trading and create a process for making their own edges.

Have you made that shift yet?

Happy New Year!

-Dave

Get instant access to the Amibroker AFL Course

Why Trading Stocks Is Easier Than Futures

2025-12-31T15:30:00-05:00

Here's a reader question that comes up a lot, most recently from Karl J. (name used with permission, question lightly edited for brevity).

Karl J.

I have been using Tradestation for a long time. Focused mainly on futures, I can consistently achieve around a 65% success rate. My biggest problems are getting out early by moving stops, being too chicken to take a good trade, and other stuff that I think automation could help with.

I would love to hear your opinion about why you think I can do better with stocks instead of futures.

Dave:

One thing I've learned to identify in traders is when they have more potential for success than they realize.

Perhaps the strongest indicator for this is when you're trading a futures contract systematically and have had results even remotely resembling mild success.

My consistent message to traders who reach out to me in this situation is: you'll have more success trading stocks.

This often surprises traders when I tell them this, so I've written this post to explain why.

The first reason is pure math: if you can find edge in a single instrument, imagine what you could find if you applied the same process to the thousands of stocks in the US equities market.

The strategies you'll find for trading will yield more trades, stronger profitability, and greater staying power with stocks, just based on the numbers alone.

Second, your pool of competitors is smaller. Almost every trader on the planet has a chart of the SPY on their screens.

It's easy to create a rudimentary program to backtest a single instrument. (I'm looking at you, TradingView.)

Anyone can do that with almost no effort.

Add the fact that there's so much liquidity in the ES, and you're now competing with institutions as well.

It's much harder to create a backtest that works across thousands of stocks, so your competition is significantly smaller.

So if you've had any level of fleeting success trading a system in the ES or another futures contract, you're already shown that you can accomplish the hardest part: creating a profitable strategy.

You've already developed execution experience as well, which will crossover to stocks.

Once you get the basics of trading stocks, there's no reason you shouldn't be able to create a much stronger edge that trades a lot more frequently.

This became super clear to me when I abandoned 4 profitable futures strategies several years ago - there was just more profit potential in the edges I find in stocks.

Great question, Karl, and thanks for sharing with the list.

-Dave

P.S. Do you wish you had a strategy that actually made money? Create your own in minutes, not months with MabeKit. Get Instant Access

Ship Something Every Day

2025-12-30T15:30:00-05:00

There's a concept in software development called "ship something every day."

It sounds easy, but when you're creating software that many people use, it's hard because you don't want to break things.

To get to that point when developing software, there are a lot of guardrails you have to put in place to make things build smoothly and roll out to production seamlessly.

But once you get that foundational architecture in place, you're off to the races.

Without the infrastructure in place, any change feels monumental.

And if you go for extended periods without making any changes to the software - even trivial ones - it becomes harder to make any change.

"If it ain't broke, don't fix it" mentality creeps in, and the entire process fossilizes.

The same phenomenon can happen with your trading strategies.

If it's working well enough, you postpone changes, and then come the excuses.

"I don't want to make a change, because it might be curve fitting."

Imagine how much better your trading would be if you made one improvement every day.

No matter how small the improvement, do something every day to get better.

With this mentality, you'll begin to generate new ideas for improvement.

Within a month, you'll be a completely different trader.

In a year, you'll be crushing it.

-Dave

P.S.

Are you sick of second-guessing yourself every time you click buy or sell?

Trade with conviction using MabeKit. Get Instant Access

How To Run Your Trading Like A Franchise

2025-12-29T15:30:00-05:00

You've all probably heard how you should "treat your trading like a business."

But most small businesses fail within 5 years.

So you should treat your trading not like any small business, but the type of business with a much higher success rate: a franchise business.

In this week's episode of Line Your Own Pockets, we discuss the actual nuts and bolts of what that means:

Systematize everything
A process for eliminating low-value work
What makes sense to outsource and what you should keep in-house
Make your trading survive without you

And much more...

LISTEN NOW »

-Dave

P.S. Wish you could backtest your ideas - without spending months learning to code? Run your first backtest in an afternoon using my Amibroker AFL Course:

Get Instant Access

What is the CSV Format and Why Is It Useful?

2025-12-26T15:30:00-05:00

Here's a great question from another reader, Dr. D. (Name used with permission)

Dr. D:

What is the CSV format and how is it used?

Dave:

I love this question because the CSV format is one of my favorite hacks.

CSV stands for "comma-separated values."

It's a way to organize data in a spreadsheet format.

While there are certainly more convenient formats in certain contexts, the CSV format has two major advantages that make it stand the test of time.

Minimal markup, making it efficient to read and store
Widespread interoperability

Lots of programs know how to create files in the CSV format, and lots know how to read files in the CSV format.

You can export backtests from Amibroker, Trade-Ideas, RealTest, Python, and many others into the format.

Simply double-click on a CSV file in Excel, and it will know exactly how to handle it.

In fact, I use it so often that I set CSV as the default format for saving a file in Excel.

The CSV format isn't perfect, but after 28 years of using it as my default, it's hard to imagine an alternative being more convenient.

Great question, Dr. D.

-Dave

P.S. Speaking of CSV files, I've recently documented a generic CSV format for backtests to feed to the Strategy Cruncher. Using this generic format allows you to use any software you want to create a backtest to get optimized into profitability without curve fitting using MabeKit. Here's the doc.

Are Points and Figure, Heikin-Ashi, or Renko Charts Worth Using?

2025-12-25T15:30:00-05:00

Here's a reader question from Dean J. (name used with permission):

Dean J.

Do you or have you used different types of charts, such as P&F, Heikin-Ashi, Renko, in trying to create strategies?

Dave:

I've literally never used any of those chart types.

I'm not morally opposed to using them, I just have never felt the need to use anything other than candlestick charts.

Charting is for efficiently visualizing price action.

Anything that complicates that process needs to be viewed skeptically and justified, with your default stance being to exclude anything that adds complexity.

For this reason, my charts are free of any clutter of indicators that don't have a direct impact on a particular strategy.

Similar to indicators, these fancy chart types would simply be a distraction.

Keep your charts as simple as possible, then look closely and try to make them even simpler.

If I thought any of these chart types would give a perspective that would improve a strategy, I would add a column to my column library that captured that perspective instead.

Adding columns to your column library would be a much better use of your time.

Great question, Dean - thanks for sharing with the list!

-Dave

P.S. Do you wish you had a column library that would tell YOU how to make your strategy profitable? My column library is now included with MabeKit

You Are Backtesting, You Just Don't Realize It

2025-12-24T15:30:00-05:00

Backtesting is a trading superpower.

When I ask traders if they have experience with backtesting, most of them say no.

But the truth is, many of them do have experience backtesting - they're just not calling it that.

If you're keeping a log of all the trades you're making, then you're already "backtesting" in some sense.

Running a backtest is not all that different from analyzing your trade journal.

The difference is that a backtest is entirely theoretical, while the trades you actually took are real.

Think about how long it would take to make trades, log them to a journal, and then analyze them once enough trades have accumulated.

It could take months or even years.

Backtesting is your cheat code to trading confidence.

And you're probably already doing it on some level without realizing it.

-Dave

P.S. Do you wish you had a strategy that actually made money? Create your own in minutes, not months, with MabeKit

More Ideas or Faster Strategy Creation?

2025-12-23T15:30:00-05:00

OK, quick question for you.

Let's say you could choose between one of these two options:

Create 10x the ideas for trading strategies (starting points that you could create a backtest and optimize from)
A process that could backtest and optimize an idea 10x faster than what you're currently doing

You have to choose one but not both.

Which do you choose and why?

Hit reply and let me know.

-Dave

The ICE Method for Prioritizing Strategies

2025-12-22T15:30:00-05:00

In this week's episode of Line Your Own Pockets, I discuss a prioritization method I implemented during my time as CTO at Trade-Ideas.

It worked so well that I've modified it for use by traders in prioritizing their work.

Let's say you have two ideas for strategies. They both have varying trade counts and styles. They differ from what you currently trade. But you have more confidence in one idea than the other.

Which idea do you work on first?

It's unclear!

This simple framework allows you to decide which one you should work on first.

LISTEN NOW »

-Dave

P.S. Are you in a drawdown and ready to quit? Join the other traders who reversed their drawdowns and are printing money with MabeKit:

Get Instant Access

What's a Good ROI for a Strategy?

2025-12-19T15:30:00-05:00

Here's another question from Matthew A., a long-time reader from way back in my StockTickr days in the 2000s (!!).

(Name used with permission)

Matthew A.:

What would you consider a decent “Return on Investment” for any strategy, and during back testing, how many years of consistency do you look for?

Dave:

Most new traders evaluate strategies based on the annual percentage return.

But that's the wrong way to think about it.

The right way to evaluate short-term trading strategies is by the smoothness of the equity curve.

Experienced traders recognize that drawdowns are the most challenging part.

One glance at the equity curve is going to give you more information than any combination of metrics can.

A smooth equity curve provides stability and flexibility.

A strategy with a smooth equity curve can scale in various ways.

A strategy with a good "ROI" but large drawdowns is going to be very difficult to scale to significant size.

That's why I always evaluate the equity curve - every other metric I look at is a distant second in comparison.

Remember: every trader who ever quit trading did so during a drawdown.

Thanks for the question and for sharing, Matthew!

-Dave

P.S. Think you have trading skill but nothing concrete to test? Start with the proven backtest included in my Amibroker AFL Course and make it your own.

Get Immediate Access »

Should You Use Ranking in Your Strategy?

2025-12-18T15:30:00-05:00

Here's another excellent question from a reader, Radek R. (name used with permission, question edited lightly for readability)

Radek R.

I have been experimenting with the columns and filtering trades, and it seems to improve the strategy. However, since there are usually more trades than available slots, I am not sure how to select the ranking method
to decide which trades to take. The effect of PositionScore looks quite dramatic, so it would be great if there were a way to automatically select the best ones. Do you think this can be done without repeating the backtest each time?

From your podcast, I heard that you generate a lot of trades at the beginning and then narrow them down with filters. I tried something similar by setting MaxOpenPositions to a high number, allowing me to capture all trades.

My concern is that when I later reduce it to the target number of slots, the columns may no longer be predictive. I would really appreciate your view on this.

Dave:

Let's define rank and what it means in this context. You have a system with more trades than your buying power can handle. Instead of taking all the trades or the first X trades until you run out of buying power, you decide to rank the top X trades by day by some factor and then take those.

I've tried using rank as a way to filter trades in a system, but I always abandon it because it increases complexity, ultimately based on a variable that changes over time: your account size.

First of all, the trades in a system don't care about their relative ranking to one another, so I've always felt a rank used in this way is arbitrary.

Because of that, it doesn't provide a true path to confidence in your system.

Secondly, your account size will change over time. Making decisions about your strategy that rely so much on your account size means you'll be reoptimizing periodically for an arbitrary reason (remember: the market doesn't care about your account size or your feelings.)

Using rank like this is a form of premature optimization.

I prefer to remove any arbitrary constraints and have my backtests assume unlimited buying power. (That is the first step I take before running any backtest.)

That way, you're set up to optimize your trading system for whatever your account size grows to. (And if you're doing this right, your account will be growing a lot.)

If and when you run out of buying power, dig in and figure out at that point how to adjust your system to account for it.

Using rank is trying to address that issue as you optimize, which is the wrong time.

Keep it simple!

Great question, Radek! Thanks for sharing with the group!

-Dave

P.S. Do you have periods of trading success, only to see your strategy give it back? What would it look like to get rid of the biggest losing trades from your strategy?

With MabeKit, you can.

Get Instant Access Now »

How To Build Automated Trading Systems with Dave Mabe

2025-12-17T15:30:00-05:00

Anthony Nieto from the Investor Underground's Trader's Journey Podcast had me on recently to discuss backtesting and automated trading.

LISTEN NOW »

Here are the show notes from the episode:

How Dave’s engineering background shaped his approach to markets and risk.
Journaling trades and using simple data analysis before backtesting.
The moment backtesting became central to his process
Differences Dave sees between retail and prop traders when they bring him strategies.
The full lifecycle: from hypothesis → live capital.
Common backtesting mistakes: overfitting, data mining, and more.
How Dave thinks about sizing up a strategy.
The tech stack: data sources, backtesting platforms, and building an automation pipeline

Sharing is caring...

If you find this episode useful, please share it with two friends who might also benefit. TIA!

-Dave

P.S. When you're ready to take your trading to the next level, MabeKit is the key. Here's what one RealTest trader said about it:

"The MabeKit Column Library is absolutely essential for using RealTest. It has a dual purpose: it immediately provides columns whose predictive value the Cruncher can identify, and it also serves as inspiration for adding new columns. Practically speaking, without the column library, I wouldn’t be using RealTest."

Get Instant Access to MabeKit

Automation Versus AI

2025-12-16T15:30:00-05:00

[Note: I have a backlog of excellent reader questions that I'm working through. If you've asked one and I haven't responded yet, please be patient.]

Here's a good question from Jenny M. on automation and AI (name used with permission):

Jenny M:

Automating my trades is very interesting to me. What's your view on automation vs AI?

Dave:

It might sound strange to some traders, but I view automation and AI as very different.

The most overrated concept in AI right now is "agentic AI" - that is, having LLMs do something automatically on your behalf.

Has anyone trusted an AI agent to book travel for them end-to-end? No.

If you can't trust it for booking travel, then there's no way it's going to reliably answer a question like "what's the best way I should trade AAPL right now?"

I would argue even super-intelligence isn't going to help much with that question.

Pontificate all you want about how AI is going to do this or that for you in the future, but the better question is, how can it increase your P&L right now?

Think about your process for creating trading strategies.

What are the biggest bottlenecks? Be specific.

Now ask an LLM how to solve this very specific problem you've identified in your process.

Maybe something related to automating your trades.

Maybe it can tutor you in learning a new framework that will ultimately make your process faster.

The more detailed the context you can provide, the better answers you'll get from an LLM.

Do this regularly, and your P&L will follow.

Great question, Jenny, and thanks for sharing with the group!

-Dave

Wish you could backtest your ideas - without spending months learning to code?

Run your first backtest in an afternoon using my Amibroker AFL Course.

How Much Does Speed Matter in Trading?

2025-12-15T15:30:00-05:00

In this week's episode of Line Your Own Pockets, we take on a topic submitted by Isaac, a trader I work with.

How much does timing matter? Signal to execution time, tick data versus 1 minute bar data for backtest/signals, etc.

This is a great question because technically minded people often tend to over-engineer solutions.

(I find myself doing this frequently!)

These rabbit holes can be huge time sucks for no real benefit.

We discuss:

When timing/speed matters and when it doesn't
The types of trading strategies where latency is likely the bottleneck
How rushing to solve problems can be counter-productive (waiting can reveal simpler solutions)
Concrete steps to determine if latency is really an issue and how to address it

And much more...

LISTEN NOW »

Thanks for the excellent question, Isaac!

-Dave

P.S.

Why is every other trader printing money while you’re stuck?

Close the gap with MabeKit.

Better Strategy Starting Points

2025-12-12T15:30:00-05:00

Here's a reader question from list member Matt H. (name used with permission):

Matt H.

How do you think about universe filters? I have been struggling with this all month because each back test takes 5-7 hours and I get as many as 799,331 rows of trades when starting from 2016. Which then need to be analyzed to come up with a filter or stoploss/profit target level to test. It makes testing ideas really slow. I'm only able to run about 3 backtests per day.

Dave:

First, some background.

As you've heard me preach before, most traders who start backtesting try to create a "final version" of their strategy with their first backtest.

This is, by far, the most common mistake systematic traders make.

You'll end up wasting so much time with that approach, and if you happen to end up with a profitable strategy, it will be mostly luck.

But more importantly, you'll end up with a strategy that could be far more profitable.

Once traders begin to understand this, their workflow improves by using much better starting points.

That is, the first backtest is more about collecting data in a way that will lead to a profitable strategy.

But many traders often overcorrect here and create a starting point with far TOO many trades.

If your starting point has more than 100k trades, it's almost definitely too large.

With that many trades, your backtest is guaranteed to contain a high percentage of noise.

So when you start optimizing, you'll be fitting to that noise.

This is where universe filters come in handy.

Unlike applying filters that are predictive and directly improve the profitability of your strategy, a universe filter fences in the set of stocks your strategy is willing to consider.

So a universe filter isn't providing edge per se, but it's culling your initial set of stocks to a reasonable starting point.

If your strategy has 700k trades, it's going to contain stocks like this one:

At first glance, the chart seems reasonable.

But when you look closer, you'll see that there's hardly any volume there. In fact, on most trading days, there's no volume at all!

A good universe filter eliminates this noise before it's even considered for your strategy.

That will make your entire process better:

Your backtests will be much faster
The starting points will be "cleaner" - i.e., not tainted by so much noise
Your optimization process can be solely focused on edge rather than noise removal

More signal, less noise.

Good question, Matt - thanks for sharing with the group.

-Dave

P.S. Does the market feel like it changed and left your edge behind?

Adapt instantly with MabeKit.

Amibroker Exploration Demo

2025-12-11T15:30:00-05:00

One of the most useful features of Amibroker is the Exploration.

It allows you to view bar data, indicator values - any derived data you'd like - from a completely customizable interface.

One thing traders often struggle with in Amibroker is dealing with dates and times.

So I thought I'd put together a video showing the power of an exploration in Amibroker to solve a real-world problem that traders run into with dates and times.

In this video, I show:

How to add custom columns to an exploration
Setting the width of each column to appear perfectly without manual adjustment
Showing some data with a custom background color for highlighting importance
How to remove the default columns to completely customize the interface

View the Amibroker Exploration Demo

-Dave

P.S. Wish you could backtest your ideas - without spending months learning to code?

Get the strategy included in the Amibroker AFL Course.

How To Get Confident in Your Trading Edge

2025-12-10T15:30:00-05:00

Trading is easy if you don't trade with meaningful size.

It's much harder to trade when you start increasing your position size to make serious profits.

And the hardest part is trading through drawdowns.

If you aren't able to do that, then there's a ceiling on how much P&L your trading can generate.

Of course, drawdowns suck. Bad.

If you're in a drawdown, doing all this work, and still losing money, why on earth would you keep trading through it?

The only way to do it is to have confidence in your strategy.

Confidence that there's a strong edge that will continue into the future.

Where does that type of confidence come from?

There are only two sources:

Experience trading the strategy day in and day out for an extended period
Backtesting

A lot of traders consider backtesting too hard, but when you think about it this way, it's the cheat code.

It's the shortcut to confidence.

Now imagine that every time you took a trade, you had a mountain of evidence supporting your reason for the trade.

What if you never took a trade without overwhelming evidence that you have an edge?

How much better would your results be?

-Dave

P.S. Tired of hesitating for one second and missing the entire move? Get confident in your trading with MabeKit.

Successful Traders Have This One Trait in Common

2025-12-09T15:30:00-05:00

“One day I walked away from the empire of the expertise of others.” - Gabrielle Calvocoressi, poet

My wife showed me this quote from a book of poetry she's reading.

Gabrielle turned the corner when she started ignoring the advice of the so-called experts.

There's more in common between traders and artists and poets than you might think.

Think of successful musicians.

How many of them still do covers of someone else's music?

How many artists can you name who are famous for creating replicas of another artist's work?

The answer is, of course, zero.

The same is true for trading.

The reason you see other traders doing better than you is that they're not trying to be someone else.

They're not getting rich in a trading room following the stock picks of some guru who's good at getting traders to sign up for their trading room.

Like Gabrielle, successful traders have long since ignored the "expertise of others."

When will you walk away from it?

-Dave

P.S.

Does it feel like your strategy works for everyone but you?

Make it work for your data with MabeKit »

Portfolio-Level Backtesting: Essential or Waste of Time?

2025-12-08T15:30:00-05:00

In this week's episode of Line Your Own Pockets, Michael and I butt heads over portfolio-level testing.

This feature is one of the key differences between RealTest and Amibroker.

I understand the value of it, but I think using it when creating a strategy falls in the category of premature optimization.

Let's just say Michael disagrees. :-)

LISTEN NOW »

Is this just a matter of day trading versus swing trading?

What do you think?

-Dave

P.S. Are you sick of second-guessing yourself every time you click buy or sell?

Trade with conviction using MabeKit.

Treat Your Trading Like THIS Kind of Business

2025-12-05T15:30:00-05:00

In yesterday's post, I said you should NOT treat your trading like a business.

Because most small businesses fail after just 5 years, simply treating your trading like a business isn't good enough.

But there is a type of business that has a much higher success rate than the average small business.

(A couple of astute readers guessed correctly.)

The answer is a franchise.

Why?

The reason is simple. The owner of a franchise business has designed it from the ground up to operate independently of their direct involvement.

That's the whole point of a franchise.

The ceiling for a business is much lower if the owner has to be heavily involved for it to function.

A business can't scale if the owner has to be on site at every location, making decisions.

OK, so what are the lessons here for your trading?

Systematize everything.

Are you making decisions during your trades rather than following your pre-defined script?

If you are, you're like the owner who needs to be at every location for the business to function.

How "involved" are you in your trades?

How much more capacity would your trading have if you weren't directly involved in every trading decision?

How can you get there?

Over the next few days, I'll share ways to transform your trading from a struggling small business into a growing franchise.

-Dave

Don't Treat Your Trading Like a Business

2025-12-04T15:30:00-05:00

You've heard this common wisdom:

Treat your trading like a business

But if you look closely at the failure rate of small businesses in the U.S., it's surprisingly high.

22% fail in the first year.

50% fail in the first five years.

And a whopping 65% fail by year ten.

But did you know there's a specific kind of business that has a MUCH higher success rate than average?

Any guesses what it is?

More tomorrow on what business this is and what it means for your trading.

-Dave

P.S. Amibroker users: are you trying to use ChatGPT to create a backtest only to discover how bad the LLMs are at coding Amibroker's language? You're not alone!

You need my Amibroker AFL Course. It comes with a demo strategy that serves as the perfect starting point for any strategy you want to create.

Get instant access to the Amibroker AFL Course

Increase Max Number of Bars in Amibroker

2025-12-03T15:30:00-05:00

When I install Amibroker on a new computer, there are a few steps that I take immediately.

But the very first one is something simple, but it unlocks a key capability for my backtesting.

By default, Amibroker allows up to one million bars per symbol in the local database when using IQFeed to import data.

(Important note, this limit doesn't apply if you're "manually" importing data from, say, Polygon. It only applies if you're using a plug-in like IQFeed or eSignal to backfill your data.)

In the Database Settings, it tells you that corresponds to 8 years of 1-minute bar data per symbol (in reality, it's less than that when you include all pre- and post-market data).

When you try to put a number larger than 1 million in that field, Amibroker gives you an error message.

However, there's a way to modify it to allow larger numbers for this setting.

(Warning - it involves making a change to the Windows Registry, which you should always do very carefully.)

Bring up the Registry Editor from the Start menu in Windows. (Type registry when the Start menu is in focus.)

Navigate to the following registry key:

HKEY_CURRENT_USER\Software\TJP\Broker\Settings

Right-click on the Settings folder and choose New -> DWORD (32 bit) Value.

For the name of the value, use MaximumNumberOfBars.

For the Value data field, choose Decimal for the Base radio button and enter a value higher than 1 million.

I use 1000000000 for the value, so I never run into the limitation:

With that set, I can use a much larger value for the Number of bars field in my backtesting database:

With a value of 3000000, I have data all the way back to 2008 for AAPL.

That allows me to backtest using a much larger window, if I so choose.

-Dave

P.S. Afraid to size up because you don’t trust your edge? Build confidence to trade your strategy with bigger size with MabeKit.

How To Export Data from Trade-Ideas

2025-12-02T15:30:00-05:00

Last week, a trader I'm working with (a 7-figure/year trader who prefers to remain anonymous) asked me this:

Any idea how we can get a list of tickers Trade-Ideas considers US based?

It's definitely possible to export data from Trade-Ideas in this way, although there are a few steps involved.

It's easier to explain in a video, so I recorded this demonstration to show the best way to do it.

It involves using a top list and the automatic logging feature I added to the program several years ago for this exact purpose.

It also uses the Country symbol lists, which are updated daily.

Watch the video here:

Let me know if you like this video format - hit reply and let me know, and I'll do more of these if folks find it helpful.

-Dave

P.S. Are you in a drawdown and ready to quit? Join the other traders who reversed their drawdowns and are printing money with MabeKit.

How Often Should You Re-Optimize Your Strategy?

2025-12-01T15:30:00-05:00

In this week's episode of Line Your Own Pockets, we discuss a common question from systematic traders:

How often should you re-optimize your strategies?

The better you get at creating and optimizing strategies, the less you have to do it.

That's because your strategies will have more staying power.

We discuss:

How to optimize so you have to re-optimize as little as possible
How better columns directly translate into more robust strategies
Hold a rule "in reserve" so you can apply it when needed without full re-optimization
Documenting previous optimization decisions will make the next strategy better
And much more...

LISTEN NOW »

-Dave

Profitable Strategy with 5% Win Rate - Realistic?

2025-11-28T15:30:00-05:00

Here's a question from Matt H. about a strategy he's working on for the challenge I presented a few days ago (name used with permission):

Matt H:

I have a strategy for the challenge based on a consolidation breakout. I am a little unconfident, but the numbers are looking great and the equity curve, too.

very tight stop = 0.27 1min ATR. The idea - catch the ones that go up and keep going.
position size based off the stop - risking $100 per trade
profit target is 27 1 min ATR or end of day
It wins about 5% of the time but when it does it's huge.

Is this real? Or am I missing something related to execution, or do you think my backtest might have a bug?

Dave:

This is a common situation for new traders.

You can create a strategy with backtesting that looks great on paper, but quickly falls apart when you trade it in real-time.

This is a classic example.

"Very tight stop"

That means there will be more slippage than usual - probably a lot more!

"position size based off the stop"

This is usually a good idea, but combining that with a "very tight stop" and you realize the position sizes will be large, magnifying the slippage even more.

(The profit target seems reasonable.)

But the biggest red flag here doesn't come from a metric in the backtest.

Even if the backtest matches reality perfectly (which it won't), this strategy would be incredibly tough to trade psychologically.

With only 1 of 20 trades profitable, there will be long streaks of losing trades.

Then imagine the winning trade comes along - and you miss it or get a partial fill.

Talk about frustrating!

These mental aspects are important - considering them as you create a strategy should be a crucial part of your process.

Thanks for the question and for sharing with the group, Matt!

-Dave

LLMs: What I'm Doing in Amibroker is Impossible

2025-11-27T15:30:00-05:00

A list member who prefers to remain anonymous recently sent me this from a session with ChatGPT where he's trying to decide if Amibroker is right for him:

I also spoke to ChatGPT who argued the Amibroker would use terabytes of ram potentially for 10k symbols 15y and 200 custom columns.

This is ChatGPT saying what I've done for over 15 years is impossible.

In fact, I've got over 400 columns in my column library, and a backtest takes less than an hour to complete.

It's easy to be wooed by the fake confidence in ChatGPT and other LLMs.

Don't be fooled.

LLMs are incredibly powerful, but using them proficiently requires practice and discernment about what they're telling you.

-Dave

P.S. Tomorrow is a half-day, so don't forget to close your positions before the earlier close. This is a good time to test your half-day logic in your code.

Why Are LLMs So Bad at Trading?

2025-11-26T15:30:00-05:00

I use LLMs a lot.

I think they're simultaneously the most overhyped and underhyped tech we've seen in a long time.

But are they good at trading?

The answer should be obvious, but here's some proof to show how bad they are at it.

Someone set up a trading contest - with real money and real trades - and pitted each LLM against each other.

Here's a snapshot of how it's going. Spoiler: they're all lighting money on fire.

This should not come as a surprise - there are several reasons LLMs are terrible traders.

The primary reason is that LLMs are trained using data on the public internet.

In that way, they're literally trained to follow the crowd and therefore lose money trading.

Just try finding an idea for a great trading strategy by searching Google.

There's a great lesson for traders here.

How is your trading unique? How is it different than what the masses are doing?

What is your process for creating more unique ideas for strategies over time?

LLMs are great for lots of purposes, but creativity isn't one of them (yet).

-Dave

A Generic Portfolio Analyzer Submitted By a Trader

2025-11-25T15:30:00-05:00

A few days ago, I suggested that you don't need any particular tool to analyze a portfolio of backtests.

In fact, this task is the perfect project to improve your AI chops and have ChatGPT create a generic Python script that can work across backtests from any platform.

Long-time list member, Anthony S., took up the challenge (name used with permission, lightly edited for readability):

Anthony S.:

I was considering getting RealTest to do this kind of thing.

I am running systems based on EOD data in Amibroker. As my systems are short-term long only, I was concerned about concentration risk and wanted to do exactly what you mentioned. My assistant, Claude, and I discussed the pros and cons of switching to RealTest, but neither of us considered this approach LOL.

This is a very straightforward idea to implement.

I have a working version that I really like and am happy to share with the community if you feel it has some value.

Portfolio Analyzer

It is very simple but serves my needs.

Dave:

Well done, Anthony, and thanks for sharing with the group!

I'm glad you and your team were able to tackle this. :-)

"Very simple" is almost always best in trading - more on this topic in the coming days...

-Dave

Is Moving Your Stop To Breakeven A Mistake?

2025-11-24T15:30:00-05:00

On this week's episode of Line Your Own Pockets, we answer a question I received from Emmett:

Towards the end of a recent episode, you guys started talking negatively about moving stop losses up to break even on a winning position. I found this interesting as I tend to move my stops up. The reason being that I don't like to have more than a certain % of my account at risk at any one time and so if I'm in a position to take risk off somewhere, it allows me to take on new positions or maybe add risk elsewhere. Am I thinking about this all wrong?

It's a great question that many traders eventually consider.

We discuss:

Similar to taking partial profits, moving a stop to breakeven is more about psychological comfort
Profitable trading requires tolerating discomfort, as difficult as that is at times
It seems like a simple idea to test, but it quickly adds significant complexity to a backtest
How to actually test this in a backtest

This is a great example of the platitudes you often hear from people who are good at talking about trading, but don't actually trade.

LISTEN NOW »

-Dave

An Even Cheaper Way to Get Data into Amibroker

2025-11-21T15:30:00-05:00

Last week I shared my script for importing Polygon (er, Massive) data into Amibroker.

Long-time list member, Matt H., sent me a way to import intraday data for even cheaper - free in fact!

It's not for the faint of heart, as it's not a turnkey solution, but he tells me it works.

He has offered to share his code with members of the list in this GitHub repo.

I haven't tested this, and there are some caveats to consider. For example, you need to open an Alpaca account, and the data takes a considerable amount of time to get into Amibroker.

However, if you're looking for the most cost-effective way to import data into Amibroker and are willing to put your nerd hat on for a while to make it happen, you might be interested in this.

Thanks for sharing with the group, Matt!

-Dave

Your Most Profitable Strategy...

2025-11-20T15:30:00-05:00

The trading strategy that you'll make the most money from over your trading career, you haven't thought of yet.

But the idea isn't going to come to you magically out of thin air.

It might feel that way when it happens, but it will be the result of putting yourself in a position to notice unusual market behavior regularly.

Not just when you feel like it.

Not just when it's convenient.

Not just when your TODO app reminds you.

Professional chefs don't need to be reminded to sharpen their knives.

What habit can you create for yourself today, so that in a year, you're pulling serious profits from a strategy you haven't thought of yet?

-Dave

Make Your Amibroker Code Pretty - Automatically

2025-11-19T15:30:00-05:00

If you're an Amibroker user, you might be tempted to use an external editor other than the built-in AFL Formula Editor for editing AFL files.

I've tried using Vim (my favorite text editor by far) to edit AFL files over the years.

And I always find myself returning to the built-in editor in Amibroker.

Why?

Because it's so carefully thought through, and the workflow is seamless.

Here's yet another example of that.

In the AFL editor on the Edit menu, there's an unassuming item called Prettify Selection.

When selected, it will automatically format all your code to the AFL standard style:

All your extra spaces, parentheses scattered about, etc, are standardized across the entire file in one fell swoop.

Standardization like this is important. More important than you might think.

When you see something in code that technically works, but stands out as non-standard (extra spaces, say), there's a background thread in your brain that notices it and obsesses about it.

Having these non-standard annoyances automatically handled (the technical term is "linting your code") will streamline your routine and eliminate the background threads.

-Dave

P.S. The code in the screenshot is the Amibroker template I use for each strategy I create. This is included with the Amibroker Course I'm working on, which will be released publicly soon. Add yourself to the waiting list to be notified the moment it's released.

Backtest Workflow Diagram

2025-11-18T15:30:00-05:00

One of the most rewarding aspects of writing this newsletter is attracting smart and motivated traders.

Here's a great example of that.

Long-time list member Rami A. sent me this diagram he put together with his take on my backtesting workflow.

Very impressive, Rami!

The Core Performance Metrics section is not perfect (I have strategies with Profit Factors lower than 1.75 and also much higher than 2.0), and I use more indicators than the six listed there, but the spirit of this is spot on.

Diagramming workflows like this is an underrated skill (I just coached my daughter on this exact topic this week).

Take a look and see what you think:

Any suggestions for improvements? Hit reply and let me know.

Thanks again to Rami A. for sharing with the list.

-Dave

Next Steps when a Strategy Fades

2025-11-17T15:30:00-05:00

This week on the Line Your Own Pockets podcast, we follow up with Andre, whose strategy stopped working. He sent me some more details about his strategy and how he backtested it.

Michael and I discuss the next steps for Andre to try to get his strategy back to profitability.

Topics include:

Ways to try to include more profitable trades in the system
How to add more predictive columns to improve the strategy and create new ones
How to re-optimize more smartly to create a more robust strategy with staying power
Much more...

LISTEN NOW »

-Dave

P.S. Do you have trading questions you'd like to hear answered on the podcast? Hit reply and let me know.

Cheapest Way to Get Data into Amibroker

2025-11-14T15:30:00-05:00

Several traders have asked about using Amibroker and the best way to import data.

The easiest way to import data is to use the IQFeed plugin and then backfill data.

I've used this method to import data going back to 2005 in my backtesting database.

But IQFeed is not the cheapest way.

The cheapest way is with Polygon (inexplicably renamed to "Massive" recently).

If you aren't yet sure you'll use Amibroker with real-time data, it's a great choice for backtesting only.

Polygon has a "flat files" offering that allows you to download their minute agg files.

These are zipped files that contain 1-minute bar data (Open, High, Low, Close, Volume) for every US equity on any given trading day.

This is ideal for importing into Amibroker to use for backtesting.

I like this approach for traders who are getting started because it allows them to focus on the hard part (creating a profitable strategy) in the cheapest way possible.

Once you create a strategy that looks great, then you can go down the path of trading it in real-time.

If you're a Strategy Cruncher user, you can download the scripts I use to download the Polygon files and import them into Amibroker.

Here's the documentation for how the process works.

-Dave

Why Different Volume Filters in Premarket Versus RTH?

2025-11-13T15:30:00-05:00

Several folks replied to my posts about relative volume in the premarket and asked variations of:

Why not just use "percent of average volume" across the premarket and regular trading hours? Why have different filters for volume during premarket versus RTH?

This is a great question, and there's a good reason for using two different calculations in each context.

For most stocks, it's unusual for them to be doing any volume at all in the premarket.

To try to calculate relative volume in the premarket wouldn't make sense.

Here's an example. Let's say symbol XYZ normally trades very little in the premarket (a very common situation).

Then one day it trades 100 shares.

On that day, the theoretical relative volume calculation would be:

volume today / normal volume at this time of day

Which would be 100 / $A_REALLY_SMALL_NUMBER. Which could easily be infinite.

This should point you to the simpler volume / average daily volume * 100 calculation for the premarket (I'll refer to this as the volume percent calculation).

But, conversely, if you try to apply this to regular trading hours when stock XYZ (and most stocks) trade plenty of volume, if you use volume percent, then you end up with a calculation that isn't normalized across the trading day.

The simple volume percent calculation will be in the single digits at the start of the regular trading hours, and then slowly increase to 100 as you get closer to the market close.

That is, it's not normalized by time of day.

In the context of RTH, the relative volume calculation really shines.

On a normal day, the relative volume will be 1.0 throughout the trading day.

-Dave

View Performance Across Multiple Strategies in Amibroker

2025-11-12T15:30:00-05:00

Here's a question from long-time list member, Abhishek K. (name used with permission):

Abhishek K.:

I have 2 strategies I test separately in Amibroker.

How can I get the metrics of these 2 strategies together? (similar to RealTest?)

Dave:

This is a common question for traders coming to Amibroker, but looking at aggregate performance across strategies has never been very important to me (compared to other traders).

I would put this in the category of premature optimization. (More on this topic later.)

The simplest way to do this is to open the CSV files generated from the Amibroker backtests in Excel.

Combine the results into a single sheet, then look at the Profit column across both strategies.

It's tempting to do this as a one-off task in Excel each time, but if you find yourself doing this routinely, it's a good idea to systematize it.

In fact, I think this is a great project to use an LLM to create a generic Python script that lets you combine multiple backtests and view performance.

The inputs would be the CSV files generated from Amibroker backtests.

The outputs would be whatever summary statistics you want to see (an equity curve, aggregate metrics, etc).

It's a good idea to always add command-line arguments to control the behavior of a script like this.

That forces you to think more generically, and it's an excellent habit to get into.

The goal is to create a script with flexible parameters so you can run it on any number of backtest files without having to modify the code each time.

Good question, Abhishek, and thanks for sharing with the group.

-Dave

The Best Way to Make Your Backtest Faster

2025-11-11T15:30:00-05:00

Many new traders, whether using Amibroker or other backtesters that can handle large amounts of intraday data, focus on speeding up the backtest.

And that's certainly worth doing.

But, by far, the biggest bang for the buck in this area is setting up your backtests so that you only have to run one of them!

If you're still "guessing and checking" by running backtest after backtest after backtest, you can dramatically improve your testing workflow simply by setting up your initial backtest differently.

When you add your custom library of columns to your backtest, you only have to run a single backtest!

And when you only have to run one, then it doesn't matter nearly as much how long it takes.

Your path to a profitable strategy is significantly shorter.

In fact, if you're not doing it this way, you'll very likely never end up with a profitable strategy, and if you do, it will be by accident.

-Dave

P.S. I accidentally sent a duplicate email this morning. Sorry about that! I'm updating the site, and that one snuck through while I was running this morning.

You Missed A Trade But It Comes Back

2025-11-10T15:30:00-05:00

The price blew through your planned entry, leaving you without a fill. Frustrating!

But now it comes back, giving you another chance to enter at your original price.

Do you take that trade?

On this week’s episode of Line Your Own Pockets, we go deep into this common situation.

Your default should be to take the trade if it still matches your system
There's more information to decide on - what can you add to your backtest?
What are post-entry columns, and how can they help?
How deep thinking about the issue can help you create brand new strategies

And much more…

LISTEN NOW »

-Dave

Automated Trading While At Work?

2025-11-07T20:30:00-05:00

Here's another reader question, this time from Danny S. (name used with permission, lightly edited for readability).

Danny S.:

I've been listening to the podcast, great content! I've mostly done manual trading, but also dabbled in automated trading, mainly on futures through Tradestation.

Is it reasonable to have intraday automated systems run during the day while I'm at work during EST hours? I haven't looked at Amibroker, but I am confident I can learn it. Or is that idea too risky?

Dave:

Is it reasonable or too risky?

It all depends on your risk preferences and the confidence in your strategies.

Some traders can easily overcome the mental hurdle of automated trading without constant supervision, but others feel the need to watch things like a hawk.

There's definitely a path to get there, and I've worked with several traders to become comfortable enough to do it.

Here's the thing:

It's not all or nothing - there's a continuum from completely manual to fully automated, unsupervised trading.

There's a whole range of things you can do to move down that continuum.

Every step you take down that range will improve your trading, regardless of whether you make it all the way to the last step of full automation while you're at work.

The first step is backtesting a strategy and getting it in good enough shape to trade.

Staring at a great-looking equity curve you've created is usually all the motivation you need to start taking steps toward automation.

If you've used TradeStation, you'll have no problem using Amibroker, and your backtesting will get a lot better and faster, thanks to the ability to add custom columns to your backtest.

(It's mind-boggling to me why TradeStation hasn't added that feature; there's no way I could use it without that.)

Thanks for the question, Danny S. and good luck!

-Dave

RVOL in Premarket with Trade-Ideas

2025-11-06T20:30:00-05:00

In yesterday's post, I shared a common approach for determining if premarket volume is unusual or not.

If you are a Trade-Ideas user, there are two applicable filters/columns already included in the program to use for this purpose.

The first is Relative Volume. As I mentioned in the previous post, this is often quite predictive for strategies when used in regular trading hours.

The second is the calculation you should use in the premarket. In TI, the filter is called Volume Today %.

In this screenshot, you can see both of these columns in use: Vol Today ($) and Rel Vol

I took this screenshot in the premarket, so you can see that Relative Volume is 1.00 even though both of these stocks have already done far more volume than their 10-day average volume.

It also shows clearly how the Volume Today % is calculated (divide the Vol Today column by the Avg Vol (10D) column and convert to a percentage).

-Dave

P.S. I'm considering sharing a few of my go-to Trade-Ideas alert windows and toplists that I use regularly. These are not trading strategies per se, but views of the market I use to review the day and understand what's moving. If you're a Trade-Ideas user and this interests you, let me know by clicking this link:

Relative Volume in the Premarket

2025-11-05T20:30:00-05:00

I made a guest appearance on SMB Capital's Bionic Trader yesterday, and there were lots of great questions after my presentation on backtesting software.

One was: "Are there certain columns that the Strategy Cruncher identifies routinely as predictive across strategies?"

There are definitely a few, and one of them is Relative Volume.

With the increase in premarket trading over the last few years, there has been more interest in calculating Relative Volume in the premarket.

But I think most traders think about this calculation in the wrong way.

Even though there's more premarket trading now, there are still plenty of stocks that don't trade at all in the premarket session.

But in regular trading hours, it's unusual for a stock not to trade.

This is what makes the Relative Volume calculation so effective during RTH trading.

So in the premarket, a Relative Volume calculation is less meaningful because the variance is so high (and often premarket volume of zero is normal).

The better approach for the premarket is a much simpler calculation:

Until significant premarket volume becomes truly "normal," that's the better calculation to use.

And then treat RTH and premarket volume separately when designing your system.

-Dave

"I want to backtest, but I'm not a programmer"

2025-11-04T20:30:00-05:00

Here's a question from new list member Emmett H (name used with permission).

Emmett H:

I want to start backtesting. I'm sold after reading your stuff and listening to the podcast.

Do you think RealTest would be a good start for someone with no coding experience?

Dave:

RealTest is a good place to start, with one caveat.

RealTest operates on daily bar data only.

If you ever want to use intraday data, then you'll need another backtesting tool.

(And note that the vast majority of traders who trade for a living are trading intraday strategies. There are a variety of reasons why this is the case, which I'll review in future posts.)

Here's a quick overview of the options for intraday strategies:

Trade-Ideas

No coding required
Backtest is very fast
Downside: only 3 months of historical data

Amibroker

Unlimited backtesting history (the only limit is the amount of data you can find to import)
Has its own language to learn (coding required)
Downside: LLMs are not great at coding Amibroker

Python

General-purpose language
Unlimited flexibility
Much harder to get up to speed with trading

That said, I've worked with several traders who also said "I'm not a coder," but once they start seeing what's possible trading intraday strategies, they find a way to backtest with Amibroker.

Good-looking equity curves can be incredibly motivating.

The other thing to point out here is most developers reflexively choose Python for backtesting, but the better choice for them is Amibroker.

I've helped several traders switch from Python to Amibroker, and they're much happier!

Good question, Emmett!

-Dave

NASDAQ's Announcement on Tokenization of Stocks

2025-11-03T20:30:00-05:00

On this week’s episode of Line Your Own Pockets, we discuss NASDAQ's recent announcement of its initiative to tokenize all equities by next year.

What tokenization is and what that means for equities
How it affects settlement and paves the way for 24/7 trading
Prediction markets and positive externalities of betting ("Betting is a tax on bullsh*t.")
Dave proposed a bet to Michael based on the volume traded in the opening and closing crosses in the future

And much more...

LISTEN NOW »

-Dave

"But I'm Worried About Curve Fitting"

2025-10-31T19:30:00-04:00

Remember when you were a kid and you were scared of the dark?

I bet there was a phase when anytime your mom put you to bed and turned out the lights, you got scared.

But at some point, you learned that the dark wasn't as scary as you thought.

It's not that there are no dangers when it's dark - you're a lot more likely to fall down the stairs in the dark than when it's light.

But you learned to live your life without a terrifying fear of darkness.

Many traders have the same irrational fear of curve fitting.

They're scared to make any improvement to their trading strategy because it "could be curve fitting."

You should consider curve fitting when optimizing your strategy, but with the right process, it should not be crippling you with fear.

Think of one way you could improve your trading strategy.

How can you revisit it with fresh eyes, knowing that most traders are too scared of ~~the dark~~ curve fitting?

-Dave

Statistically Significant Number of Trades

2025-10-30T19:30:00-04:00

List member Simon replied and asked a question that crosses the minds of all systematic traders at some point or another. (Name used with permission.)

Simon:

How do you determine if a model has a statistically significant number of trades?

Dave:

My thinking has evolved on this over the years.

I used to think: "The more trades, the better." In general, I still think this and always try to create the most trades possible in a strategy.

However, as your intuition and "strategy taste" improve over time, you can be more confident in strategies with fewer trades.

If you understand the workings of your model well, with a strong signal, you can develop the faith to trade a strategy with size even if there are a small number of trades.

There have been multiple times over the years when I've shared the details of one of my strategies with smart people with PhDs in statistics.

I remember one of them told me, "Yeah, there's nothing there. It's not statistically significant."

This is a strategy that generates multiple 6-figure years in profits.

Yet, it's not "statistically significant" if you apply all the fancy t-tests and such.

Here's the thing.

The only person you need to convince that your strategy has edge is... yourself.

Specifically, your future self who is trying to find the confidence to continue trading through a system's drawdown.

Would that person find more confidence if there were more trades or fewer in the backtest?

So, start with more trades than you think you might need, but eventually you might find that fewer trades can work when you develop more intuition.

Great question, Simon - thanks for sharing with the list.

-Dave

Execution Hints in a Backtest

2025-10-29T19:30:00-04:00

Yesterday, I addressed Matt's question about the rabbit hole of trying to model perfect execution in a backtest and what not to do.

Today, I'll share a way to include meaningful data in your backtest that's highly correlated with execution while still keeping the super simple "one entry and one exit" backtesting approach.

It will come as no surprise to Strategy Cruncher users that the answer is to add custom columns to your backtest.

What Matt's really trying to do is capture profit from symbols trading with less volume than most larger traders will notice.

I like this approach because the default for a lot of systematic traders is to use a hefty minimum threshold for volume in their strategies. That is, they only consider the trades in the thickest symbols.

(I bet your stomach would drop when you see how thinly traded some of the symbols are in some of my models!)

Of course, there is a limit to how thinly traded it can be, but there are many tricks you can use to trade thin names.

When you're running a backtest, you should include columns that describe a symbol's thickness and then you have a good idea of how low to go and a reference point to adjust to real-world trading results.

Here are some column ideas you can use to capture a symbol's "thickness":

Average Volume
Relative Volume (recent volume versus average)
Spread (ask - bid) (raw value and in terms of ATR)
Very recent volume
Very recent volume as a percent of today's volume

Notice that a lot of these columns will apply not only to execution, but could very well be predictive for your strategy more generally.

With the Strategy Cruncher, there's no reason to limit the number of columns you add since it will tell you which ones are the most predictive. (Some users have over 300 columns in their backtests.)

Do you have any suggestions for other "thickness-based" columns? Hit reply and let me know.

-Dave

P.S. A lot of these columns are included in Trade-Ideas backtests by default, so TI users will see how to improve their strategy using the Cruncher in seconds. Click here to get started:

Backtesting Versus Execution

2025-10-28T19:30:00-04:00

Here's a good question from long-time list member, Matt H (name used with permission), on simulating real-world executions in a backtest for his strategy in Amibroker.

Matt H:

I have a different AmiBroker question. I spent many hours trying to get this to work, but have not been successful yet.

I know you prefer to have a single entry and exit, but for my current strategy, for the sake of trying to capture liquidity, I need to have several buy and sell locations per symbol.

The first entry position size was properly calculated and entered correctly, but no matter if I pre-calculated an array for the order size (based on candle volume) or calculated the position size inside the for loop, the subsequent entries were oversized and uncorrelated to volume.

Dave:

You're absolutely right that my default is to have a single entry and exit in my backtests.

The reason for that is important: it keeps your backtest simple.

Backtesting is daunting for a lot of traders already.

But it is so key to creating consistently profitable strategies - that's where your valuable insights will come from.

Your backtesting process should be as streamlined as possible, so you can get better at this skill by getting a lot of reps.

The more complicated your backtesting process, the less you'll end up doing it, so the fewer profitable insights you'll create for yourself over time.

Modeling execution (which is what Matt's describing) is a rabbit hole to avoid.

Does that mean you should ignore the differences between your backtest and execution?

No, but understand that any modeling of execution in your backtest is going to be imperfect and totally guessing.

And always one step away from a more "complete picture", e.g. "if I only include NBBO data" turns into "if I only include Level 2 data".

A classic rabbit hole requiring a lot of work and resources for minimal benefit.

Tomorrow, I'll share a minimalist approach for getting almost all the benefits while keeping your backtest as simple as possible.

Thanks for the question, Matt!

-Dave

What To Do When A Strategy Flips

2025-10-27T19:30:00-04:00

On this week’s episode of Line Your Own Pockets, we discuss a listener's question. Andre asks about a strategy he's backtested, put live, and traded successfully.

Then, the strategy stops working and, in fact, the edge reverses.

Topics discussed:

What this situation says about your strategy and ultimately your optimization process
Steps to take if this happens to you
How to prevent this situation in the future
Much more…

LISTEN NOW »

-Dave

A Tool to Create a Strategy from a Chart

2025-10-24T19:30:00-04:00

Imagine going to a high-end restaurant with a famous chef.

You get seated and you're ready for a fantastic meal.

But instead of having menus, the chef arrives at your table and says, "OK, what should I make?"

Wouldn't that be bizarre?

Yet, that's what you're doing when you try to create a strategy from a chart - it's hard!

To create a strategy, you need a signal.

Wouldn't it be nice if you had a menu of signals that actually occurred on a chart to choose from?

That's exactly what the very underrated and free (!!) Stocks Like This tool at Trade-Ideas does.

Take a chart like GTX from 10/23. Let's say you were trying to concoct a signal to fade the up move in the yellow rectangle below:

You would plug in the symbol, the date, the time of day, and the duration into the Stocks Like This tool (link to the results).

It returns a comprehensive list of the signals that occurred during that time period in the stock, along with the number of times the signal occurred. Here are the first few:

Rather than an open-ended starting point (like the chef asking you what he should make), this allows you to order a signal off a menu.

A much easier starting point.

Kick the tires a bit and let me know what you think.

-Dave

Strategy Ideas from a Chart

2025-10-23T19:30:00-04:00

Yesterday, I showed the mistake most traders make when trying to formulate a strategy based on a stock chart.

A few readers responded with their thoughts on the RTX chart in that post.

Let's brainstorm some ways to create a strategy based on that chart.

Here are a few ideas that come to mind from this one example. Here's the chart again for reference, ideas follow:

Strategy Ideas:

Find an alert in the first tall green bar (probably a new high alert with some volume)
After the first tall green bar, go long the pull back in the second green bar with the long wick
Fade the initial move by finding a threshold that the price has gone up too far
After the first two green bars, a consolidation forms. Go long the breakout of that consolidation.
Go short the breakdown of that consolidation (wouldn't have triggered in this example, but easy to find other examples that would have)
A hammer bar forms in the consolidation (the 10th bar in the yellow box) - go long the break of that candle
Short the subsequent move up (above the yellow box)

There are seven ideas to test from this one chart.

Can you think of others?

Each of these ideas is easily testable in Amibroker, and some can be modeled in Trade-Ideas.

The point here is not whether these ideas would have worked in this particular RTX example.

The real value is creating ideas from this chart to apply across the entire market.

Anyone interested in testing one of these ideas and sharing the results with the list?

If so, hit reply and let me know. I'll give you a free month of Strategy Cruncher access to do a case study.

-Dave

Strategy Ideas from a Chart

2025-10-22T19:30:00-04:00

As you do your daily review of the charts of stocks that moved, what exactly are you looking for?

You're brainstorming ways you could have realistically participated in that move.

The key word there is realistically.

Most traders look at a chart and immediately gravitate towards the area before the big move and try to find a signal there.

Take this chart of RTX from yesterday that appeared on my "Stocks with the Biggest Range" scan in Trade-Ideas:

Most traders try to concoct a strategy signal where the red arrow is pointing, but you're mostly wasting your time looking for a signal there.

The better approach is to find a signal after some initial movement.

It's tough to predict which stocks the market will react to (although RTX had earnings that caused this spike - good luck predicting the direction ahead of time, though!)

It's significantly easier (not easy!) to create a strategy that trades the reaction to some event.

So the first place I would look on this chart is not the red arrow, but the yellow triangle.

Maybe you get lucky and find a trade or two where the red arrow is, but we're looking for something repeatable.

Something that happens frequently that we can capitalize on.

Tomorrow I'll go over ideas for signals for a trading strategy from looking at charts.

-Dave

Where Do Strategy Ideas Come From?

2025-10-21T19:30:00-04:00

It's hard for new traders to imagine having too many ideas for trading strategies, but that's what happens when you create a process for yourself and follow it.

The best traders put themselves in a position every day to notice.

What are they noticing?

Trading strategies come from not just everyday market behavior, but from unusual market behavior.

The normal stuff is noise, but the unusual action provides the seeds that can turn into a trading strategy.

To notice the unusual stuff, you need to look at charts.

This will not come naturally to traders who come from an engineering or programming background, who prefer to work in a spreadsheet.

Creating a process to review charts is important.

You don't need to scan the charts of every stock in the market every day.

So which charts should you look at?

Start with the stocks that traded unusually today.

Here are a few ideas for different scans to get started:

Stocks that went up the most today (in terms of percentage or ATR)
Stocks that went down the most today (in terms of percentage or ATR)
Stocks that moved the most today (the largest ranges)
Stocks that gapped up today
Stocks that gapped down today

There will be significant overlap between stocks in those lists and stocks that appeared in successful trading strategies.

The next step is formulating an idea based on what you see in those charts.

That's the topic for tomorrow.

-Dave

P.S. Do you have other scans that you look at regularly and would like to share? Hit reply and let me know.

Stopped Out by a Penny? Good.

2025-10-20T19:30:00-04:00

On this week's episode of Line Your Own Pockets, we talk about stops.

Psst, and I've got news for you - there's nobody who cares enough about your stops to go "hunting for them."

And getting stopped out by a penny is frustrating, but it's actually a good sign.

Blaming an algo or anything else for your trade getting stopped out is counter-productive
Why most traders are completely wrong about placing stops
How to select stops for your strategy in a data-driven way
Much more...

LISTEN NOW »

-Dave

Share Your Ideas

2025-10-17T19:30:00-04:00

One of the big mistakes you can make in your trading career is not sharing your ideas.

"Who was I to put ideas out in the universe?"

"Why would I do that?"

"What was the ROI?"

"Why would anyone read what I wrote?"

These are all thoughts I had at various times.

But looking back, they were just excuses.

The more you share, the more you get back.

But even before getting anything back from the universe from writing, there's a very immediate benefit from it.

Writing forces you to crystallize your ideas.

To turn them from fleeting thoughts into well-formed, actionable ideas.

I'm always grateful when someone benefits from something I write or from the podcast.

What's really great, though, is when someone shares their ideas as a result.

That's why I want to highlight the work of long-time list member, Bruce Tharp.

Here's his latest post describing his futures strategy.

He describes one thing he learned from the podcast that "opened a whole new world of results" from his backtests.

Well done, Bruce, and thanks for sharing!

-Dave

P.S. For a good book on the subject of sharing, I highly recommend Give and Take by Adam Grant.

Turning on Your Trading Idea Spigot

2025-10-16T19:30:00-04:00

When beginning traders are getting started, they're typically starving for good ideas for strategies.

That's the bottleneck at first.

Once you have some success, the ideas start to come.

It often sneaks up on traders and they're caught flat-footed without an organized way of capturing and processing the ideas that start flowing.

It's always interesting to me that new traders are terrified of not having ideas, but experienced traders literally have the opposite problem: too many ideas!

That's the real bottleneck for the experienced trader.

It might seem like an avalanche of trading ideas is a lifetime away.

Or that you weren't born with the "trading idea" gene.

But that's simply not true.

Professional baseball players didn't emerge from the womb able to hit a 100mph fastball.

But they did create a process for themselves to improve.

To get a little bit better every day.

Great traders put themselves every day in a position to notice the important patterns.

Patterns that could turn into a trading strategy.

I'll be focusing on this topic in the coming days.

Stay tuned!

-Dave

A Useful Amibroker Keyboard Shortcut

2025-10-15T19:30:00-04:00

It's not every day that I learn a new feature in Amibroker, but that happened just yesterday.

This is something I wish I'd have known years ago - I bet it would have saved me thousands of mouse clicks per month.

Here's how it works. The AFL editor where you edit your code is in a separate window from the analysis window, where you run your exploration or backtest.

So, you're often switching between these windows to try something, then going back to your code to make adjustments, and then trying again, etc.

To make this workflow efficient, I would place the AFL editor window on a different monitor.

But now that I stumbled upon a convenient keyboard shortcut, I've completely changed how I do this.

The keyboard shortcut is control-backtick (cntl-`) (the backtick is above the tab key).

This toggles between the main Amibroker window and the AFL editor window.

Here's a video showing it in action: (I'm simply typing cntl-` to make this happen)

If the video doesn't appear, you can view it on the web here.

Now I have the AFL editor right behind the main Amibroker window, and I can efficiently toggle between them with minimal context change.

A big improvement.

Do you have other keyboard shortcuts you use in Amibroker? Hit reply and let me know.

-Dave

Amibroker: Coding a Time Stop

2025-10-14T19:30:00-04:00

Long-time reader Thanit P. (name used with permission) sent me a code snippet in AFL with a question about coding a time stop, that is, an exit after a certain amount of time if another exit order hasn't executed.

(I won't include the entire AFL code to keep Thanit's strategy logic private, but I'll share the logic in question in my response.)

Thanit P.

It would be great if you could give some suggestions on my following code as it has failed to give any signal in live trading (a topic I have never talked about with you before but would be eager to). However, it gave normal backtesting results.

The reason is that I think you may be able to help is that your demo code involves the use of a loop, which is something I didn't think of before about AFL. However, after trying to code "exit on X bars", ChatGPT gave me this loop. At first, I thought it would be OK as the backtest was fine. I suspect the function "barcount" may work differently in a live environment?

Dave:

The AFL code in question is this:

First of all, ChatGPT is notoriously poor at AFL.

Hopefully, it will improve, but I end up fixing a lot of bad AFL code for traders who generate it with ChatGPT.

In theory, this code should work, but there are edge cases where it won't.

For example, this won't work if there are bars where the symbol doesn't trade. That is, if you're expecting to exit in 30 minutes and the symbol doesn't have trades for half of those bars, then this logic won't exit until 60 minutes!

For time stops, it's always a good idea to use minutes since the market open and/or minutes until the market close as a reference.

It's easier to follow the logic, and it's extensible. For example, you could integrate half-day support and your logic wouldn't change.

Real-time versus backtesting in Amibroker is a big topic.

There are major differences that come into play in real-time trading that you don't have to think about in backtesting.

Is Trading Gambling?

2025-10-13T19:30:00-04:00

In this episode, we tackle this popular question. I polled several traders I coach and got some surprising answers.

How much is trading like, say, poker, or something that is even more up to chance?
Even starting a business can be called gambling if defined purely as "risking money on uncertain outcomes."
Does having an edge make trading less like gambling?
In a casino, is the house "gambling" because it has a strong edge?

What's your take?

LISTEN NOW »

-Dave

Amibroker Performance Tool: Profiler

2025-10-10T19:30:00-04:00

When troubleshooting Amibroker performance, there's a valuable tool that most users don't know about or appreciate.

It's called a code profiler.

Developers might recognize this type of tool from other languages (for example, Visual Studio includes an excellent one for C#).

A code profiler tells you all the function calls your program is making and how resource-intensive each one is.

This is invaluable for tracking down performance issues.

In Amibroker, it's available in the AFL Formula Editor window by going to Tools and choosing the Code Check & Profile menu item.

Here's the report from an AFL file I'm working on now:

I can see that the GetGradient function is only called 3 times, but the time spent in that function is 94ms, the most of any function called.

This allows you to quickly track down which functions are causing the biggest delay in your code.

Typically, this doesn't matter THAT much for backtesting, but when you start using Amibroker to trade in real-time, it becomes very important.

-Dave

Does Automated Trading Require a Developer?

2025-10-09T19:30:00-04:00

Early in my career, I remember wondering if I could even write code since I didn't have a computer science degree.

It turns out I could.

Self-taught programmers are usually good because they've learned to code from a genuine desire to automate a need they had.

It's one thing to learn to program by following an example in a book or course.

It's a lot more motivating to learn when the task is not some contrived example project, but a real-world thing that will make your life better.

And can you guess what the most motivating project is?

One that magically converts "non-developers" into people who can write code?

Just one glance at the equity curve of a decent trading strategy can turn someone who isn't a developer into someone who can get it done.

I've seen this many times.

Equity curves have a way of being very motivating.

-Dave

Signal Generation and Trade Execution - Separate?

2025-10-08T19:30:00-04:00

Here's another great question from a new list member, Chip, about how to set up the code for automating his trading strategy. (Name used with permission)

Chip:

I've always kind of known discretionary wasn't for me...been at this unsuccessfully for a long time. Had previously used Python to do some analysis work, but your stuff really inspired me to revisit a backtest for an idea I had. Changing the approach to adding columns was a game-changer for finding the edge in the idea (I think). It's taken weeks to get it to a usable place, but I started trading it a few days ago. Not fully automated yet, it's just spitting out the signals, but I'm excited about seeing how it works and figuring out how to automate the orders.

Is it best practice to have the alert script place the orders? Or, do you create a separate script to read the alert output and then place the orders?

Dave:

The signal generation and acting on it are two different things. In this case, I like having them separate.

That makes it way easier to test things, and you'll have separate code files for each function.

The computer science term for this idea is separation of concerns.

And it's not something you simply learn in school, it's a practical way to design your code structure that makes your life way easier.

One thing I ALWAYS include in either script is plenty of parameters to control the behavior without actually modifying the code.

One of them in particular is a --pretend mode (sometimes called --dry-run).

In that mode, it takes all the steps except actually doing anything - it simply reports what it WOULD do if it weren't in pretend mode.

I can't tell you how many times a scenario comes up where pretend mode comes in handy!

Trying to cobble that together when you need it is trickier than it seems, so I do this right from the beginning when I create almost any script or code.

Thanks for the question, Chip, and welcome to the list!

-Dave

Monte Carlo Simulations for a Backtest

2025-10-07T19:30:00-04:00

Long-time list member Marek R. wrote in to ask about Monte Carlo simulations (name used with permission).

Marek R.:

I've recently discovered Monte Carlo simulations. How do you approach this? Do you use this kind of random order of the trades to confirm the edge and avoid curve fitting to only the historical data sequence?

Dave:

I think Monte Carlo simulations are a useful tool to have in your toolbox.

I don't use them frequently, but occasionally I'll use them to visualize different ways a strategy might have played out.

The idea is you take your backtest, which is a list of trades in order by entry time, and reorder them randomly.

You can do this multiple times and then compare the resulting equity curves against each other.

The ordering of your trades is somewhat random, so when you reorder them, you are simulating plausible scenarios that could have occurred, but didn't happen just by chance.

You can better visualize what could have happened, and therefore what sort of variance you can expect going forward.

Is this useful? Yes.

Is it a silver bullet that you can use to improve your strategy or prevent curve fitting? Probably not.

But it's certainly worth knowing about and having in your bag of tricks.

Good question, Marek - thank you!

-Dave

Using Alternative Data in a Backtest

2025-10-06T19:30:00-04:00

In this episode, Michael asks me how to include alternative data in one of his backtests.

We discuss:

What is alternative data, and how can you use it in a strategy?
Examples of alternative data
Using it in real-time versus a backtest
How to automate the process for backtesting and real-time trading

LISTEN NOW »

-Dave

Dynamic Sizing Based on Risk?

2025-10-03T19:30:00-04:00

List member Brandon C. replied in response to my recent post on position sizing with a good question (name used with permission).

Brandon C.:

What are your thoughts on dynamic sizing based on risk? For example, you have set parameters for grading an opportunity/catalyst and risk tiers and acting accordingly.

Grade A and A+: 80 to 100% of your daily stop
Grade B setups: 40%
Grade C setups: 20% and so on.

Dave:

I love this approach.

It's definitely not for beginning traders, but it's something all traders should be shooting for and thinking about.

Why?

It puts you in a mindset to scale your strategy.

Take a look at your equity curve for your backtest.

Now imagine, before entering, being able to identify the most profitable 20% of the trades (without curve fitting).

When you can do that, you have a powerful way to scale up your strategy by increasing your size in the most profitable trades.

Some traders tell me that there's no way they can do this with their strategy - every trade has the same probability of succeeding.

But there's just no way that can be true.

Once you develop a strategy that works, this is the next step for making it significantly better.

Thanks for the question, Brandon C.

-Dave

P.S. The Strategy Cruncher is the perfect tool for figuring out how to increase size in the most profitable trades in your backtest. Here's an example from one of my strategies that I backtest in Amibroker. This comes right from the cruncher report. I can quickly see from this one suggestion from the cruncher that I can use a larger size for this set of trades. This rule is based on the distance from yesterday's close price - something I would not have been aware of if the cruncher hadn't suggested it.

Percent of Account to Risk

2025-10-02T19:30:00-04:00

Following up on yesterday's post to address the crux of Abhishek's question.

What percent of your account should you be risking per trade?

This is one of those questions where there aren't any right answers, but there are a whole lot of wrong ones.

The way I like to approach this is: what's the smallest number you can use and still accomplish your goals?

In general, risk is trader-dependent. There are too many factors to have a one-size-fits-all answer.

Here are some factors I've used over the years to determine the risk to use per trade in one of my strategies:

My age - in my younger trading years, I could afford to risk more since time was on my side
Tail risk - does the strategy have significant tail risk? If so, tend towards a lower number than you think
Strategy quality - does the strategy have the ability to scale? If I think so, I'd start with a lower number with the plan to increase over time
Win rate - definitely an overrated stat, but still, strategies with a lower win rate are psychologically difficult to trade
Historical drawdowns - how deep are the drawdowns? How much am I willing to go in the hole in the future? If they're large, then I'd tend towards a lower percentage
Smoothness of the equity curve - the most underrated stat!
Confidence in the above factors - you'll very likely have varying levels of confidence in the previous factors. If my confidence is fuzzy, I'd start with a lower number and increase as things come into focus

If this feels like a wishy-washy answer, good! That's the right takeaway.

Risk is a personal decision, and when in doubt, risk a lower amount than you think is prudent.

Risk is one of those things that should keep you up at night a little.

How might you be fooling yourself? Overconfidence is a far bigger problem than underconfidence.

Thanks for the question, Abhishek!

-Dave

What Sizing is Best?

2025-10-01T19:30:00-04:00

Here's a follow-up question from Abhishek K. (used with permission) to my recent post on two position sizing approaches.

Abhishek:

When the sizing is based on stop, are you risking a fixed % of your capital every trade? If so, how much do you recommend: 1%, 2%, or 5% per trade?

Dave:

Yes, with most strategies, I risk a certain amount of capital with every trade.

This is different than the total amount of money at work for a given trade.

This is a crucial concept to understand.

The amount at risk is the important part - the total money at work is almost irrelevant for good trading system design.

Here's a hypothetical example from the Get Systematic Roadmap I offer:

You go long 1000 shares of AAPL at $186 with a stop price of $176. You exit with a profit of $1900.
You go long 1000 shares of AAPL at $186 with a stop price of $185. You exit with a profit of $1900.

One of those trades is a LOT better than the other.

Can you tell which one?

Tomorrow I'll address the meat of Abhishek's question about the percent of account size to risk.

-Dave

Special Symbols for your Backtest

2025-09-30T19:30:00-04:00

On Friday, I showed how easy it is to add alternative symbols to your Amibroker backtest using the SetForeign function.

I showed how to add data from the SPY, but there are many interesting special symbols available to you if you know where to look.

Although you can't trade these symbols, from your data feed's perspective, they look and feel exactly like regular symbols.

This makes them very convenient to add to your backtest as a column.

And once you add it as a column, you can easily optimize on it.

Here are the ones in my column library that I include in each backtest as columns (IQFeed symbol in parens):

TICK (TICK.Z) - The NYSE Tick: number of NYSE‐listed stocks whose last trade was above the previous trade minus the number whose last trade was below the previous trade. In other words, net upticks minus downticks.
TRIN (TRIN.Z) - Also called the “Arms Index” or “NYSE Trin”. It is a breadth‐oscillator that compares advancing vs declining issues (number of stocks up vs down) relative to their respective volume. Formula is something like (Advancers ÷ Decliners) divided by (Advancing volume ÷ Declining volume).
VIX (VIX.XO) - The CBOE Volatility Index — often called the “fear index”. It measures the market’s expectation of 30-day forward volatility implied by S&P 500 option prices.
IINA (IINA.Z) - The number of advancing issues (stocks trading up from prior close) on the NYSE — at a snapshot (often cumulative through the trading day) or repeated interval snapshots.
IIND (IIND.Z) - The number of declining issues on the NYSE — stocks trading down from their prior close, same framing as IINA.Z.
IINU (IINU.Z) - The number of unchanged issues on the NYSE — stocks whose price hasn’t changed (from their prior close) at that snapshot.

Your data feed will likely have slightly different symbols for these and other special symbols. Search for "symbology" to find the documentation for your data feed.

Here's the link to IQFeed's Market Indices Symbols.

You can bring these symbols up in a chart and get a sense of the range of values to understand what's normal and extreme.

(I use IQFeed as my real-time data feed for Amibroker.)

-Dave

A Different Way to Go Live

2025-09-29T19:30:00-04:00

In this episode, Dave discusses a conversation he had with John M. from SMB Trading and his unique approach to taking a strategy live.

We discuss:

John's 35+ strategies he runs live
How quickly he gets a strategy running in production
His approach to collaboration with other traders
What "strategy taste" is and how you can improve yours over time

LISTEN NOW »

-Dave

Adding Data from Other Symbols into a Backtest

2025-09-26T19:30:00-04:00

The beauty of using the Strategy Cruncher is that there's no reason not to add more columns to your backtest.

The Cruncher will tell you which ones are important.

I have over 200 columns in my column library - some traders have over 300 - that get automatically added to every backtest I run.

One type of data point traders often overlook is data from other symbols.

For example, you have a strategy that trades gapping stocks.

One useful column might be the current SPY gap.

If SPY is gapping up, maybe a stock gapping up isn't that unusual.

Amibroker makes accessing this data easy using the SetForeign function:

Now, any calculation can be made on SPY data and included as a column in your backtest.

Next time, I'll share the alternate data points I include in my backtest - stay tuned.

-Dave

Backtesting on Short Timeframes

2025-09-25T19:30:00-04:00

Here's a question from list member Marek R. on how to do backtesting on small timeframes.

Marek R.:

How do you approach backtesting on 1-minute data when there are trades with a trade duration less than 1 minute?

When I design the strategy, I try to intuitively engineer the strategy that I would avoid trades executed within a 1-minute candle, but when I was doing trade review today, I noticed that yesterday I had 11 trades and 5 were within a 1-minute duration, which turned the winning ratio to:

Backtest: 7 winners from 11 trades
Paper trading: 2 winners from 11 trades (both with duration more than 1 minute)

Dave:

This is a common scenario in backtesting.

You should always look closely at the duration of the trades in your backtest to determine if the precision of your data is causing skew.

If you're backtesting on 1-minute bars, and you have durations of one minute, then you can bet your backtest is too optimistic.

The first instinct of many traders is to try to find data with finer precision, but that's last on the list of ways to handle this situation.

Why? Because even if you get 1 second bars and backtest on them, you'll still run into this issue.

In fact, even if you use tick data, you'll still run into issues with what the bid and ask were historically.

Even if you solve that, you'll still encounter issues with the depth of the order book (level two data).

All of a sudden, your data requirements have exploded, and the resources required to store and process a backtest would be prohibitive for almost anyone reading this.

However, the good news is that you don't need that level of precision to backtest a strategy like this.

The first thing to do is run your backtest without stops or targets - only your time stop.

This removes any precision problems in your backtest around the entry bar.

(You shouldn't trade without stops, but this exercise is useful for having a deeper understanding of how your backtester works - and your strategy.)

In most strategies, removing a stop should make your backtest look better.

If it makes it worse, then I would review charts of the trades with and without the stop to fully understand what's going on.

I love Marek's approach here - he learned a valuable lesson by paper trading and therefore didn't put any money at risk to learn it.

Well done!

-Dave

Two Position Sizing Approaches

2025-09-24T19:30:00-04:00

Several of you responded to yesterday's post about the different position sizing approaches I use.

Here's a nice visual I put together to see the difference in one of my strategies.

This is the pre-optimized version of the strategy, before putting it through the Strategy Cruncher.

Both the green and the red lines have the same trades, but with only a single difference.

The green line is using position sizing based on the distance to the stop price.

The red line is using a constant share size.

Which equity curve would you rather use as your starting point?

Why are the lines so different? Two reasons:

The stop price is selected based on recent price action
The sizing is based on the distance to the stop

You can see how this approach incorporates sizing at a fundamental level - it's baked into the strategy itself.

The strategy doesn't really make sense without this sizing.

Choosing the right position sizing approach will make or break your strategy.

If you're bolting it on at the end as an afterthought, it's unlikely to be good enough.

-Dave

How do you do position sizing?

2025-09-23T19:30:00-04:00

List member Dean J. wrote in with a question on position sizing (used with permission):

Dean J.

When you are doing your backtesting, do you use a standard size for each stock, ie, every trade is 100 shares, or do you size by a % or something else? In other words, a $20 stock won't move as much as a $100 stock if they were all the same size, wouldn't it make the results look different than the true value of each stock might be in your strategy?

Dave:

There are a few ways I'll size positions based on the strategy:

Constant shares (rare, but there are strategies where this is the best choice)
Constant dollars - e.g. $1000 / entry_price
Based on ATR or volatility - e.g. $1000 / ATR
Based on the stop distance - when signal is from a pattern with a logical stop

I have strategies that use all these approaches.

I think the most underrated is the last one - sizing based on the stop distance.

I see some really good traders who don't even consider sizing based on stop distance.

The reason it's so valuable is that the sizing is fundamentally based on the trading signal.

When you do that and then optimize your strategy in the Cruncher, you'll get a completely different set of predictive variables.

And it's easier to find ways to scale the strategy - because you'll have trades where the stop is a short distance away.

And because it's based on a pattern, the setup itself (and the sizing) leads to a strategy with a clearer path to confidence.

That is, you have a path to believe in it enough to trade with significant size.

-Dave

Follow Up On Quant/Discretionary Collaboration

2025-09-22T19:30:00-04:00

In this week’s episode of Line Your Own Pockets, we review last week's interview with Mike Bellafiore and Nick Coutrakon from SMB Capital.

We discuss:

How Dave first connected with Bella
The cultural DNA of SMB Capital
The challenges of quant/discretionary collaboration
The importance of being a giver, not a taker

LISTEN NOW »

Books mentioned:
Give and Take by Adam Grant|
The Go-Giver by Bob Burg and John David Mann

-Dave

Plan for a Drawdown Like a Pro

2025-09-19T19:30:00-04:00

One of the biggest problems with drawdowns is that they seem to come out of nowhere and catch you off guard.

There's never a convenient time for a drawdown - in fact, they have a knack for selecting the worst possible time to occur.

But you don't have to be caught completely flat-footed.

After being blindsided by drawdowns several times, I got fed up and came up with an approach that works really well.

When I optimize a trading strategy initially, I create two versions.

The first version is the one I'm planning to go live with - my best guess at the optimal way to trade the strategy.

The second version, however, is one with fewer but more profitable trades than the first version.

If you go back to the example strategy I shared a few weeks ago with different versions, I might go live with version one:

Version 1:

Profit Factor: 1.87
Win Percent: 53.8%
Trades: 3,859
Trades per day: 3.3

But then hold version two in reserve to have ready to go if the strategy goes into a drawdown:

Version 2:

Profit Factor: 3.29
Win Percent: 55.1%
Trades: 1,619
Trades per day: 1.4

This approach gives you a systematic way to plan for drawdowns from the outset.

And when you're optimizing your strategy, you're in exactly the right mindset to create this plan.

If you wait until you're already in a drawdown, you'll be frustrated and pissed - exactly the wrong mindset you need to come up with a plan.

-Dave

P.S. If your backtested strategy is in a drawdown, you can use the Strategy Cruncher to improve it. One trader told me this week that he covered over 2 years of the Cruncher's cost with just a single use.

Get Started with the Strategy Cruncher

Drawdowns Make You Better If You Let Them

2025-09-18T19:30:00-04:00

Every trader who ever quit trading did so during a drawdown.

But at the same time, every profitable trader experienced the same drawdowns and didn't quit.

In fact, profitable traders will often cite drawdowns as fundamental inflection points in their trading career.

They learned from them.

Why do some traders quit while others treat drawdowns as learning opportunities?

I believe it comes down to your attitude about the markets.

If you believe your drawdown isn't your fault...

If you believe the bad guys came after your stop...

If you believe the Chinese manipulators caused your drawdown...

If you believe your guru in the trading room didn't give you the signal fast enough...

Then you will eventually quit trading during a future drawdown.

But if you realize that you alone are responsible for your current drawdown, as painful as that might be, then you have the right attitude.

Because if you're responsible for the drawdown, then you can make the next one a lot shallower.

What would your results look like if your drawdowns were half as deep and half as frequent?

When you take responsibility for your own trading, you can make that happen.

-Dave

Compare Real Trades to your Backtest

2025-09-17T19:30:00-04:00

After you refresh your backtest to current, comparing it to your live trades can point you to the reasons for your drawdown.

Here's a list of things you can compare, in order of importance:

Missing Big Winners

Sort by the largest profit in your trades list. How many of those are missing from your live trades? Find out why.

Slippage on Entry

Compare your entry prices in the backtest with your entry prices in your corresponding live trades. How much of the drawdown is coming from this difference?

A good way to do this is to add another column using Excel for the total slippage in terms of profit dollars for each trade, and then sum it up.

Slippage on Exit

Compare your exit prices in your backtest with your live exit prices. Add another column for exit slippage and sum it up to see how much it's contributing to the shortfall.

Here's the thing:

Your live trading is never going to perfectly measure up to your backtest, but that doesn't mean you can't take action to minimize all these things in the long run.

If your current drawdown is barely visible on your backtest, don't get frustrated - that's a good thing.

There's always something you can do to address these issues.

-Dave

Refresh Your Backtest in a Drawdown

2025-09-16T19:30:00-04:00

Most traders will run a backtest, implement a strategy in live trading, and then largely disregard the backtest.

At any point in time, your list of trades from the backtest might be a few weeks or even months old.

When you're in a drawdown, the first thing you should do is update your backtest to the most recent trading day.

(It's important enough that I have code in place to automatically run my backtests each day, and I strongly encourage the traders I coach to do the same.)

Why is this so important?

When you're in a drawdown, you can feel like your world is falling apart.

Nothing is going right.

You're starting to have doubts, sometimes serious doubts.

"I knew my success had to end at some point," you might tell yourself.

Drawdowns have a way of flipping your mental negativity switch.

This is the opposite mindset of what you need to be successful.

Looking at an up-to-date backtest almost always puts you in a productive mindset.

With a backtest as your guide, you can:

Get a zoomed-out perspective across time (is this drawdown normal?)
Find concrete things to do to improve your live trading
Identify ways to avoid poor trades to prevent future drawdowns

Your mental switch flips back to positive almost immediately.

You realize you have plenty of ways to get better.

The perspective you get from a backtest is valuable anytime - but especially when you're in a drawdown.

-Dave

Mike Bellafiore and Nick Coutrakon from SMB Capital on Trading Teams

2025-09-15T19:30:00-04:00

In this week’s episode of Line Your Own Pockets, we're joined by Mike Bellafiore and Nick Coutrakon from SMB Capital.

Bella and I were recently discussing the makeup of trading teams at SMB. After giving it more thought, I realized it would make an excellent topic for the podcast.

Get an inside view into the teams at one of the best trading firms in the world.

We discuss:

How teams have traditionally been formed at SMB
Incorporating quants into a primarily discretionary trading group
What quants can do to fit in and what they should avoid
What discretionary traders can do to create the most profit through collaboration
Much more…

Whether you're a discretionary or a quant trader, you don't want to miss this episode.

LISTEN NOW »

-Dave

Reducing Size in a Drawdown

2025-09-12T19:30:00-04:00

Every car crash could be avoided if one of the cars were going a little slower.

If you're in a hurry for any reason as a trader, it's almost always a bad sign.

And that includes being too rushed to make profits from your strategy.

The quickest way to turn a modest drawdown into a big one is to maintain your same size (or increase it!)

And the big drawdowns are when you'll give up - on your strategy or even trading altogether.

I know this because I came very close to quitting trading several years ago, and it was precisely because I stubbornly refused to reduce size during a drawdown.

One reason you might be refusing to reduce size is that your strategy is working now, but you think it might stop working soon, so you maintain your size to capture profits while they're available.

But if that's the case, then by definition, you don't have a path to confidence with your strategy.

If you don't have confidence in the durability of your strategy, then you haven't put enough thought into it.

You've chosen rules that you don't quite fully believe in.

Reducing size isn't admitting defeat; it's living to fight another day.

-Dave

Handling a Drawdown

2025-09-11T19:30:00-04:00

I've heard from more than a few traders over the past few days that they're in a drawdown due to recent market ~~manipulation~~ events. (See long-time friend of the list Maoxian's recent post on his Substack.)

Here are some suggestions for handling drawdowns (which are inevitable, despite what the folks who are good at talking about trading rather than actually trading might have you believe).

Reduce size - psychologically difficult, but better in the long run
Refresh your backtest up to current - the perspective a backtest provides is incredibly helpful
Observe market action in real-time - more than you normally would
Develop theories to improve your strategy - and add new columns to your backtest to capture aspects you're missing
Deploy a "version two" of your strategy for exactly this type of situation

Drawdowns are the market giving you clues for how to get better.

They also flush out the hobbyists.

Every trader who ever quit trading did so during a drawdown.

Handling drawdowns separates the pros from the pretenders.

It's not if another drawdown comes, but when.

What can you do now to be better prepared for the next one?

More on this topic over the next few days.

-Dave

Strategy Starting Points

2025-09-10T19:30:00-04:00

In yesterday's post on Amibroker performance, I shared some steps to minimize the time it takes to run a backtest.

It's worth digging into the details and figuring out how to maximize your use of whatever backtesting tool you're using.

If you can reduce the amount of time you're twiddling your thumbs waiting for a backtest to complete, that's more time you can spend doing the fun part - optimizing your strategy.

Part of that process is figuring out the strategy to start with.

Remember: your first backtest shouldn't be an attempt at your "final answer" - it should be a strategy with minimal filtering to use as a starting point.

Most often, after optimizing with the Strategy Cruncher, the version I end up going live with has a fraction of the number of trades as the original backtest - sometimes less than 10%.

The backtest mentioned in yesterday's post had over 134k trades over 5 years.

That's on the very top end of the number of trades I've ever started with for a strategy.

It's more art than science, but choosing the right starting point for a strategy ends up saving a lot of time in the long run.

The more trades in your backtest, the more memory your machine has to use to add custom columns and complete the portfolio phase to merge all the trades at the end.

Another important consideration is that with 134k trades over 5 years, there has to be a lot of noise in that starting point (noise as opposed to signal).

The higher the signal-to-noise ratio in your starting point, the better your strategy will end up being - and the easier your optimization process will be.

You'll get better and better at choosing good starting points the more you do it - it takes practice.

-Dave

Troubleshooting Amibroker Performance

2025-09-09T19:30:00-04:00

Here's a question I received from Mugu M. about his local Amibroker performance and how long it takes him to run a backtest (shared with permission).

Mugu M.

I noticed in the email you sent to the group as a follow-up to your new computer acquisition that you can run a backtest across the entire market (1-minute bars) in 35 minutes in Amibroker.

This got me thinking, I could be missing a few setup tricks.

Here is a backtest I ran on S&P 500 constituents:

Does anything stand out? This backtest took 6.5 hours on 10-minute bars 2015 - 2019: 5 years. I have an Amibroker database in 1-minute granularity from 2009/2010 to date.

I can think of the extra compute from the for loops vs the Amibroker native way of handling array operations, but this gives us the benefit of predictive columns extraction from the backtest.

Dave:

There is some background I should review here for readers. Mugu was an early adopter of the forthcoming Amibroker course, which comes with a sample strategy showing you the right way to code a strategy in Amibroker.

Given how poor ChatGPT is at creating Amibroker code (it's shockingly bad, but it thinks it's great at it!), this sample strategy is a big head start for traders using Amibroker.

The sample strategy contains two sections that are very important to creating a profitable strategy in Amibroker.

One is a for loop that iterates through all the bars in your database.

Why is a for loop required? It's required to add custom columns to your backtest.

Why are custom columns required? Because otherwise you're going to be forever stuck in "backtest world" without figuring out how to make your strategy profitable and actually trade it live.

The other section turns on Amibroker's "custom backtester" interface. This interface allows you to add custom columns to the resulting backtest.

Here's what I suggest Mugu do to determine where the slowdown is.

Run a backtest with just this AFL code:

This is the simplest backtest possible - no for loops - in fact, it won't even take any trades, but it will iterate through all the bars in the database with minimal processing.

Measure how long it takes for this to complete.

The next step is to run another backtest with the same code, but with a simple for loop added:

Measure this and compare.

There are a lot of technical details here, but they're important. If you can get your backtest down to a smaller amount of time, your entire workflow is going to be faster, which will eventually translate into more profits.

I ultimately believe that Mugu's performance issues are related to the number of trades in his backtest.

Baby Steps Towards Automating Your Trades

2025-09-08T19:30:00-04:00

In this week’s episode of Line Your Own Pockets, we discuss several tiny steps you can take to get closer to automating your trades.

There's a whole range of steps you can take on your progression towards automation.

We discuss:

Various custom trading programs I've created for myself over the years
Tiny steps you can take to get more and more confident with automation
How even small steps make you a better trader
How automation opens up new strategy possibilities that manual click traders can't consider
Much more…

LISTEN NOW »

-Dave

P.S. Where are you on the manual-to-fully automated trading continuum? Hit reply and let me know.

Missing the Big Winning Trades

2025-09-05T19:30:00-04:00

When you first start trading a strategy live, the very first thing you should do is compare the backtest to the live trades.

This is not a step you should put off until later.

Do it as soon as possible after the first day you have live trades.

Some traders like to let some time pass at this stage to "collect more data."

But that's a missed opportunity.

You can get answers so quickly when you compare your trades to your backtest, even on an average day for your trading system.

Doing this lets you shift your path to confidence in your trading system into hyperdrive.

When comparing to the backtest, there are lots of data points you can reconcile. (Slippage in, slippage out, etc.)

But by far the most important, the easiest, and the most motivating thing to look for is...

Missing the big winning trades.

If you're missing them, you should drop everything else you're doing and figure out why.

Because at that point, it's the most important thing you can work on (and it's not even close).

-Dave

Success Story from Reader Robin J

2025-09-04T19:30:00-04:00

Fellow list member Robin J responded to my message from a couple of days ago with a success story about applying lessons from the Get Systematic Roadmap (she was an early beta tester for it) on expectancy (shared with permission, with minor formatting changes):

Robin J:

I met with you when you were starting your individual sessions. I'm the teacher who quit teaching to trade.

When I started trading, it was like printing money. Then came the breakeven period. Thankfully, even with drawdowns, I've never ended up at a loss.

I just thought, reflected, let it percolate.

Then came the epiphanal moment on how to finally get my risk management under control, consistently. I had been feeling like the more I strived for the generating consistent income approach, the more I missed.

It took about a year to really nail it down. (You and I worked on R primarily in my session with you.)
I thought I'd share that one of the things that has helped me tighten this up was actually using the expectancy equation.

Where:

Pw = probability of a winning trade
Aw = average win size
Pl = probability of a losing trade
Al = average loss size

From there, I could think about how to cast a wider net in a way that allows me to continue to scale. I also decided that it would have to scale itself, like a biz building itself. I wanted to prove the concept, so I started in my paper account and then took it live once it had accumulated enough evidence for me.

Essentially, I shifted from trying to catch a medium or large fish each trade to how can I catch lots of smaller fish in one net on a regular basis, and tip the balance in my favor in a way that I can then end with a bigger haul than I would have.

Our talk about R made me realize:

that I didn't know what that was!
that I needed to adjust my expectations.
that I was going to have to put in some work and calculations to identify exactly how to make my strategy work. When we run so much based on statistics, but when you are 1 person with 1 account, that changes how the statistics are going to work in reality.
And the mantra "live to trade another day" needed to be integral to my practice.

And this is my equity curve with my newly applied risk management, starting late July:

Congrats to Robin on her breakthrough!

I hope this inspires other traders to leverage good risk management and apply it to their own strategies.

-Dave

"And Now a Word From Our Sponsors"

2025-09-03T19:30:00-04:00

Just kidding LOL.

There are no sponsors for this newsletter and no plans to add any.

There's so much snake oil in the trading business, it's mind-boggling to me.

Affiliate programs are everywhere - and they've never sat well with me.

If your product is good enough, you shouldn't have to pay someone to incentivize them to tell others.

If I recommend something, it's because I genuinely think it will benefit you, not because someone is paying me to suggest it.

There are people who are good at trading, and people who are good at talking about trading.

The overlap between those two sets is... tiny.

OK, stepping off my soapbox now.

-Dave

How Do You Know Your Strategy Has An Edge?

2025-09-02T19:30:00-04:00

There’s a huge difference between carrying a stethoscope and being a doctor.

In the markets, it's trivial to execute buy and sell orders, but that doesn't make you a trader.

Trading is easy when you trade with inconsequential amounts of money.

It's dramatically harder when you set out to trade with significant capital (whatever amount that might mean to you).

For every strategy you trade, you should have a path to confidence.

What questions would you need to answer to trade it with bigger size than you are now?

The first question I ask traders is:

How do you know your strategy has an edge?

If you aren't thinking about that question - and charting out your path to confidence - then you're putting a ceiling on how good you can be.

-Dave

Which Version of this Strategy is Best?

2025-09-01T19:30:00-04:00

In this week’s episode of Line Your Own Pockets, we discuss the responses to my recent post on different versions of a strategy I'm working on.

We discuss:

The tradeoffs between different versions of a strategy
How newer traders might be drawn to a specific version
How automation gives you more flexibility for trading a strategy with lots of trades or infrequent trades
Much more…

This is one of my favorite topics.

LISTEN NOW »

-Dave

A Great Use Case for Trading with a VPS

2025-08-29T19:30:00-04:00

Here's an interesting exchange with a trader named Angel R. (name used with permission) about using a local trading computer or a remote VPS (virtual private server).

Angel's situation seems like a slam dunk for using a VPS.

Angel R:

Congratulations on the first year of the podcast!

The episode of Line Your Own Pockets was very interesting about trading when traveling.

I was not familiar with Chrome Remote Desktop, I like to use Anydesk to access my trading computer at home, but I think that the connection with Teamviewer is too slow.

But I am wondering, what do you think about a VPS for running IB Gateway (from IBKR) remotely? I am considering it to have a stable network (avoiding connection and power issues at home), and also to reduce latency on IB servers (I am living in Panamá).

I imagine I will need to access the VPS every morning to log into IB Gateway and run my scripts.

Dave:

When you have a questionable internet connection, I think it makes a lot of sense to use a VPS and the IB Gateway or TWS.

Are you considering the IB Gateway for performance reasons?

Angel R:

Yes, I am testing IB Gateway for better performance. The worst-case scenario I've seen with TWS is an 11-second delay when placing an order (I am a day trader), which can be quite long, but with IB Gateway, orders are placed fairly quickly (about 1 second).

Dave:

The IB Gateway is a headless version of TWS - basically just a local endpoint that exposes the IBKR API in the most efficient way.

I knew it had lower overhead than the full-blown TWS, but I didn't realize the performance difference was that dramatic!

In this case, the benefit of a VPS seems overwhelmingly worth the cost.

I'm curious, are other IBKR traders using the IB Gateway rather than TWS?

Reply and let me know.

-Dave

P.S. Have a great Labor Day weekend!

Commissions and Slippage in Backtest?

2025-08-28T19:30:00-04:00

Here's another great question from list member Glenn B. (used with permission). He's asking about Amibroker, but this applies more generally to any backtest.

Glenn B.:

Should I include these in backtests? I know AmiBroker has built-in commission tracking, but I didn’t see much on slippage. Is it worth factoring in, or better to skip?

Dave:

You should include commissions in your backtests, but I don't recommend including slippage.

Here's why I don't.

Commissions are 100% predictable - there's no guessing - like death and taxes, they're a fact of life.

For trading strategies with lots of trades, including commissions can change the optimization a surprising amount.

Slippage, however, is incredibly unpredictable.

Trying to model slippage is hard and not worth the effort, in my opinion. (Sometimes your trades will experience positive slippage - meaning you get a better fill than your backtest - try modeling that!)

Does that mean you should put your head in the sand and pretend slippage doesn't exist? Of course not.

You should have a general sense of how much slippage would make your strategy unprofitable.

Knowing that before trading your strategy with real money will give you a quicker path to confidence once you go live. (For more info, listen to the discussion on "pre-mortems" in the podcast episode called Your Backtest Looks Great - What Could Possibly Go Wrong?)

Rather than trying to predict slippage on any particular trade, I prefer to treat the backtest as what's theoretically achievable by the strategy.

Your live trading will, of course, fall short of that threshold by some amount, but that's fine - your strategy shouldn't require perfect execution to be profitable.

When measuring performance against the backtest, though, I prefer to compare against "perfect execution."

Great question, Glenn B. - thanks for sharing with the group.

-Dave

Trading Computer Specs

2025-08-27T19:30:00-04:00

As mentioned this week in How Not To Buy a Trading Computer, here are the specs for the system I bought a few weeks ago.

It's working well, and a couple of traders I'm coaching have used this as a reference to buy their own systems.

One of them had an 80% reduction in the time it takes to backtest the entire market with Amibroker compared to their previous system.

The thing I love about this system is that the CPU is liquid-cooled. This means there are no noise-making fans to cool the CPU.

In fact, I completely turned the case fans down so the only fan running is the video card (which is surprisingly quiet), and it stays plenty cool.

The only thing missing from this quote is two SSDs - one for the system drive and one for a separate drive that I've dedicated to Amibroker backtesting and market data (which is important).

With this setup, I can backtest 17 years of 1-minute data across the entire market in about 35 minutes.

Here are the specs and prices I paid:

Trading Computer Specs

-Dave

Is the Optimize Function in Amibroker Useful?

2025-08-26T19:30:00-04:00

Here's a reader question from Glenn B. (used with permission):

Glenn B.:

After learning about the Strategy Cruncher, the Optimize in Amibroker feature seems like it could easily lead to curve fitting. Are there scenarios where you find it genuinely useful?

Dave:

Good question. And, for the most part, the answer is no.

Here's what the Optimize function does:

When you do a backtest in Amibroker, gap_percent is the value in the default variable.

When you click Optimize, though, Amibroker will run a backtest for every value defined in the Optimize call from min to max in steps of step and then give you aggregate results across all the individual backtests it runs.

The Optimize function in Amibroker is made completely obsolete by the Strategy Cruncher.

The Cruncher tells you the optimal rules you can apply to your strategy to increase profitability in seconds.

To do that with the Optimize function would take literally years to complete.

There is, however, one rare situation where I might use it.

It could be useful to run X different versions of a backtest to figure out the best "starting point" strategy to feed to the Cruncher. (Where X is relatively small.)

It can be a convenient way to run a small number of backtests to get a general sense of a good starting point.

The more you use the Optimize feature of Amibroker, the harder it is to avoid curve fitting, so it should be used very sparingly, if at all.

Thanks for the question, Glenn B.

-Dave

How NOT To Buy a Trading Computer

2025-08-25T19:30:00-04:00

In this week’s episode of Line Your Own Pockets, we discuss buying a new trading computer.

I recently replaced my trading computer with a new one.

And it was a huge pain.

We discuss:

Why I no longer build my own trading computers
The mistake I made when buying a new one
How I resolved it
How you can avoid the same mistake
Much more…

LISTEN NOW »

-Dave

P.S. Holiday Reminder - One week from today is Labor Day, and the markets will be closed. Plan something fun if you haven't already!

Which Equity Curve Is Better?

2025-08-22T19:30:00-04:00

Here's another Strategy Cruncher question from Mugu (shared with permission).

Mugu:

I am confused by my back test optimization results below regarding column Diff1:

How should I interpret this? It could be gold or bad data. Your thoughts?

Dave:

This is a situation that often confuses traders.

Notice the red line (the set of worst trades the cruncher found) was above the green line (the set of best trades), but they ended up with the same profit.

Aren't these two strategies about the same? No!

Look closely at the number of trades in each line (look at the legend).

The green line achieves the same total profit as the red line with only HALF the trades.

The cruncher found a way to make your strategy far more efficient:

Fewer trades with the same total profit
Increase in profit factor to 3.92
Increase in win rate to 76%

Think about the two strategies.

Which one gives you a better path to confidence to trade it eventually with significant size?

It should be pretty clear!

Thanks for the question, Mugu.

-Dave

P.S. When you're ready to take your strategy to the next level, the Strategy Cruncher is here.

Your First Amibroker Import

2025-08-21T19:30:00-04:00

When you first start using Amibroker, most traders are very eager to get a lot of historical data into their database.

Often, they're accustomed to backtesting in Trade-Ideas, and realize some of their strategies will benefit from a larger backtesting window.

It's tempting to spend your time loading the database with all the data you can obtain (e.g., I have over 17 years of one-minute bar data in mine).

You might be surprised to learn I don't recommend doing this right away.

Here's why.

Importing the data can take a while. It might take a script running all weekend to gather all the data, convert it to the proper format, and import it into Amibroker.

I've seen traders spend 3 days importing data, only to realize their data was slightly incorrect and then have to start all over.

Three days wasted!

Instead of importing all the historical data at first, just import a handful of recent market days.

There are a few benefits to this approach.

First, it will be much faster. You'll have data to start doing some initial tests in minutes rather than days.

The real work begins after you import your data.

Second, having a smaller database will make your initial testing way faster.

You won't be tempted to run a backtest across all your data (which will take a while), and when you have to verify your backtest is working properly, it will feel a lot less overwhelming to review trades over a smaller timeframe.

Your feedback loop will be a lot faster.

You'll learn the basics way quicker.

After you've created a backtest and verified it works as expected, then you can take the time to import all your historical market data.

And you'll be ahead of the game.

-Dave

P.S. Do you want to get up to speed on Amibroker really quickly? Then you'll love the Amibroker course I'm putting the final touches on. Traders who have taken the course report that they've saved months of time and effort.

Click here to be among the first to be notified when it's available and get early-bird pricing.

Sources for Data in Amibroker

2025-08-20T19:30:00-04:00

There are several sources for market data that you can use in Amibroker.

Each has benefits and drawbacks.

It's a lot to learn all of Amibroker right from the outset, so it's useful to separate usage into two phases:

Backtesting
Real-time trading

Backtesting is simpler since you don't need to generate signals in real-time.

For that reason, I always have traders start with the backtesting phase first.

(And when you create your strategy with an awesome equity curve and you're ready to trade it, you'll have plenty of motivation to tackle the more complex real-time workflow.)

So let's focus on data sources for backtesting.

The cheapest way to get lots of market data for backtesting is the Polygon flat file service.

Polygon provides a flat file each day of intraday minute bar data that you can download.

You'll need one level up from their free service (currently the "Stocks Starter" plan) to access the daily file downloads.

Once you get access, you'll need to do some Python/LLM wrangling to get the data in a format that Amibroker can import.

You can completely automate this process using Amibroker's Import Wizard and ASCII Import.

Other options for backfilling your database are:

Amibroker's IB plugin (free with an IB account, but the IB data is rate-limited so it's not practical for complete backfilling)
IQFeed real-time data service (also has excellent backfilling history, but most costly than the other options)
eSignal real-time data service (nice backfilling history, but even more costly than IQFeed)
Norgate data (no intraday data, daily only)
See P.S. for another option from a list member

Tomorrow I'll go over the best way to approach your first data import.

-Dave

P.S. Long time list member Matt H. created another way to download historical data for free to import into Amibroker through Alpaca. He's graciously shared his Python code to do this through an Alpaca account. I haven't tested this, but here's the link to his Github repository. Thanks, Matt!

Backtest Speed

2025-08-19T19:30:00-04:00

Does the speed of your backtest matter that much?

Backtesting differs from live trading since you can do it after hours.

So does it really matter if it takes a while to complete?

It matters a lot!

A backtest is an attempt to answer a question.

You've developed a theory and determined a way to test it without putting money at risk.

Think of a backtest as your personal question answerer.

But if it takes days or months to get answers, then the answers become less valuable.

The quicker you can generate answers to your questions, the better.

Zoom out and think about your entire feedback loop.

From the initial thought in your head ("hey, this chart looks odd - I wonder if that has an effect on my strategy?") all the way to applying a rule to make your strategy more profitable.

Most new traders think you'll be answering a question or two, and then you'll have your final answer - your profitable strategy that never changes.

But that's not how it works - you'll be constantly asking questions about the markets.

And the answers are great, precisely because they often generate more questions that you hadn't considered before.

So your question/answer feedback loop is critically important. (Way more important than even the strategy you trade.)

How can you minimize the time to generate answers?

How to Trade When Traveling

2025-08-18T19:30:00-04:00

In this week’s episode of Line Your Own Pockets, we discuss trading when you travel.

It's not something you have to give much thought to if you're not trading with an edge, but if you've got a solid trading business, then vacations can be incredibly expensive when you include the cost of missing trades!

We discuss:

The best remote desktop solution I've found (by far!)
Why vacations are different when you have a trading edge
How to prepare for trading on the road
How to do a "dry run"
Much more…

I also share the notes of a trader I coach who traded during his recent trip to Aspen.

Lots of things to learn in this episode...

LISTEN NOW »

-Dave

P.S. We just completed our first year of the podcast! Thanks so much for listening - if you enjoy it, please consider giving it a rating and leaving a review on your podcast platform of choice.

That helps other traders find the show.

Databases in Amibroker

2025-08-15T19:30:00-04:00

An important part of using Amibroker is understanding how the database works.

All market data is stored locally in an Amibroker database, which is simply a folder with various files and subfolders in it.

You can set up multiple databases and switch between them.

And I encourage traders to use two databases:

One for backtesting with lots of data and another for real-time trading with the minimum data required.

This allows you to separate your work and get the most out of Amibroker depending on the situation.

When real-time trading, time and speed are critical.

But when you're backtesting, time is not of the essence, so speed doesn't matter as much.

So it's smart to set up your databases to reflect this.

My backtesting database has 18 years of 1 minute bars for every symbol across the US markets.

My real-time database contains less than one year.

The backtesting database isn't nearly as fast as the real-time database, but that's fine - I don't need it to be as fast.

That said, Amibroker is much, much faster than backtesting in Python.

I've worked with traders who see a 5X increase in speed in their backtest switching from Python to Amibroker!

Next time I'll discuss backtesting speed and why it's more important than you think...

-Dave

P.S. Are you stuck in your trading? You know you have potential, but you're not sure what to do next? Get unstuck with my one-on-one coaching call.

Using Amibroker - First Steps

2025-08-14T19:30:00-04:00

(Note: This is the first post in a series about using Amibroker for creating and trading strategies.)

Amibroker is a tool I've been using for backtesting for at least 15 years.

It's a powerful tool for backtesting, real-time charting, and trading.

It works well with Trade-Ideas (more on that later) and other tools.

But it can be overwhelming when you first start using it.

It's useful to think about using Amibroker in two phases:

Backtesting
Real-Time Trading

You should start with backtesting - that will be cheaper to get data and you minimize the technical hurdles required to move your trading needle.

The idea is that once you get a strategy you're confident in, then you can take the next step of using real-time data in Amibroker, which will add some complexity that you can ignore for now.

Why would you want to use Amibroker?

You have ideas to test that would benefit from a longer backtesting window than is available in Trade-Ideas
You want to backtest on daily and intraday data, which rules out RealTest
You want to backtest across all stocks, which rules out almost every other backtesting software out there
You want to be able to add custom columns to your backtest for use in the Strategy Cruncher
You want a completely customizable charting platform that runs locally (Amibroker's charting is way underrated)

For now, focus on backtesting and creating your strategy.

Once you create your strategy with a fantastic equity curve, you'll have plenty of motivation to progress to using Amibroker with real-time data.

Tomorrow, we'll focus on the very first step: creating your database in Amibroker.

-Dave

P.S. Are you interested in using Amibroker for backtesting? I’m putting the final touches on a course on Amibroker that shows how traders who actually trade for their income use it. Click here to sign up to be notified when it’s available:

Does Your Strategy Tell a Coherent Story?

2025-08-13T19:30:00-04:00

First, one of my favorite quotes of all time by John Feynman:

"The first principle is that you must not fool yourself, and you are the easiest person to fool."

This should be in the back of your mind whenever you're optimizing trading strategies.

A skeptical mindset in this phase can save a lot of time and drawdown pain later.

When you first start optimizing a strategy, it's easy for traders to fall into the trap of "following the data" too closely.

Not thinking deeply about which rules to apply to a strategy.

Adding too many rules, because, hey, that's what the data is telling me, and who am I to argue with the data?

What many traders overlook when adding rules to their strategy is ensuring the rule tells a coherent story.

The next time you add a rule to your strategy, imagine having to present your case to a jury of skeptical traders that your rule is predictive and worth adding.

Given the strategy's entry signal, WHY will this rule improve the strategy?

"Because the data says so" is not good enough - but that's what most traders use to justify it.

Does the rule tell a coherent story?

It better!

-Dave

P.S. I'll be doing a series of emails on Amibroker soon, a backtesting and charting software I've used for years. Several traders have beta tested my Amibroker course, and the feedback has been excellent. Look for an announcement soon on the official course launch and early bird pricing.

A Daily Routine

2025-08-12T19:30:00-04:00

Here's a quote from the War of Art, a book I'm reading about artists. (There are surprising parallels between great artists and traders.)

Someone once asked Somerset Maugham if he wrote on a schedule or only when struck by inspiration. "I write only when inspiration strikes," he replied. "Fortunately it strikes every morning at nine o'clock sharp.”

If you only review your trades when you feel like it...

If you only brainstorm for new ideas when you feel like it...

If you only try to get better when you happen to be in a drawdown...

Then you're putting a ceiling on how good you can be.

Inspiration for improving your trading should strike every day when the closing bell rings.

It doesn't take much to make big improvements.

But it does take consistency.

How can you get just a little bit better today after the close?

Imagine doing that every single day.

-Dave

Follow Up on Running Out of Buying Power

2025-08-11T19:30:00-04:00

In this week’s episode of Line Your Own Pockets, we follow up on last week's discussion on buying power.

There are serious risks when using leverage, so controlling risk is always the number one priority.

We discuss:

Can you lose more money than is in your account? (Spoiler: yes)
What happens when that occurs?
You don't have a "right" to a brokerage account
Are there catastrophic risks to your trading that you're not thinking about?
Much more…

LISTEN NOW »

-Dave

Switching from Swing Trading to Day Trading

2025-08-08T19:30:00-04:00

A trader recently emailed me about potentially switching from swing trading to day trading.

Some of his hesitations are:

Sunk cost into his current swing trading process
Significant learning curve to switch to day trading
A reliable source for intraday data
Confidence in day trading idea generation

I made this switch over 25 years ago, so I have lots of thoughts on it.

But I want to poll traders on the list to get your thoughts.

Have you switched from swing trading to day trading?

How did it go? What advice would you give to someone considering the move?

Hit reply and let me know.

-Dave

Deciding Between Two Ways to Improve a Strategy

2025-08-07T19:30:00-04:00

Strategy Cruncher user Mugu sent me this question (shared with permission). This is a great question that gets to the heart of how to improve strategies.

To give you some background, Mugu submitted his backtest from Amibroker with column data he added using the sample code provided by me in the forthcoming Amibroker course.

The Cruncher parsed through his backtest and is suggesting optimal ways to improve his strategy. He's trying to choose between two ways to make his strategy more efficient. That is, fewer trades but higher profit per trade.

Mugu:

In which order should I implement the suggested column filter improvements on a report like this.

Should I prioritize curve improvement or total profit improvement on the Cruncher output?
The second suggestion in the report results in a good improvement in profit factor + Sharpe ratio and half the exposure of unfiltered strategy run. It seems to me the second suggestion should have been ranked as number one on the report from the cruncher?

Dave:

The ranking in the cruncher report is ordered by the optimal way to split the trade set where the difference between the average profit of the green set and the red set is largest.

(It's hard to explain, but the sample report gives a good visualization of the ranking. Scroll through the charts here.)

And it's doing that across all columns - no matter how many you've included.

(A Trade-Ideas backtest has over 200 columns and I have Amibroker backtests with over 300 columns.)

In the charts from Mugu's cruncher report, notice the smoothness of the green line in the first one compared to the second one.

I consider that more consistent and therefore more likely (although not guaranteed) to continue into the future.

Also look at the second chart. In that one, the red line is smoother than the green one. In fact, the recent period shows performance that's roughly equal across both the green and red lines, and the red line is profitable overall.

For these reasons, all things equal, I'd prefer the first suggestion from the cruncher.

Thanks for sharing, Mugu.

-Dave

Which Metrics Are Best?

2025-08-06T19:30:00-04:00

Here's a reader question from Rami A. (shared with permission):

Rami A:

I’m trying to create a day trading strategy. Which financial metrics should I consider, such as risk-reward ratio, Sharpe ratio, drawdown, etc., to determine if it’s a good one?

Dave:

It's easy to overcomplicate things here for no real benefit, so I keep it super simple:

Profit Factor
Win Percent
Total Profit
Trades Per Day

And, of course, the most important factor is looking at the equity curve.

That's it!

Why is the equity curve so important? Because it's telling you a story that no metric can capture.

It's telling you the pain you would have felt during those drawdowns.

If I had to choose just one "metric", it would be the equity curve (by a mile).

When you find a smooth equity curve, it gives you a lot of flexibility in trading the strategy.

Thanks for the question, Rami!

-Dave

Follow Up to What Is The Best Strategy

2025-08-05T19:30:00-04:00

Here are my thoughts on my original message, where I asked which strategy you think is best, and then later posted the responses.

There was some insightful feedback, so it's worth going back and reading those threads if you haven't already.

This is one of those rare strategies where one or two of the columns I've added to the backtest are highly predictive.

In fact, each version of the strategy is just using increasingly extreme values for just two columns.

For that reason, I'm not worried about curve fitting, even with version 4 of the strategy.

If I had to use several rules that the Strategy Cruncher suggested to create version 4, that would have been a different story.

When you identify a column or two that are highly predictive, it gives you lots of ways to trade the strategy. (There are no wrong answers to my original question.)

In this situation, I like starting with a version that trades frequently and doing so with tiny size.

This lets you quickly see if the trades are measuring up to the backtest in live while risking a negligible amount of money.

More on this topic and next steps soon...

-Dave

Is Running Out of Buying Power A Good Thing?

2025-08-04T19:30:00-04:00

In this week’s episode of Line Your Own Pockets, we discuss one of my favorite topics.

I remember feeling a sense of shame the first time I ran out of buying power in my trading. It took me a while to realize that it's a good thing.

We discuss:

Why you should think about the efficient use of buying power
What to do when you run out
How buying power issues are fun to solve
What to do if you aren't running out of buying power
Much more…

LISTEN NOW »

-Dave

In-Depth Response to What Is The Best Strategy

2025-08-01T19:30:00-04:00

Long-time list member Mahmound G. responded to my original message about different versions of a strategy in addition to the other reader responses I posted yesterday. (Shared with permission.)

Mahmoud G:

The best scenario, in my opinion, will depend on two factors: the trader's career stage and their execution method (fully automated or discretionary).

Discretionary traders should adopt high–winning-percentage strategies, as they won't be able to capture all the backtested trades. This can significantly impact the strategy's performance and cause a major divergence from the backtest results. Scenarios 3 and 4 would be more suitable for discretionary traders.

Career stage will also determine the balance between drawdown tolerance and profitability. In the early phases, traders usually have smaller accounts, so their tolerance for losses will be more critical.

Case 1: Discretionary trader + Early Career = Version 4 (building small account + missing traders won't highly impact the backtest results)

Case 2: Discretionary trader + Experienced trader = Version 3 (favoring profitability over winning % + missing traders won't highly impact the backtest results)

Case 3: Automated trader + Early Career = Version 2 + taking version 4 with higher size (building small account + missing traders rarely occur)

Case 4: Automated trader + Experienced trader = Version 1 + taking version 4 with higher size (favoring profitability over winning % + missing traders rarely occur)

Very interesting breakdown here.

Any thoughts on this approach?

I'll share my thoughts next week. (Speaking of, see the P.S. below)

-Dave

P.S. I'll be in NYC most of next week speaking at the event with SMB Capital. If you're interested in meeting up for coffee or a drink, hit reply and let me know.

Responses to What is the Best Strategy and Announcement

2025-07-31T19:30:00-04:00

Announcement: I'll be speaking next week with list member Garrett Drinon from SMB Capital in their Bionic Trader meeting. Come join us!

Several of you responded to my question a couple of days ago about which version of my strategy you think is best.

Here's a summary of the particularly good ones (shared with permission):

Isaac H:

I would lean towards version 1 if slippage and fees aren't eating all the profits... if they are, I would go with version 2 because I would assume it makes the most for a given position size. I'm not confident the drawdowns would be as small as versions 3 or 4 though.... which may mean you could more easily size up versions 3 or 4.

Fabrizio A:

I probably would like to trade the version 2 even if i'm not sure if there is a mathematical reason... I usually want to know avg winner and avg loser and calculate Kelly, which i use more as a metric than as a sizing tool. Anyway, just following gut feeling, I like profit factor, win rate, and trade frequency of that version 2.

Matt H:

I don't know which is the best version, but I like version 2 with version 3 1.5 size and version 4 with 2 or 3x size (maybe more)

Nish K:

Version 4 looks great as it has highest win% so PSYCHOLOGICALLY easy to execute. It has best profit factor. It also has least trade count so least fees and slippage but enough for statistically significant.

Roget B:

Is this a trick question? Haven't you taught us it all starts and ends with the equity curve!

That said, I'd start with the one with the fewest rules and a solid PF - likely #2, maybe #3. #4 is way too overcooked. I'd want to see it eliminate a smaller percentage of trades with each iteration, not more.

All excellent responses! (Glad to see Roget listening closely to my preaching about the equity curve.)

There was another in-depth reader response that deserves its own email, so look for that tomorrow, and then I will share my thoughts next week.

Thanks again to all who responded and agreed to share with the group.

-Dave

P.S. I'll be in NYC most of next week speaking at the event with SMB Capital. If you're interested in meeting up for coffee or a drink, hit reply and let me know.

Long and Short in Same Backtest?

2025-07-30T19:30:00-04:00

New Strategy Cruncher user Mugu M. wrote in with an excellent question (shared with permission):

Mugu M:

Does it make sense to send the Longs and Shorts separately into the Cruncher? For example, when I’m using a momentum oscillator like RSI, extremes like 70, 30 will be used for overbought/oversold to decide buy/or sell..but the Cruncher returns one suggested optimal value that does not make 100% sense for both buy/sell.

Dave:

My default is to separate longs and shorts for optimization, assuming there are enough trades in the backtest to warrant this approach.

If you feel there aren't enough trades in the backtest to get confidence in optimizing, then it is certainly a viable approach to keep them together.

But combining them does cause weird situations like this one for RSI.

The issue is that the RSI for the long side is looking for a value of 70, but the equivalent value for the short side is 30.

This is a perfect example of a column that isn't normalized, so you're not giving it the best chance for the cruncher to detect it for importance and therefore improve your strategy using it.

Here's a simple way to create a normalized version of RSI across direction just for this very purpose.

Add a new column called directional_rsi.

For longs, directional_rsi is the same as rsi.

But for shorts, directional_rsi should be 100 - rsi.

For shorts, a value of 30 for rsi has a value of 70 for directional_rsi.

Now, the Cruncher can measure extremeness across both directions and weed out the weaker trades.

Great question, Mugu - thanks for sharing!

-Dave

P.S. Are you interested in creating your own strategies? If you’ve got a backtest, you owe it to yourself to try the Strategy Cruncher.

Here’s what one user said recently about it:

Matt: “By using the Strategy Cruncher, I can very easily find the very best filters for any type of strategy backtest without being concerned about over-optimization. Last week, in a mean reversion strategy, in 4 iterations of the cruncher, I found filters that reduced drawdown and increased overall profit by 10x.”

Which Is The Best Strategy?

2025-07-29T19:30:00-04:00

Here's a good example of the deep versus wide approaches.

This is a strategy I'm working on, and I'm trying to decide which version to go live with.

My approach to backtesting is always the same - start with no filtering, then use the Strategy Cruncher to figure out which trades to remove (without curve-fitting).

All these versions correspond to the same entry signal, but in each subsequent version, I've used the cruncher to add a rule to remove the poorest trade set.

So, version 4 is a subset of version 3, which is a subset of version 2, etc.

Using only this information, which one do you think is best and why?

Version 1:

Profit Factor: 1.87
Win Percent: 53.8%
Trades: 3,859
Trades per day: 3.3

Version 2:

Profit Factor: 3.29
Win Percent: 55.1%
Trades: 1,619
Trades per day: 1.4

Version 3:

Profit Factor: 4.65
Win Percent: 63.2%
Trades: 427
Trades per day: 0.4

Version 4:

Profit Factor: 7.59
Win Percent: 72.6%
Trades: 106
Trades per day: 0.1

-Dave

P.S. Are you interested in creating your own strategies? If you've got a backtest, you owe it to yourself to try the Strategy Cruncher.

Here's what one user said recently about it:

Matt: "By using the Strategy Cruncher, I can very easily find the very best filters for any type of strategy backtest without being concerned about over-optimization. Last week, in a mean reversion strategy, in 4 iterations of the cruncher, I found filters that reduced drawdown and increased overall profit by 10x."

Deep vs. Wide: Two Paths to Trading Profits

2025-07-28T19:30:00-04:00

In this week’s episode of Line Your Own Pockets, we discuss two very different mindsets for developing strategies.

You can take lots of trades with a smaller average profit per trade, or fewer trades with a larger average profit per trade.

These are both perfectly valid approaches, but the mindsets couldn't be more different.

We discuss:

What's the difference between the two approaches?
What can traders with one mindset learn from the opposite approach?
Which approach is better?
Much more…

Which mindset do you have?

What can you learn from the opposing camp?

LISTEN NOW »

-Dave

"I Don't Have Time"

2025-07-25T19:30:00-04:00

A lot of traders say they don't have time to work on their trading.

I used to think this was a problem to try to overcome.

But for traders in a certain situation, this is a strong predictor of future success.

Why?

For most traders, the hard part is coming up with ideas to work on.

Thinking of ideas that will have a profitable edge.

If your biggest problem, though, is not having enough time to work on your existing ideas, that's a great sign.

That means you have more profitable ideas than time to work on them.

And that is a problem you can solve.

And it's much easier than coming up with ideas in the first place.

Tolstoy had thirteen kids when he wrote War and Peace.

He knew he had a good idea, so he solved his "I don't have time" problem.

Focus on the profitable ideas, and I guarantee you'll find the time.

-Dave

Overriding Your Trading System

2025-07-24T19:30:00-04:00

You've put in the work:

Backtested your trading strategy
Optimized it so you're taking the most profitable set of trades
Responsibly put it into production with small size at first

But you still find yourself wanting to override your system.

"I think that stop should be looser."

"This trade doesn't make sense because of $REASON, so I'm going to close it early."

"If I give this one more time, surely it will work."

All these doubts you have during the day are normal.

However, acting on them can erode your entire trading process over time.

When you override your system, you're telling yourself that the work you did to prepare wasn't good enough.

You're not respecting it.

All those thoughts you had listed above could be tested.

Next time you have those doubts, instead of overriding your system, make a detailed note instead and add it to your research TODO list.

And then see what would happen if:

You used a looser stop across all your trades
You added $REASON to your backtest as a column to see if it really has an effect
You held all your trades a little longer

Tracking down those answers outside of regular trading hours makes your trading process stronger over time rather than eroding it.

Amateurs use their doubts to override their work, but pros use them to get better.

-Dave

A Cure for Helicopter Parenting Your Trades

2025-07-23T19:30:00-04:00

The last message about helicopter parenting your trades struck a nerve with several readers.

Here's a way to get rid of your over-involvement in your trades.

Continue trading as you normally do, but...

For each trade where you intervene and override your plan, create a tag called "Overrode" (or even "Helicopter" lol) and apply that tag to these trades in your trade journal (you ARE keeping a database of your trades, right? Right?!?)

Let some time go by and be honest and consistent in applying the tag.

After a while, filter your journal on this tag and compare the results to a baseline (ideally a backtest, but it doesn't have to be.)

You'll very likely see that the trades with this tag underperform the others.

That is, the trades where you intervene and override your plan are worse.

This makes it very clear that there's a cost to your meddling with your trades.

When you see this in such stark terms, it becomes highly motivating to change the behavior.

But what if your helicopter parenting improves those trades?

That's a great problem to have - and one that I'll address tomorrow.

-Dave

Helicopter Parenting

2025-07-22T19:30:00-04:00

If you have kids, you know the kind of parent I'm talking about.

They're overly involved.

Making sure things are perfect.

The kids would be better off if the helicopter parent loosened their grip and gave them more autonomy.

The freedom to make a mistake or two.

It's hard to see in the moment, but that's the better approach in the long run.

So what does this have to do with trading?

I see a lot of traders doing the same thing with their trades.

Monitoring every tick during a trade.

Not providing any real value - just being overly involved - which leads to mistakes.

Are you helicopter parenting your trades?

-Dave

Restrict Your Strategy to a Specific Symbol List?

2025-07-21T19:30:00-04:00

In this week's episode of Line Your Own Pockets, we have a surprisingly heated discussion about whether to restrict your strategy's universe of symbols or not.

This seemingly simple question has numerous implications.

Can you backtest a strategy that trades a symbol list you don't control?
Is each symbol in the list weighted equally?
Is a symbol list simply a filter?
Should you include or exclude ETFs in your strategy?
Much more...

Buckle your seat belts, this is the biggest disagreement Michael and I have had on the podcast so far!

We don't come to blows, but pretty close.

Which side do you fall on?

LISTEN NOW »

-Dave

The First Thing To Do With Any Backtest Software

2025-07-18T19:30:00-04:00

You've just gotten access to a powerful backtesting engine like Amibroker, RealTest, or Trade-Ideas.

You can't wait to dive in and get your strategy working.

But there's one thing you should do before writing any code or configuring your strategy.

And it's probably not what you think.

You should remove any restrictions on buying power or account size.

That is, have the backtester assume you have unlimited buying power.

But why? Shouldn't you configure your exact account size and buying power settings? No.

There's a good reason for this.

When you run your first backtest, you want to avoid any artificial filtering. You want the entire set of trades that match your rules.

Let's say you're testing a strategy that has up to 10 trades on some days.

When you restrict your buying power in the backtester, it might only return the first 5 trades on those days.

So it will artificially hide half of the trades on those days from your backtest.

This is NOT what you want.

You want to start with the entire picture - all trades that your system could take - even if it's way more than you have buying power for.

That's fine, because you're going to filter this initial trade set down, removing lots of crappy trades using filters from your columns.

You're going to end up with a much better-looking equity curve by the time you start trading it.

But that's literally not possible if your backtester is trying to be "smart" and excluding trades.

-Dave

Brute Force Optimizations

2025-07-17T19:30:00-04:00

Here's a question from Matt H. (name used with permission):

Matt H.

How do you optimize things like the gap %, how long a moving average period value should be or other variables that might make sense in an automated guess and check scenario? Running a backtest takes a couple of minutes, but running an optimization (in Amibroker or TradeStation) can take hours or days.

Dave:

Optimizations in tools like Amibroker, TradeStation, or NinjaTrader are what I consider brute force optimizers.

If you're planning on living for several centuries, they're not bad. Otherwise, these tools are a waste of time.

(This is no exaggeration. Try brute force optimizing 200+ columns in a backtest. It will take at least a century to complete, but the Strategy Cruncher will do it in seconds.)

Gap percent is very different than the moving average period value.

Add Gap percent to your column library, and the cruncher will let you know when it's predictive for any strategy you run it on.

The moving average period value is different. If the moving average is being used in your strategy's signal, then I'd use the approach I mentioned yesterday: pick 3-4 combos and run backtests for all of them to pick your values.

If the moving average values you're referring to are for columns in your backtest to potentially filter on, then I would pick ~3 different values and add them each as columns.

I have different values like this in my column library that I label:

Long
Medium
Short

There won't be a single, magical value for the moving average period that will make or break your strategy.

In fact, if there is a specific value for the period that is significantly better than adjacent values, that would worry me!

-Dave

P.S. Are you interested in using Amibroker for backtesting? I'm putting the final touches on a course on Amibroker that shows how traders who actually trade for their income use it. Click here to sign up to be notified when it's available:

Optimizing Time of Day Across Multiple Signals

2025-07-16T19:30:00-04:00

Long-time list member Fabrizio A. sent me this question (name used with permission):

Fabrizio A.

Trade-Ideas backtest results present some challenges because TI only keeps the first occurrence of each alert per symbol per day. That means the Strategy Cruncher can't evaluate whether a better trade might have occurred later in the day. So basically, it only works properly if the alert is natively designed to trigger just once per day. In other cases, I use the optimizer for other types of filters, but I need to try different time windows by running multiple backtests

Is there a better way to approach this?

Dave:

Fabrizio is describing the backtesting puzzle I posted about several days ago.

How do you optimize a strategy that's based on an alert that can happen multiple times a day (like a new high)?

When you apply a filter, oftentimes you're simply "postponing" the trade in a symbol that you believe should be filtered out since a symbol can print many new high alerts throughout the day.

(Contrast the new high alert with an alert like an opening range breakout, which can only happen by definition once per day.)

So, how do you optimize a strategy based on an alert that can happen multiple times?

There are two main ways to approach this problem.

Optimize on columns whose values don't change during the day
Select a handful of combos to run backtests on

Let's take #1:

When you restrict your columns to ones that don't change during the trading day (ATR, Gap%, etc), you simplify the problem significantly since you eliminate the "peek-a-boo" trade issue above.

That is, when you filter on columns that don't change, even if a new high alert appears throughout the day it will still be filtered out.

This is one of the main reasons I prioritize columns whose values don't change during the day.

When this isn't possible (maybe none of the columns are predictive enough to use), then it's perfectly fine to run multiple backtests to try to find the best starting point.

I wouldn't obsess too much about finding the "perfect" window of time for your strategy, though.

There's likely not a "holy grail" time window. Just use your experience about the trading day to choose 3-4 windows of time that make sense and run backtests for each of them.

I'd be looking at the results to compare:

The number of trades (more = better)
Proximity to the open (more movement, in general)
The metrics/equity curve of each starting point backtest

Great question, Fabrizio - thanks for sharing with the group!

-Dave

Less Precision to Avoid Curve Fitting?

2025-07-15T19:30:00-04:00

Another question from Hanns K. about the Strategy Cruncher and adding filters to your strategy to make more profit with fewer trades.

Hanns K.

I've read that you shouldn't optimize with a too high "resolution" in order to avoid overfitting and not to create too high expectations of the strategy's performance, since it probably will never reach this historically optimal performance in live trading. I have the feeling the Cruncher is doing that to some extent and that the brute force method probably is a bit more conservative by doing larger step sizes during optimization.

Dave:

Good question, Hanns.

I see this as a variation of the round number fallacy, where traders choose round numbers for the values for their rules even though it's not optimal as a way of somehow avoiding curve fitting.

The strategy and the market don't care that you've chosen a round number that appears more "pleasing" compared with the optimal number.

Also, let's take the precision argument to its logical conclusion.

If you think using less precision will be better in the long run, then maybe you should use a LOT less precision - that would be even better according to this theory.

So let's say the Cruncher suggests a value of 5.6 for gap percent for improving your strategy. That is, if you were to apply the rule and only take trades where the gap percent is greater than 5.6, you would get the same profit with fewer trades.

In an effort to supposedly avoid curve fitting, you choose 6 for the value (rounding up from 5.6).

If that's somehow an improvement, why not choose 10? That's an even more pleasing number!

You can see where that leads.

The best number to use is the one that has shown itself to be optimal over a long historical period.

Thanks for the question, Hanns K.

-Dave

P.S. Are you still fooling with Excel to try to create your trading strategy? The Strategy Cruncher lets you generate more profit from fewer trades in your backtest in seconds, not days or weeks.

Check Out the Strategy Cruncher

Hide Your P&L? Yes

2025-07-14T19:30:00-04:00

In this week's episode of Line Your Own Pockets, we discuss a bad habit that's easy to avoid: looking at your P&L.

There are a lot of emotions wrapped up in watching that number and it can encourage you to make bad decisions.

We discuss:

How so much effort is done by platforms to make the P&L number as attractive as possible
Why watching that number is toxic to good trading
Even at the end of the trading day, your P&L number is ultimately irrelevant
Much more...

LISTEN NOW »

-Dave

Optimizing on Time of Day

2025-07-11T19:30:00-04:00

Here's a question from Hanns K. (name used with permission) about optimizing based on time of day.

Hanns K.

About brute force vs. Strategy Cruncher: the speed of optimization is impressive and definitely faster than brute force by several orders of magnitude.

Using my systems for intraday futures trading, I found that time filters are among the most powerful ones. So I allow trading during a certain time window each day only and also close trades at a certain time. I was wondering if you see a possibility to incorporate time filters into the approach. Of course it would be possible to filter out certain trades completely based on the opening time of the position but I think this would not give the complete picture.

Dave

You're right, time of day is an important filter to consider.

If you're not considering time of day, I can guarantee you're taking a lot of trades that you shouldn't be.

So how do you determine what the cutoff should be for time of day? And is using a cutoff for time of day even worth it when considering other columns that could be even MORE predictive?

Here's the approach I use.

For time of day, I don't use a timestamp (which doesn't help much), I use the number of seconds since the market open.

So, for example, if the trade enters at 9:31:00, the value for the seconds since open column is 60 since the market opens at 9:30:00.

Premarket numbers are negative (which is fine), so a trade that enters at 9:20:00 is -600 (-10 minutes X 60).

This normalizes time of day into an integer that you can feed to the cruncher.

Now, the cruncher can tell you how relatively predictive time of day is compared to dozens of other columns in your backtest.

Once you see how important (or not) time of day is compared to other columns, you can decide to use it or not in your strategy.

It can also lead you to completely new strategies based on the findings.

For example, if time of day is predictive, you can restrict your strategy to a tighter window of time and loosen the remaining filters to find more profitable trades during the most profitable time of day.

Great question, Hanns K., and thanks for sharing this with the group.

-Dave

Trading Goals

2025-07-10T19:30:00-04:00

Do you have a goal to be the best trader in the world?

Or to make enough money from your trading to buy a yacht?

It's counterintuitive, but grandiose goals like these are signs of an amateur.

The best traders are setting goals that are far more acheivable.

I like to have traders set a range of goals:

Conservative
Moderate
Radical

That way, you can set an ambitious goal for your radical one, but not be devastated if you miss it since you'll have some modest goals you're shooting for as well.

Of course trading is about making money, but it's better to be process oriented rather than results oriented.

For example, instead of a goal to make $X dollars this year, set a goal to get 3 new strategies trading live.

Or backtest Y new ideas.

The results (profits) will take care of themselves if you improve your process.

-Dave

Fold or Raise Situations

2025-07-09T19:30:00-04:00

As many of you know, I'm a poker enthusiast.

In Texas Hold'em, when facing a raise and it's your turn to act, you can either fold, call, or raise.

Most players tend to call far too often - it's a passive play and it's tempting for new players to call a bet simply to see another card.

Thinking players understand there are "fold or raise" situations.

These are scenarios where most players would call, but the far better play in the long run would be to either be aggressive and raise, or completely give up on the hand by folding.

In fold or raise situations, calling is common and most players' default, but it's by far the worst option.

The same concept applies to your trading business.

Is there something you're doing now by rote or as a default that would be better to either quit (fold) or go all-in on (raise)?

A good candidate is something you do that a lot of other traders do as well.

What would it look like if you stopped doing it or even did the opposite?

-Dave

Out of Sample Performance

2025-07-08T19:30:00-04:00

The last question from Chris B. (name used with permission), who’s using the Strategy Cruncher to create an intraday system that trades SPY.

Chris B:

Do you have an objective way to measure a filter’s effectiveness in the out of sample period? My observation when comparing the -0.3308 (dojiness) against the baseline results, the improvements in MAR, Expectancy, AvgLoss, and ProfitFactor are basically the same for in and out of sample backtests. That would give me confidence in the filter.

Dave

You're right, Chris. It's a great sign that the threshold the cruncher suggested is the same for your in sample and out of sample trade sets.

That should be a big confidence boost that the optimal filter it found should hold up into the future.

If your strategy's signal is strong enough and you have enough trades, it won't matter if you do in sample and out of sample testing.

Why? Because the cruncher will give you the same suggestions whether you have it look at the in sample set or the entire backtest.

If the Strategy Cruncher had suggested wildly different values for the optimal filter for Dojiness for in sample and out of sample sets, what would that say about your confidence in the filter?

You should always be thinking about your "path to confidence" with a strategy.

Trading is easy if you're trading with small size.

It gets more interesting and difficult when your goal with each strategy is to trade it with significant size.

What questions would you need to answer about your strategy to trade it with more size?

What's stopping you from getting those answers?

-Dave

P.S. When you're ready, the cruncher is here. The Strategy Cruncher is like having a cheat code for your trading strategy. Here’s what Matt H. said about the cruncher:

“The cruncher suggested a few filters for my strategy. I plugged them in, ran the back test and WOW! 20% improvement in total profit, and with another, a significant reduction in drawdown. I recommend this for anyone truly serious about optimizing their strategy.”

Try the Cruncher

The Backtest Looks Great - What Could Possibly Go Wrong?

2025-07-07T19:30:00-04:00

In this week's episode of Line Your Own Pockets, we discuss all the pitfalls that can happen when you go from a backtest that looks awesome to trading it live.

Topics include:

Missing the big winners
Slippage on entry
Slippage on exit
Buying power issues
Why you're especially susceptible to disappointment
Much more...

The more you understand the causes of the backtest/live trading shortfall, the better strategy you can create.

And your expectations get more well-calibrated.

LISTEN NOW »

-Dave

Constrain Yourself

2025-07-04T19:30:00-04:00

"The right constraints can lead to your very best work." - Austin Kleon

That's a quote I love from Austin Kleon in his book Steal Like an Artist.

Artists and traders have much in common.

Uniqueness and success are highly correlated in both fields.

Great traders and artists don't emerge from the womb with an innate ability.

They have a dedication to their process that creates uniqueness.

If you find yourself bouncing from strategy to strategy because they don't seem to work, you're very likely spreading yourself too thin.

Figure out how to go "an inch wide, but a mile deep," as John Arnold claimed was a huge part of his success. (He's generally known as the best energy trader of all time.)

It almost doesn't matter the strategy you pick, but when you constrain yourself to a small area, you'll almost guarantee you'll end up with something unique the deeper you dig.

Here's the podcast with John Arnold where he discussed the constraints he went out of his way to apply.

What constraints can you apply to yourself to lead to your best trading?

-Dave

How Often Do You Re-Optimize?

2025-07-03T19:30:00-04:00

Here's another question from Strategy Cruncher user Chris B. (name used with permission).

Chris B.

How often do you re-optimize a strategy?

Dave:

First, a confession. Like any good programmer, I'm lazy.

Hopefully in the best sense of the word.

What I mean by that is I try to do a little more work in the present to save work for myself in the future.

That's especially true for backtesting and optimizing trading strategies.

Optimizing a strategy is hard! You have to spend a lot of mental energy making decisions about the strategy.

The entire reason the Strategy Cruncher exists is to make optimizing strategies easier.

But the better you get at it, the more you separate yourself from other traders.

How often should you re-optimize a strategy? As little as possible!

But that means you have to work harder when you optimize to make sure the strategy won't require rework later.

With every decision you make about your strategy, you should have long-term robustness in mind. That is, when deciding between two rules to apply to your strategy, pick the one that's most likely to have staying power.

It's easier said than done, but over time, you'll get better and better at creating robust strategies in the first place, so you DON'T have to re-optimize.

Thanks for the question, Chris B.! (Look for another question from Chris tomorrow.)

-Dave

P.S. Enjoy the holiday weekend!

Optimize on Entire Backtest?

2025-07-02T19:30:00-04:00

The next question from Chris B. (name used with permission), who's using the Strategy Cruncher to create an intraday system that trades SPY (details here).

Chris B.

Do you include the entire history of a backtest or a more recent subset?

Dave

Backtesting is a confidence builder.

You're building confidence in your idea for the trader you are now, which is really valuable, but it's not the most valuable part.

Your backtest and the decisions you make about rules for your strategy are really for your future self, when the strategy is in a drawdown and you're wondering whether to give it up or not.

Every trader who ever quit did so during a drawdown.

And they quit because they didn't have confidence in their system to keep trading through the drawdown.

The backtesting decisions you make now will help you have confidence during that drawdown.

When you're in a drawdown, do you think you'll say to yourself, "Man, I wish I would have backtested on a smaller set of trades."

Of course not!

You'll want to have as much perspective as you can have.

So I start with the entire history that I can feel confident in.

For a strategy like Chris' that trades a single instrument, you're going to have to go back a long time to get the number of trades required for confidence.

For a strategy that trades many instruments (or the entire market), you don't have to go back too far to create a backtest with a lot of trades.

So my default approach is to gather as much data as possible.

You can always trim down or exclude a period (like we discussed yesterday).

Great question, Chris B. - thanks for sharing.

-Dave

P.S. The Strategy Cruncher is like having a cheat code for your trading strategy. Here's what Matt H. said about the cruncher:

"The cruncher suggested a few filters for my strategy. I plugged them in, ran the back test and WOW! 20% improvement in total profit, and with another, a significant reduction in drawdown. I recommend this for anyone truly serious about optimizing their strategy."

Try the Cruncher

Strategy Cruncher Questions

2025-07-01T19:30:00-04:00

For the next few days, I'll be answering an excellent set of questions from a Strategy Cruncher user named Chris B., who agreed to share these with the list.

Here's the first question:

Chris B.

I've been playing with the Strategy Cruncher with an intraday system I'm running that I've backtested using RealTest.

The system trades SPY intraday, long and short.
I have data from 2001 through the present.
In-sample is 6/2002 through 12/2014.
Out-of-sample is 1/2015 through today.
I separated long and short trades into two CSVs.

I ran the in-sample set of the short side of the strategy through the cruncher with the aggression factor set at 33 with 1456 trades and this was the best chart.

I noticed all the charts had accelerating equity curves during 2008 so I asked myself how might SC suggest values without that year of trades. I ran the short trades through SC again without 2008, which produced this chart:

Both filter values for Dojiness clearly improve the system in terms of CAR and MDD with about 40% fewer trades.

Does eliminating that period of trades make sense, or is that just overfitting?

Dave:

This is a great question, Chris. I would not consider this overfitting for a few reasons.

It would be one thing if the period you remove from the backtest is worse than the overall backtest, but this period improves the strategy. That difference is significant - if the period made the strategy worse overall and you removed it for testing purposes, then I would say that IS more likely to be curve-fitting.

I also consider the period itself. Is it a significant event that you can identify in a way that makes sense? Yes, this is the 2008 financial crisis.

How likely is this type of event to recur in the future? Sure, you can imagine a scenario where it might occur again, but it's not very likely!

This strategy should be optimized for the "normal" periods, which are the vast majority of the time covered by Chris' backtest.

The equity curve for the rule the cruncher found looks much smoother by looking at just the "normal" periods.

I don't create strategies that wait around for these black swan-type events that very likely will never come about again. And if it does recur, there's certainly no guarantee they'll behave the same way.

I think this is a great example of what I discussed in the Curve Fitting series a few weeks ago. Traders get stuck with this type of decision for fear of the curve-fitting boogeyman.

Does this mean you can exclude whatever periods you want to make your strategy look better? Of course not.

But I think it's totally legitimate to remove this period in exactly the way Chris did.

I'll tackle another one of his questions tomorrow. Thanks, Chris!

-Dave

P.S. Would you like to improve your strategy by finding ways to make the same or more profit with way fewer trades without curve-fitting? Lots of serious traders are using the Strategy Cruncher to create their own trading strategies. If you have a backtest, you should be crunching.

Try the Strategy Cruncher

When Is Your Strategy Good Enough To Trade?

2025-06-30T19:30:00-04:00

If you have perfectionist tendencies, it's easy to get stuck in "backtest world", thinking your strategy could just be a little bit better before trading it live.

In this week's episode of Line Your Own Pockets, we discuss when your strategy is good enough to take the next step.

Topics include:

Backtest equity curves as drawdown detectors
The better your process for logging trades, the quicker you can go live with a strategy
Going live is the beginning, not the end, of your learning
You know what a post-mortem is, but what's a pre-mortem, and how can it help?
and much more

LISTEN NOW »

-Dave

P.S. As recognition of our 50th episode (!!) of Line Your Own Pockets, we'd love to hear questions from YOU to answer on the podcast.

Do you have a trading question that would make a good topic? Hit reply and let me know.

Another Column for your Backtest

2025-06-27T19:30:00-04:00

An astute reader caught my mistake in yesterday's email on dojiness, where I said I would be sharing two column ideas, but only mentioned one. (Good catch! See - I never use AI for these messages. Note the text in the footer below.)

The second column I like to use as a pair with Dojiness is Close Position.

If you aren't familiar with the dojiness concept, go back and read yesterday's email.

When you think about it, you'll notice that dojiness describes just part of the full picture of a candle.

A candle could be a perfect doji, but it could open and close anywhere in its range.

That's where the Close Position comes in.

The formula is similar to Dojiness:

Close Position = (Close - Low) / (High - Low)

The value ranges from 0 to 1, where 0 means the candle closed exactly at the low and 1 means it closed exactly at the high.

I use this column in all sorts of situations, especially the ones I listed yesterday for Dojiness:

Applied to yesterday’s daily candle in an intraday strategy
Applied to the most recent candle before your trading signal
Applied to today’s opening range candle
Applied to recent daily action

The other situation where I'll often use this is the position of the entry price of a trade in today's range.

Some of you might be thinking:

"Candlestick patterns? Those are complete gobbledygook. There's no edge when a candle makes a doji."

And you're right - that alone won't make a strategy, but it also completely misses the point.

A Column for your Backtest

2025-06-26T19:30:00-04:00

Here are two columns from my column library that most traders aren't capturing in their backtests.

I created these many years ago, and they've been in every backtest I've run since.

The first is what I call dojiness.

You probably know what a doji candle is.

If you look up the definition of a doji you'll find a lot of disagreement about what is or isn't a match - which is pointless.

Anytime you try to reduce some factor to a binary yes/no, that should be a red flag.

This is why I created the dojiness concept. It describes the degree to which a candle is a doji.

Here's the definition:

dojiness = (Close - Open) / (High - Low)

The range of values varies from -1 to 1, with zero being a "perfect" doji (where the open price equals the close price).

A value of 1 means the candle has no wicks and is perfectly green.

A value of -1 means the candle has no wicks and is perfectly red.

When applied thoughtfully, this column often appears as important when I run the Strategy Cruncher on my backtests.

In fact, in one of my strategies, the value of this tells me whether I should go long or short (pretty dang predictive!)

Here are situations where it might be useful in your strategy:

Applied to yesterday's daily candle in an intraday strategy
Applied to the most recent candle before your trading signal
Applied to today's opening range candle
Applied to recent daily action

Like any indicator, it's not a silver bullet, but with some creativity, you can apply it to a strategy in a way that's predictive.

-Dave

P.S. Question: Are you an Amibroker user? I'm looking for some volunteers to beta test something I'm working on. Hit reply and let me know if you're interested.

DAS Trade Exports

2025-06-25T19:30:00-04:00

I know several of you trade through DAS Trader, so I wanted to make you aware of a new feature I requested that the good folks at DAS have implemented.

There's now a setting that can be used to automatically export your executions to a CSV file regularly.

IB's TWS has had this feature forever, which makes automated reporting much easier. I turned this feature on in 2016, so I have a record of every trade I've made for almost a decade, categorized by strategy (using the important Order Reference field).

You can now turn this on in DAS Trader as of version 5.8.1.3.

Here's the configuration screen, which you can get to by going to Setup, Other Configuration, then scrolling down to the bottom:

The executions get saved to the folder you specify in a file called Trades.csv. Currently, that file gets overwritten each day, so you'll need to copy it, unfortunately.

They will fix that in a release soon, so it will automatically write to a new file each day.

Good record keeping is essential to trading well (details matter!), so I'm happy DAS added this functionality.

-Dave

The Current Bottleneck

2025-06-24T19:30:00-04:00

Today, I just have a quick question for you.

Look back at your trading results from last year and find your total net profit for the year.

Assuming it's positive, take that number and add a zero to it. (Multiply by 10)

What's stopping that new number from being your total net profit this year?

You might be thinking "more buying power," but in my experience, that's never the current bottleneck.

Hit reply and let me know - thanks in advance!

-Dave

The Key to Backtesting: Your Library of Columns

2025-06-23T19:30:00-04:00

This week on Line Your Own Pockets, we discuss how to add columns to your backtest. This is the second episode in a series on creating profitable strategies using backtesting.

We review:

How most traders backtest the wrong way
How to add columns to your backtest
What columns make the most sense
How your "library of columns" gets more and more valuable over time

LISTEN NOW »

-Dave

How To Add Predictive Columns

2025-06-20T19:30:00-04:00

A trader asked me recently how he could set up his backtest to improve his strategy.

He had added some columns, and while some were modestly predictive, none were as predictive as the Yesterday's Change from Open % example from one of my strategies that I posted recently.

Here was my suggestion to him:

The thing to focus on is adding features (stat-speak for "columns") that are highly likely to have predictive value on your original signal in the strategy.

Think about your signal and make sure you've got everything about it covered in a column in the backtest.

For example, let's say your strategy enters long on a gap down today. I'd make sure I had the following data points in the backtest as columns:

the gap in terms of ATR
yesterday's gap in terms of ATR
yesterday's change
yesterday's close in its range
yesterday's volume compared to normal
today's open as a position in yesterday's range
pre market range
today's open as a position in today's pre market range
etc…

Note that the further away a column is from describing your signal, the less predictive it will be. In our example, the gap from two days ago might be only very slightly predictive, so the improvements you get from it would likely be minor.

Feature selection is hard!

It's worth thinking deeply about, though, because good, predictive columns pay off quickly in improvements to your strategy.

But more importantly, they provide aha moments that you can use to improve every strategy you create in the future as well.

-Dave

Avoid Windows Entirely?

2025-06-19T19:30:00-04:00

Fellow trader Randall T. replied to my original post on avoiding Windows Updates. Not only does he avoid the updates, but he also avoids Windows entirely.

Here's Randall's response with a link to his tutorial on giving Linux a spin as a desktop computer (as opposed to simply a headless server, which I'm already a huge fan of). (Name and response posted with permission.)

Randall T.

I hope all is well. I've been running Linux as my sole OS since 2010 and miss Windows like the common cold. When I am not running native Linux applications (e.g., TradingView, Thinkorswim, Trader Workstation), I run my Windows applications such as Excel in Crossover which spoofs the Windows environment so that they run natively. In the rare case that I need a true Windows environment, I run Windows as just another application within VirtualBox.

This way, I retain control of my computer at all times. I started 15 years ago with Ubuntu (which is on the Debian evolutionary branch) and have moved to Linux Mint, which is also on the same branch.

I strongly recommend giving it a look!

Here's a link to Randall's tutorial on using Linux Mint as a desktop.

This is a step too far for me due to the custom applications I run for my trading business, but I'm sure other readers will find this interesting.

Thanks for sending this, Randall!

QUESTION: Do any other traders out there use non-Windows environments? I'd love to hear more about your setup. If there's enough response, I'll summarize it in a message to the list.

-Dave

Combine Long and Short Strategies to Optimize?

2025-06-18T19:30:00-04:00

A new Strategy Cruncher user, Dave P, asked this excellent question about whether to combine long and short versions of a strategy for optimizing or to keep them separate (posting with permission):

Dave P:

Thinking ahead to other mean reversion strategies that I am running, I wanted to get your input on how to approach Strategy Cruncher for long/short strategies. Do you recommend running both sets of trades (long & short) through Strategy Cruncher at the same time? Or, do you recommend splitting into separate trade lists (long only, short only) prior to running through the Cruncher?

First off, I love how Dave has taken one idea and created two strategies from it.

It's not always the case, but when you find edge in one direction (long), you can often find edge in the opposite direction as well.

It is usually not a simple flip of the strategy - usually, there are some tweaks to be done in either direction.

For that reason, my default approach is to treat them separately - as two distinct strategies.

I'll run each of them through the Cruncher separately to optimize them.

There is a situation where I'll combine them, though.

If there's a situation where the strategy is already low on trades - that is, the sample of trades is low enough that I feel like I can't get much confidence in the data.

I have had situations where that's the case, and I'll combine long and short into the same set in order to create a larger set of trades that I feel better about drawing conclusions from.

Combining them works best in strategies where both directions are more equivalent.

I'll also add columns that work in both directions.

For example, instead of just a column for Gap Percent, I'll add a column for the absolute value of Gap Percent.

Optimizing on Gap Percent across long and short strategies doesn't make sense, but the absolute value of Gap Percent is absolutely valid and likely to be identified as predictive.

See this post from several weeks ago where I show a more detailed example:

How To Make Your Strategy More Predictive

Great question, Dave P., and thanks for sharing it with the list!

-Dave

A Clever Way to Avoid Windows Updates

2025-06-17T19:30:00-04:00

A few days ago, I posted a method to push off the Windows Updates for up to several days that a reader suggested. Another reader, Ishmeet S., responded with a method he uses to push the updates out for... 25 years (!!) (name used with permission).

For normal Windows users, these unscheduled Windows Updates are a minor annoyance. For traders using software to enter trades, these updates are very costly!

When you're trading with a strong edge, it pays to avoid anything that prevents you from executing your trades.

Ishmeet does something clever to push the updates further than Windows deems appropriate with these steps:

Sets his system clock to a date way in the future (the year 2050 or beyond)
Pushes the Windows Updates to the furthest date possible
Sets his system clock back to the current date

I've verified this works - see this screenshot:

The only issue with this is that if you restart your machine, the setting is forgotten, and you have to do it again.

That didn't deter Ishmeet, though!

He created a script that automatically performs the steps above and used Windows Scheduled Tasks to execute it upon startup.

He graciously offered to share the script with other readers. It modifies the Windows registry, so I'm not linking to the script directly here, but if you're interested, hit reply and I'll send it to you.

Thanks for sharing this clever solution, Ishmeet!

-Dave

P.S. Are there any DAS users out there who use the Trade Signal feature to generate alerts? I'm working on something you might be interested in. If you're interested in beta testing it, hit reply and let me know how you're using the Trade Signal feature.

You're Probably Backtesting Wrong

2025-06-16T19:30:00-04:00

In this week's episode of Line Your Own Pockets, we're starting a series on creating your own profitable trading strategy using backtesting.

We review how most traders start backtesting in the most inefficient way possible.

Topics include:

The mistake almost all traders make when they start backtesting
Why the "guess and check" approach is like shooting in the dark
How to take your backtesting from slingshot to sniper rifle
What your very first backtest of a strategy should accomplish (you shouldn't be shooting for your final version right away!)

If you've ever backtested or are looking to get started, this series of episodes is for you.

LISTEN NOW »

-Dave

P.S. HOLIDAY REMINDER: This Thursday (6/19) is the Juneteenth holiday, and the US markets are closed, only to reopen the next day for Options Expiration. It's an odd week, so plan something fun for Thursday (Joan and I are having lunch with some good friends), but don't assume Friday will be a snoozer since it's between a summer holiday and the weekend.

How To Trade Through a Drawdown

2025-06-13T19:30:00-04:00

Is there anything more painful in trading than a drawdown?

I often tell people that trading is like working on a 200% commission.

You've put a lot of work into your strategy, and then not only could you not have anything to show for it, but you could be worse off than when you started!

There's no question about it - drawdowns suck.

But to succeed in the long run, you have to find a way to deal with them.

And that starts well before you pull the trigger on your first order to trade a strategy.

Every decision you make about what filters to apply to your strategy, what position sizing algorithm to use, and how frequently the trades occur - everything - affects the types of drawdowns you'll see.

Drawdowns are when traders quit; so it should be at the forefront of your mind in every step of creating your strategy.

It's not IF a drawdown will happen in your strategy, it's WHEN.

If you're surprised by a drawdown when trading live, then you haven't thought deeply enough when you created your strategy to begin with.

In my first really great trading years - the best years I'd had at the time - there was a streak where I lost 14 trades in a row over the course of a week.

14 losing trades in a row at the biggest size I'd traded up until that point.

It was terrible, but I was confident (though not 100% sure!) that the sky wasn't falling and my strategy still had an edge when I zoomed out.

That's why you have to look at the equity curve when making decisions about your strategy.

Boiling it down to the fanciest metric won't work.

-Dave

P.S. If you've ever run a backtest, you'll love the Strategy Cruncher. It's the tool I've used to gain confidence in my strategies to trade through drawdowns. If you're still fiddling with Excel to improve your strategy, do yourself a favor and check it out.

This is the last chance for the early-bird discount for the Strategy Cruncher! Use promo code EARLYCRUNCHER to get 50% off the subscription forever.

The price doubles this coming Sunday at 11:59pm ET.

Learn About the Strategy Cruncher

The Story an Equity Curve Tells

2025-06-12T19:30:00-04:00

The most important metric you should use to evaluate your strategies isn't a metric at all.

It's a picture.

The equity curve conveys so much more information than a single number.

It shows you where you'll be overconfident and where you'll feel like quitting.

Every trader who ever quit trading did so during a drawdown.

Why? Because they didn't have enough confidence in their system to trade through it.

The equity curve is the first thing I look at when evaluating a strategy.

Because it's showing you all the points in time when doubt will creep in, and you'll feel like reducing your position size.

The hardest part of trading is trading through drawdowns.

Evaluating a strategy using a single metric (or even a few metrics) hides all the important details.

The equity curve tells you a story - you should listen to it!

Announcement: This coming Monday I'll be doing a free webinar with Interactive Brokers called Creating a Trading Strategy That Can Work which will show you how to create your own profitable trading strategies.

It's the proven process I've used for 20 years to create my strategies.

The webinar is on Monday, 6/16/2025 at 2pm ET. Even if you can’t attend live, go ahead and register so you can be notified of the recording and watch it afterward at your leisure.

This is not a sales call masquerading as a webinar – this is practical advice to apply to your own trading.

I hope to see you there.

-Dave

Simple Strategy Metrics

2025-06-11T19:30:00-04:00

In my post yesterday on deciding when a strategy is good enough, you may have noticed how imprecise the language was:

Is the win rate "in the range"?
Is the profit factor "reasonable"?
Is the number of trades per day "sufficient"?
Is the equity curve "smooth enough"?

In other contexts, I might refer to these ambiguous phrases as weasel words.

Those who know me well might find this surprising - I routinely offer bets to people who use weasel words.

So why would I purposefully have such vague rules about evaluating trading strategies?

Two reasons:

First, if you have precise, black and white rules about trading strategies, you ignore the trade-offs that come from relying too much on a particular metric.

Do you want a higher profit factor? That almost always comes with a reduction in the number of trades in a strategy.

Second, it's very easy to overlook a great strategy because it doesn't fit one of your rigid rules.

Yesterday, I spoke to a trader who shared that he only considered strategies with a profit factor above 3.

That's all well and good, but doing so ignores the boatload of profitable strategies with profit factors below 3.

What would a strategy just outside your range need to look like for you to trade it?

Next time, I'll go over the most important "metric" of them all: the equity curve.

-Dave

When Is a Strategy Good Enough?

2025-06-10T19:30:00-04:00

You're creating a trading strategy.

You've made some tough decisions about filtering using your column library.

It looks a lot better than when you started.

But is it good enough?

Should you continue optimizing or is it time to send it?

Most traders try to boil this down to a single metric, but doing that comes with too many tradeoffs.

It's more art than science, but here are the things I look at:

Is the win rate in the range? (Lower win rate strategies are more difficult to trade, so I take this into account.)

Is the profit factor reasonable?

Is the number of trades per day sufficient to keep me interested?

Is the equity curve smooth enough?

Below is an example of one where I'd try one more optimization step to try to improve it:

You might notice a lot of popular portfolio metrics that aren't in the list above.

Sharpe, Sortino, blah blah blah the list goes on.

I'll share tomorrow why I keep this list so simple.

-Dave

P.S. Time is running out for the early-bird discount for the Strategy Cruncher. Discount code EARLYCRUNCHER will get you almost 50% off the price forever. You'll never see that price again after 6/15, so act now before it expires:

Start Using The Strategy Cruncher

"I've used Strategy Cruncher to increase size on trades where there's a stronger edge. In one specific short strategy, I found that the edge increases linearly with a specific parameter. So I decided to scale up the size gradually as that parameter increases. The improvement in the backtest is significant, and now I just need to verify in live trading to verify the edge holds up, but I'm very confident."

-Fabrizio

How Real Traders Use AI to Trade

2025-06-09T19:30:00-04:00

In this week's episode of Line Your Own Pockets, we discuss ChatGPT and how traders can use it in their workflow.

I explain how I used it recently to help build the Strategy Cruncher (and how much time it saved me!)

We discuss:

How LLMs can help you learn something new
What they are NOT good at
How big a deal are the hallucinations?
Using ChatGPT to improve your trading business

And much more.

LISTEN NOW »

-Dave

Optimizing Your Strategy

2025-06-06T19:30:00-04:00

Yesterday, I went over the details of how you can use columns in your backtest to improve your strategy and showed a specific example from a strategy I've traded for years.

Today, I wanted to share some thoughts about my approach to optimizing my strategies.

Remember, you shouldn't be shooting for your final version of the strategy with your first backtest.

Think of the first backtest as setting the stage for designing your final version.

As you begin optimizing your strategy from that first backtest, you'll find large sets of unprofitable trades to eliminate using rules.

As you get closer to a version you'll consider trading live, you should be looking for smaller and smaller subsets of poor trades to remove.

As a general rule of thumb, as the strategy gets more mature and is working in live trading, you'll want to be stingier about adding rules since there's a tradeoff with removing total profit.

Here's the thing.

You could keep optimizing down to a single trade in your backtest that you're really confident (but not positive) would be profitable.

But that's not very valuable - imagine waiting a year for a single trade to come along - you better be ready!

So how do you know when a strategy is "ready"?

That will be the focus of this series next week.

-Dave

P.S. Matt H. signed up for the Strategy Cruncher and sent this feedback to share:

"I ran the Strategy Cruncher on my strategy and it suggested a few filters. I plugged them in, ran the back test and WOW! A 20% improvement in total profit, and with another, a significant reduction in drawdown. I recommend this for anyone truly serious about optimizing their strategy."

The early bird discount code to get 50% off the Strategy Cruncher is EARLYCRUNCHER and expires 6/15, so act quickly before it’s too late.

The Best Columns Are...

2025-06-05T19:30:00-04:00

A few of you responded to my last post about some of my favorite columns for creating strategies with the correct answer.

The best columns are normalized. This is not the first time you've heard me use this term.

Why is it so important?

It's only important if you want to create a strategy that's actually profitable. :-)

Normalized columns allow you to maximize the number of profitable trades in your trading system.

Here's a real life example from a long strategy I've traded for almost 20 years now.

I followed the exact process I've outlined in recent posts:

The first backtest has very little filtering
I add my column library to the backtest

When I put the backtest through the Strategy Cruncher, here's what it identies as highly predictive:

From all the dozens of columns in my backtest, it tells me that Yesterday's Change from the Open % needs to be small:

(I've obscured the exact value it tells me is optimal to use.)

When I apply this one simple rule to the strategy, it reduces the number of trades, but the trades that remain are 20X more profitable.

Compare that to another column that a lot of traders try to make a rule from: Price.

When I run the Strategy Cruncher and tell it to look at Price, it gives me this:

It's identified the optimal rule for Price, but there's hardly any improvement in the strategy by applying it.

Notice where the lines end up. The average profit per trade are essentially the same.

I could apply the rule based on Price and technically I'd improve the strategy slightly, but I would be removing a LOT of profit from the system for very little gain.

This is why it's important to add normalized columns to your backtest.

It gives you a path to quickly increase the profitability of your strategy while removing as few trades as possible.

-Dave

P.S. Interested in reducing your drawdowns? Here's how Isaac used the Strategy Cruncher to do exactly that:

"I started using Strategy Cruncher and it gave me some suggestions for improving my system that I hadn't considered. It reduced my trade count without sacrificing system profitability and actually reduced drawdowns. The lower trade count means less fees and less required buying power as well. I ran the optimized version in a live account, side by side with my current strategy, and the improvements are very real."

Filter Ideas

2025-06-04T19:30:00-04:00

Last time, I shared a way to logically classify filters.

When creating intraday trading strategies, you should prefer* filters/data points that don't change during the day.

It simplifies the problem - a LOT.

Here are some columns from my library that should be useful (RealTest users see P.S. below).

Today's Gap (in percent or, better yet, in terms of ATR)

Anything related to yesterday's action:

Yesterday's range in terms of ATR

Yesterday's volume compared to normal

Yesterday's change in terms of ATR

Yesterday's close position within its range

Aside from these data points being "set" (don't change), do you notice anything else similar about these?

Reply and let me know.

* Notice I said "prefer" and not "exclusively use"

-Dave

P.S. Are you a RealTest user? If so, you'll want to check out the Strategy Cruncher. All Strategy Cruncher users get access to my RealTest column library to use in their strategies. Early-bird discount available until 6/14. Reply if you want the code.

Two Types of Filters

2025-06-03T19:30:00-04:00

Several years ago, my daughters gave me a t-shirt for Christmas that they knew I'd like.

And it always comes to mind when I think about this concept.

The shirt said: "There are 10 types of people in the world, those who understand binary and those who don't."

(I wore that shirt until it was threadbare.)

Think about all the filters/columns you could consider using in a trading strategy.

There are perhaps hundreds that you could use.

It can be completely overwhelming - where do you even start?

I've found that the most useful way to think about filters is to classify them in one of two buckets.

Filters where the values change during the day
Filters where the values don't change during the day

Why is that important?

Go back to the backtesting puzzle I shared a few days ago.

If you use filters that don't change during the day, you avoid the conundrum outlined in that post.

You simplify the problem of creating a profitable trading strategy dramatically.

It's not always possible to exclusively use filters that stay constant during the day, but I always start with those because it reduces complexity.

Tomorrow I'll share some specific examples of my favorite filters.

-Dave

What Metric Should You Optimize On?

2025-06-02T19:30:00-04:00

In this week’s episode of Line Your Own Pockets, we discuss a common question from systems traders:

What metric should you be optimizing on?

I go over the 4-5 metrics I use and why trying to boil it down to a single metric is a form of "holy grail" searching.

I explain the definition of the equity curve quality metric I use to evaluate equity curves.

We discuss:

Profit Factor
Win Rate
Expectancy
Sortino
Sharpe Ratio

I completely ignore the last two metrics, and I explain why.

LISTEN NOW »

-Dave

Another Way to Deal with Windows Updates

2025-05-30T19:30:00-04:00

Several readers responded to my post on dealing with Windows Updates. One of my clients said his Windows machine rebooted even after installing the program that supposedly disables it.

Fellow reader "Another Brian" wrote in with his clever workflow for dealing with Windows Updates. (Posting with permission.)

Another Brian:

I set my updates to happen on the furthest out Saturday it offers, in the advanced settings.
I always leave my computer on, too.

Dave:

Interesting, Brian. Are you referring to this setting? And do you reset this every time an update comes through? (see image below)

Another Brian:

Yes, that’s it. I set the pause date to the furthest Saturday, and whenever I remember on a weekend, I’ll run the updates. Once that’s done, I reset it back to the furthest Saturday again. That way, if I happen to forget to update, the machine still will reboot over the weekend under that plan.

Better Volatility Metric?

2025-05-29T19:30:00-04:00

Matt H. responded to the post on predictive columns and asked about ATR. (Posting with permission)

Matt H.

Is there a NEXT level of standardization of a column of ATR vs. security's typical ATR? Or is that a step too far vs. computing power?

If you allow yourself, you can conjure up a fancy, complex metric to describe anything.

But the K.I.S.S. principle is best here.

Simpler is typically better.

The volatility of a stock is probably the most important aspect to capture in your backtest.

It provides the basis for several other important columns in my column library, which I add to every backtest I run.

I've used two different metrics over the years for "how much a stock typically moves."

I mostly use ATR now because it's so easily and widely available across most trading platforms.

Another one worth considering is the Trade-Ideas Volatility metric, which is the average height of a 15-minute bar over the last several trading days.

If you think about it, this is highly correlated with ATR, but not perfectly.

It doesn't matter so much which one you choose, but pick one, keep it simple, and be consistent.

Thanks for the question, Matt!

-Dave

P.S. If you use Amibroker for backtesting and are interested in the code I use to simulate the Trade-Ideas Volatility, hit reply and let me know.

Backtesting Puzzle Explanation

2025-05-28T19:30:00-04:00

Here's a detailed explanation of what I've referred to as the "peek-a-boo trade" problem in backtesting. (See the More Trades Than You Expected and the responses posts for more background.)

You're backtesting for new highs, and there are 900 trades in your backtest.

When you analyze the trades list, you notice that filtering out lower values for volume today improves the resulting trade set and removes 300 trades.

So you add a filter in your backtest that excludes new highs with volume today < X.

When you run a new backtest, you expect to find 600 trades, but you find over 700 trades.

Many traders see this, throw their hands up in the air, and assume the backtest software is somehow broken.

But the backtest is working fine - here's what's actually going on.

Take SBET yesterday. It was running up all morning. Because your strategy looks for new highs, your original backtest found the first one at 10:30am. (See chart below)

If you apply a minimum volume today filter at 8.2M, the first instance at 10:30am is excluded, but the next one at 10:45am matches your rule set since volume today has increased by then to 9.7M (9.7 > 8.2).

You'll still have a trade in SBET in your backtest, but the entry time will be later in the day.

You thought you were excluding the SBET trade, but you were simply postponing it in your backtest.

Add these all up in your backtest, and you'll often end up with several more trades than you expected.

Over the coming days, I'll share specific ways you can address this issue in your own backtests.

-Dave

Responses to More Trades Than You Expected

2025-05-27T19:30:00-04:00

There were a couple of excellent responses to the backtesting puzzle I posted the other day. (Go back and read it first.)

First, Ken H. responded (used with permission) with an explanation that I wasn't thinking of but is still perfectly valid:

Ken H.

More trades appeared due to freeing up capital by eliminating existing trades that tie up capital for too long. This means the system is generating multiple signals, and it's important to add ranking criteria to execute on high-quality entry setups/signals. Also, it's important to evaluate exit criteria and/or holding time for trades that stop performing.

Dave

Nice response, Ken! That isn't what I had in mind, but that scenario could absolutely cause the situation I described.

Ken H.

Nice challenge, let me try again.

Let's say the system looks for continuation patterns and buys on new highs and generates the 900 trades.

I'm studying volume and market profile now and I find that continuation patterns are more reliable with above average volume, so applying an above average volume filter narrows down the outcome to 600 trades. When re-running the backtest with an above average volume filter, it produces 750 trades.

The system could be generating those additional/new trades in various other bars because it considers those other bars as new highs due to filtering out bars with low volume ones. I don't know if there's a technical term for this phenomenon.

Matt H. responded first, saying it could be look-ahead bias. When I gave him a hint, he nailed it as well:

Matt H.

Well, entering a few bars after the excluded trade entry bar was skipped, but before the excluded trade finished its life cycle. For example, if you have a timestop of 15 bars, and don't enter on bar 1 because of the new filter is flagging false, but do on bar 4 or 5 because the filter becomes true. You could end up with more entries than you expected.

Congrats to Ken H. and Matt H. for getting the right answer.

I don't have a great name for this phenomenon, but I've used the term "peek-a-boo problem."

Suggestions welcome!

I'll show a real-life example that will demonstrate the issue clearly and then ways I deal with this issue in the coming days.

-Dave

How Far Back Should Your Backtest Look Good?

2025-05-26T19:30:00-04:00

In this week's episode of Line Your Own Pockets, we discuss a question from a trader I recently started coaching.

He had a backtest that looked great this year, but not so good before that.

His question was, basically, why should I care how the strategy performed before that?

This is a great question because it gets to the heart of why so many traders abandon strategies too early - or quit trading altogether.

We discuss:

The reason most traders give up on strategies
Trading through a drawdown
Why your "path to confidence" is so important for trading with size

And much more.

LISTEN NOW »

-Dave

How To Deal with Windows Updates

2025-05-23T19:30:00-04:00

Being forced to reboot your computer at an inopportune time is a pain.

Even worse is returning to your trading desk to a login screen because Windows "conveniently" updated itself while you were away.

Windows Updates have always been mildly annoying for everyone, but if you're auto-trading, these unplanned reboots can be expensive due to missed trades.

Traders using my trade automation software know how expensive they can be.

Long-time friend of the list Maoxian wrote about this and a solution he found to disable Windows Updates that actually works.

You should update Windows, so I'm not advocating disabling the updates and never doing it manually.

But this solution would allow you to do it on your schedule, not Microsoft's.

-Dave

More Trades Than You Expected

2025-05-22T19:30:00-04:00

You're backtesting an intraday trading strategy that trades new highs.

You find a column/filter that improves the results.

It eliminates about 1/3 of the trades - say, 300 of the original 900 in the trade set - but the average profit goes up... a lot.

So you apply the filter and re-run the backtest, expecting to see a trade set with 600 trades (900 - 300, of course.)

But to your surprise, you find there are over 700 trades in the results.

When you look closer, you see some trades you thought would be removed, but they weren't.

What's going on? Is the backtest broken?

Have you experienced this common problem?

Any guesses about what's going on here? Hit reply and let me know.

-Dave

Predictive Columns

2025-05-21T19:30:00-04:00

You're trying to improve your trading strategy.

You've added columns to your backtest.

You ran an optimization report in the Strategy Cruncher.

And it finds two rules you can apply to your strategy to improve the results.

Here's a rule it finds for Column A.

Here's a rule it finds for Column B.

Either rule could be used to improve your strategy, but it should be obvious that one is superior.

It's no accident. Column A is a normalized data point, while Column B is not.

It's easy to see on the charts. Column A has a crisp and consistent correlation.

But Column B is... soggy.

The more you compare charts like this, the more ideas you get for improving your trading strategy.

And the better you'll get at capturing those ideas in your column library.

Over time, your equity curve gets smoother, which gives you a path to increase your position size.

-Dave

All Columns Aren't Equal

2025-05-20T19:30:00-04:00

You've created your library of columns for every backtest you run, but what columns should you include?

The good news is that the Strategy Cruncher (coming soon, get notified here) can examine all of them and show you which ones are most predictive for your strategy and show you the optimal way to make it more profitable.

Even though it can look across all your columns, you still want to focus on creating columns that have the best chance of being predictive.

Some columns in my library get identified by the Strategy Cruncher over and over as predictive across many strategies, while others never appear.

What are the qualities of the columns that repeatedly show up as predictive?

They're normalized. What does that mean? Here's an example to illustrate.

Take two stocks, META and DOCS. META is currently trading over $600 per share. DOCS is trading at just above $50.

One column you might want to add to your backtest is Change from the Previous Close.

Think about the value of that column across both META and DOCS.

For example, let's say the change from the close is $10 for both.

A $10 move in META is barely a drop in the bucket. But for DOCS, that same $10 move is significant.

Because the value for change from the close varies across different stocks, it's better to come up with a value that's more "normalized."

That is, a value that more equally describes the significance across stocks with different prices.

Your thought might be to use a percent for the move, and yes, that's better than dollars, but it still misses the mark since stocks' movements vary even in percentage terms.

A better data point to use is to normalize it by Average True Range (ATR). ATR describes the normal amount a stock moves.

Incorporating ATR allows you to add a column that gives you an apples-to-apples comparison across all stocks.

Something like this is the kind of column you want in your library:

Change from the Close / ATR

(And ATR itself should be a separate column as well.)

Tomorrow, I'll show an example that demonstrates why normalizing your columns is so important (but only if you want to maximize the amount of money you make from your strategy).

-Dave

P.S. Vacation Reminder: This coming Monday is Memorial Day, so the market is closed. This is your reminder to plan something fun so you don't come in Monday morning and wonder what's wrong with your trading platform. (I speak from experience, as you can probably tell!)

How To Prioritize Among Lots of Trading Ideas?

2025-05-19T19:30:00-04:00

You have a strategy that you know you can improve.

You have ideas for new strategies you think will have some edge, but you're not sure.

You also think learning Python will help improve your trading, but only indirectly, and will take a lot of time.

In short, you've got more things on your TODO list than you have time to do.

How do you figure out how to prioritize all these tasks?

That's the topic of this week's discussion on Line Your Own Pockets.

There's a useful technique from the software development world that helps with this, so make sure you listen to the end.

LISTEN NOW »

-Dave

Your Library of Columns

2025-05-16T19:30:00-04:00

Yesterday, I discussed how valuable it is to add multiple columns to your backtest. Now let's talk about making these columns permanently valuable to every backtest you run from this point forward.

In software development, there's a powerful concept called reusability.

An experienced developer once gave me some advice that stuck with me:

If you ever find yourself cutting and pasting code, you've done something wrong.

It was the perfect time in my career to hear that, because until then, I had done boatloads of cutting and pasting code.

With just a small mindset change, you can write code in a more generic way and include it in a library that can be shared across multiple projects.

This is incredibly powerful since you make every project from this point forward easier to create and maintain.

Need to fix a bug in the code? Change it in the library, and every project that references it is instantly fixed - assuming you haven't cut and pasted code.

The same, powerful concept applies to your backtests.

As you develop more theories and ideas about what data points have a strong effect on your strategy, you can add them to the backtest you're working on now.

But, similar to the "don't cut and paste code" rule, you can add them to a shared library so that every backtest you run from now to eternity benefits from it.

Have a new idea? Add a new column to your library, and you instantly get the ability to test it across all your strategies.

It doesn't take long for your shared column library to become your secret weapon - a process to improve every strategy idea you've ever had or will ever have in the future.

Next time, I'll go over specific column examples and what makes some far more valuable than others.

Stay tuned!

-Dave

Add Multiple Columns to your Backtest

2025-05-15T19:30:00-04:00

Yesterday, I shared how to develop and test a theory about improving your trading system.

We tested a theory about the distance from the 50-day moving average and found that you can significantly improve a system I trade using a simple rule based on it.

But what if our theory hadn't panned out?

Even when this happens, it often plants the seed for new ideas and theories to test.

Or what if, during the testing process, you came up with another theory that might improve your trading system?

Maybe you realize the 50-day moving average isn't that helpful, but something more recent might be.

You review some more charts and get curious about two more data points.

Some trades in your system have large gaps from the previous close, but others don't.

Some trades have big moves on the day before the trade, others don't.

So you add columns to test these new theories to your backtest.

And remember, you haven't changed the basic logic of your backtest, you've just added columns to your existing trade set.

Instead of a "guess and check" approach that leads to an endless loop, your backtest becomes a powerful tool to let you hone in on optimal answers to your questions.

And the only limit is your imagination and creativity.

Tomorrow, I'll show you how to turn this simple process into a way to make it easier and easier to generate profitable trading strategies from your ideas over time.

Instead of an endless loop of "guess and check" frustration, an upward spiral for your trading.

-Dave

P.S. If you're enjoying this series on backtesting, you're going to love the Strategy Cruncher. It's the tool I've used for years to create the 30+ trading strategies I trade every day.

Click here to be notified as soon as it's released:

What's the Best Filter for the 50 Day Moving Average?

2025-05-14T19:30:00-04:00

Following up on yesterday's post called Filters Are Everything, today we'll look at why adding a column to your backtest is so powerful.

Remember, your system is trading new highs. After observing a few trades, you notice that some are way above their 50-day moving average, while others are below.

You know that many traders pay attention to the 50-day moving average, so surely this data point has some effect on the system.

How can you tell for sure?

Here's what most traders try (and why they continue wasting time going in circles with their backtests).

They add a line of code like this:

And they run another backtest. It results in a subset of the original trades. But the rule they tried didn't remove as many trades as they assumed.

And it didn't improve the system at all.

Most of the new highs are already above the 50-day SMA, so a simple above/below rule won't have much effect.

So they try this:

And the wasteful "guess and check" backtesting loop begins as they try different values for the distance from the 50-day SMA over and over in a futile attempt to randomly stumble upon the "right answer."

Backtesting, when done properly, should be saving you time, not wasting it in this endless rabbit hole.

The much smarter way to answer the question about the 50-day SMA, is to add a column to your existing backtest - a data point for the distance to the 50-day SMA.

Then, figuring out the best filter to use for your strategy is not an endless "guess and check" loop - it's a quick verification of the right value to use.

The value that's optimal for your trading system.

And you can get the optimal value by running a single backtest, not dozens.

Here's the answer for one of the strategies I trade:

Optimal Value for Distance from 50-Day SMA

From just one backtest, I can see that the optimal value for this particular strategy is 35. (Note that this value will be different for your strategy.)

The green equity curve in the chart above represents all the trades where the value is above 35, and the red line contains those below.

Applying this single rule to my strategy gives me:

Higher total profit
Fewer trades (which means lower commission and less risk)
Higher win%
A better equity curve
Fewer and shallower drawdowns

Announcement: I'll be releasing a new tool soon that allows you to quickly and effectively make your trading strategy significantly more profitable. Click the button below to be notified when it's released and get early bird pricing.

Stay tuned!

-Dave

Filters Are Everything

2025-05-13T19:30:00-04:00

Last week, I wrote about two traders trading the same system with wildly different results.

If you're wondering if that was just a hypothetical thought experiment, it's not. This is the normal state of the trading world.

Take a look at your recent trading results.

Imagine if you could remove, say, 10% of the losing trades. What would that do to your equity curve?

It would make it dramatically better: tilted upward and smoother with much shallower drawdowns.

This is exactly why some traders have far better results than others while trading essentially the same trading systems.

The successful traders are skipping more poor trades and not skipping more profitable ones.

Once you do this, it becomes much easier to increase your size in your trading system.

How do the best traders skip the poor trades and take the profitable ones?

They've learned what filters are the most predictive to their strategy.

How do you do that?

By watching your trades play out in real-time each day, and brainstorming ways to improve your system.

Here's an example. Your system scans for new highs and looks to get long.

It does well, but you notice some trades that come through your system are above the 50-day moving average, but some are below. You wonder if that affects the overall profitability.

The wrong way to get the answer to this question is to do what most traders do: add a rule to your backtest to exclude trades that are below the 50-day moving average. Then they compare the overall results from the original backtest to the new one.

The smart way to do it is to add a column to your existing backtest - all trades remain the same, but your backtest output now has a new column that describes whether the trade is above or below the 50-day moving average.

Tomorrow I'll discuss why this approach is so powerful compared to the way most traders backtest.

-Dave

Why Not Automate Your Trades?

2025-05-12T19:30:00-04:00

In this week's episode of Line Your Own Pockets, we discuss traders' objections to automating their trades.

Topics include:

How to take the first step
Eliminate your human errors
The turning point for many traders is automating their trades
Precaution settings in Trader Workstation
The power of the default

And much more...

LISTEN NOW »

-Dave

A Tale of Two Traders

2025-05-09T19:30:00-04:00

Following up on my post from a few days ago on when to take the signal, and when to skip it.

Step back and think about two traders. They're both trading a strategy based on new highs.

Trader A is a consistent losing trader.

But Trader B is crushing it, making consistent profits month after month.

But they're watching the same signals and even trading in the same direction, so how can they get such dramatically different results?

There's only one reason Trader B is outperforming Trader A.

And it's not that complicated.

Trader B knows that all new high signals are not the same. Some have a high probability of succeeding, while others have an extremely low probability.

So Trader B knows which signals to skip and which ones to trade.

That's the only difference!

He's trading a more profitable subset of the original new high strategy - he's better at filtering than Trader A.

Was Trader B born with an amazing, innate skill to magically know which filters to use?

Of course not.

But he has a much better process for applying rules to narrow down the new high signals (or any type of signal) to the subset with the most profitability.

He's only watching the most profitable subset and ignoring all the others.

The next few emails in the series will focus on how you can get better at this skill.

Stay tuned!

-Dave

Which Backtester Is Right For You?

2025-05-08T19:30:00-04:00

The other day, I shared which backtesting software you should consider using. Which one is right for you?

It depends on:

Your skill set
Your strategy timeframe
The amount of history you require

Do You Have Programming Experience?

Although still important, programming experience used to be a big differentiator - the factor for determining which backtesting software to use.

With the advent of LLMs, it's not as critical, but still an important factor, and it will always give you an advantage over traders who can't program.

If you don't enjoy programming, then Trade-Ideas is your best choice.

Strategy Timeframe

Do any of your strategies require intraday data? If so, RealTest only works on daily data (currently), so Amibroker is the best choice.

Minimum Backtesting History Required?

Trade-Ideas has 3 months of backtesting history available - plenty for some strategies, but not enough for others. If you have to have more than 3 months of history, then cross Trade-Ideas off your list.

Let's go through the three choices and the pros and cons of each:

Trade-Ideas

Pros:

Simple to use, no programming required
The fastest backtesting software on the market (nothing even close)
Trivial to get real-time alerts when your strategy is finalized
Built-in indicators/custom columns in your backtest
No data to maintain - all data included

Cons:

3 month backtesting window
Nice breadth of indicators, but not infinitely customizable
US Equities only

Amibroker

Pros:

No limit on the amount of data for your backtesting window
Infinitely customizable using code
Can use intraday data
Any instrument type

Cons:

Programming required through own custom language (AFL)
Third-party data source required
Some local database maintenance is required
Time-consuming to scan the entire US equities market in real-time (use in tandem with Trade-Ideas to do this efficiently)
Have to create your own custom columns for your backtest

RealTest

Pros:

Fast, simple portfolio backtesting
Infinitely customizable using code
Any instrument type

Cons:

Daily data only (currently)
Third-party data source required
Some local database maintenance is required
Have to create your own custom columns for your backtest

Summary

All these software packages are excellent - I use each for specific tasks. The best choice for you is very trader-specific.

Tomorrow, we'll return to the nuts and bolts of creating a strategy (regardless of the software you use).

-Dave

Can Forward Testing Replace a Backtest?

2025-05-07T19:30:00-04:00

In response to yesterday's post on which backtesting software is worth considering, reader Kyle Kaefer from kpsoundcompany.com and Concordia University asked (sharing with permission):

Kyle:

I do not run backtests because I am just getting my first couple of bots up and running on paper, but… if you have a good understanding of your niche edges, could forward-testing in a paper account be just fine?

It seems like backtests more often than not fool us as traders.

Dave:

That's a great question. I think you can get by without it, but only if you have a really strong sense of your niche edge. And even then, even with the imperfections of backtesting, it can be really valuable to what you're doing with your bot and forward testing.

I think a lot about a trader's "path to confidence." It's easy to trade with small size, but what's in the way of you trading with your full size for a given strategy? It's likely that there are some unknowns about how the strategy will perform in the future.

Those unknowns will fade over time with just forward testing and experience, but imagine if you had a backtest to use as a guide. Your path to trading with full size could be very short since you can very quickly check each day how your trades are measuring up to the backtest.

From there, you can extrapolate and understand quickly what results you could have expected had you started trading the strategy months ago (even several years).

That can be extremely valuable because it provides a much quicker path to confidence.

Now, imagine a year from now, and this strategy is in a drawdown. Is this level of drawdown normal for the strategy? It's hard to answer that without a backtest.

Kyle:

I totally would and will eventually backrest, just not there yet, you make very valid points! I am probably overconfident, but I do think what I have is sound and will, at a minimum, break even… been in and out of markets for 10 years, so I have some experience.

Dave:

Well, there are two paths to confidence: trading experience and backtesting. The former is the most important one, but it takes time to cultivate it. Since you already have a healthy dose of it, backtesting will be that much more valuable when paired with your trading experience and intuition.

Thanks for the question, Kyle!

-Dave

Which Backtesters Are Worth Considering?

2025-05-06T19:30:00-04:00

The fundamental question you need to answer when backtesting was the topic from last time: when to take the signal and when to skip it.

Today, we'll discuss which backtesting software has the critical feature required to answer that question.

A Basic Backtest is Trivial to Create

Why are there so many backtesting software packages on the market? From a programming perspective, the basics of a backtester are pretty simple. (My daughter created a basic backtester in an afternoon.)

But to create one that lets you answer the fundamental question of "when to take the signal and when to skip it" is much harder.

It requires the ability to do two things:

Create a trades list from the backtest
Add custom columns to the trades list

I'm always amazed how many backtesters can't even do the first one!

It's because the vast majority of these backtesting tools are created by programmers and not actual traders, much less traders who've created a profitable trading strategy.

Backtesting Software That Works

So, which backtesting software has the fundamental features that can actually get you to the starting line?

There are three available to retail traders:

Those are the ones I know of that allow you to backtest across the entire market (not just a small basket of stocks), produce a trade list in a CSV file, and allow you to add custom columns.

(I'm not including Python, but technically you can build your own backtester using it.)

If I'm missing any, let me know and I'll add them to the list in a future message.

Which One Should You Use?

That depends on the kind of trading you do, your experience, and your programming skills.

I'll go over that tomorrow.

-Dave

Follow-Up Discussion from Jared Tendler Interview

2025-05-05T19:30:00-04:00

On this week's episode of Line Your Own Pockets, we review some topics from last week's interview with Jared Tendler.

We go deeper into:

Learning from top performers in non-trading fields
The parallels of poker and trading
How improving your strategy helps with the emotions of trading
The role of optimism in trading success

LISTEN NOW »

-Dave

When to Take The Signal, When to Skip

2025-05-02T19:30:00-04:00

Now that you have your first backtest, you're ready to tackle the most important part of creating a trading strategy.

Remember, this is a comprehensive list of the occurrences of your original signal, so the equity curve might look terrible at this point. But that's ok.

You're never going to trade EVERY occurrence of the signal, so why did we include each one in the backtest?

Because you need a methodical way to determine which signals are profitable enough to trade, and which aren't.

By including all the signals in the first backtest, you're guaranteeing that the final version of the strategy at the end of this process will have the maximum possible number of profitable trades in the strategy.

Even though the equity curve might look bad, you should be incredibly excited when you step back and think about it.

There is a high likelihood that some combination of the trades already in your backtest will produce a profitable strategy.

You just need to determine which trades are good enough and which aren't.

To do that, you need to apply rules to your strategy to filter out the poorest trades from your original trade set.

The only reliable way to figure out what rules to apply to filter out the bad trades is to add data points to your backtest that could be used to create a rule.

Most traders, at this point, create the rules in their code to filter out trades from their backtest, but that's the wrong approach.

You still want all the trades in the backtest, but you need to add columns to your backtest for each rule you might apply.

This is the essence of building a robust strategy, and yet most traders aren't even aware they can do this.

In fact, most backtesting software packages out there DON'T HAVE THIS CAPABILITY. (I'm talking to you TradeStation!)

Next, I'll go over what backtesters have this fundamental feature.

Until next time,

-Dave

Your First Backtest

2025-05-01T19:30:00-04:00

Yesterday, I described how the "guess and check" approach that most traders try when backtesting seldom works.

What should you do for your first backtest?

Instead of trying to find "the final answer" with your first attempt, create a backtest that captures the entire range of possible trades for your system.

Here's an example. I trade a gap system with a well-defined entry signal that may or may not occur for any given gapping stock on a particular day.

The entry signal is simple - no fancy rules to complicate it.

I know there's some threshold for a minimum gap that I'll end up using in the final version, but I don't know what that is yet.

I also know that I'll end up applying some additional rules, but I'm not sure what they'll be.

The first backtest I run will look for the entry signal with essentially no filtering (or as little filtering as possible).

But won't you end up with more trades in your backtest than your account can handle?

Of course! Way more. Sometimes ten times more than what I end up trading.

My first backtest answers the question: how many times does this simple pattern occur?

I know I'm not going to end up trading every occurrence of the signal, but I start with a comprehensive list.

Once I have that list, I'm ready to answer the next question: under what circumstances is the signal profitable to trade?

In other words, what subset of the entire list of occurrences are worth trading, and which ones should my system ignore?

That's the crux of creating a trading strategy - and will be the topic over the next several days.

But if your first backtest uses a "guess and check" approach, you're not even close to being able to answer the most important question when creating a strategy.

-Dave

The First Backtesting Mistake to Avoid

2025-04-30T19:30:00-04:00

You've got an idea for a trading strategy you want to backtest.

You have some ballpark idea about what the thresholds should be, but you're not sure what the optimal settings should be.

That's ok, you've got powerful backtesting software that can give you the answer for what the settings should be. (That's the whole point of backtesting, right?)

It might take some time, but it's doable, you tell yourself. Just use your intuition for the settings that should work for your strategy, run a backtest, see the results, make adjustments, and repeat.

This iterative process should hone in on "the answer." (Or that's what you believe.)

Your first backtest runs, and you end up with a lot more trades than you thought you would.

And the equity curve sucks.

That's ok, it's part of the process, you tell yourself.

Maybe I should add a relative volume filter to reduce the number of trades, you think.

You add the relative volume filter and run the backtest.

Wow, now you ended up with hardly ANY trades at all!

So you pick another threshold and run yet another backtest.

Pretty soon, you've run dozens of backtests, and you're getting frustrated.

You're nowhere close to finding the right thresholds for your strategy.

In fact, you're probably further away than when you started because you've tried a bunch of settings and haven't kept track of even what you've attempted.

This "guess and check" approach to backtesting is what most traders do, but it's never going to work.

It's like trying to hit a bullseye on a target that's 400m away - with a pistol. You'll fire a lot of shots and make adjustments each time, but a pistol is never going to be accurate at that distance.

If you hit the target, it's going to be purely by accident.

Taking a different approach to your first backtest will save you a lot of frustration.

The first backtest for a strategy should be more like calibrating your scope on your sniper rifle.

More tomorrow.

-Dave

How to Backtest Series

2025-04-29T19:30:00-04:00

If you've known me for any length of time, you know how I feel about backtesting - it's your trading superpower.

Even traders who fully understand this get stuck in the backtesting mud. I'm pretty sure this is the default state when traders start backtesting.

Imagine trying to pierce a bullseye on a target from 400 meters away.

You could try using a slingshot or throwing a dart - those are good tools for similar tasks, but they won't be much help here.

Some will recognize that a sniper rifle with a powerful, well-calibrated sight is the right tool to accomplish the goal.

Now imagine the people who have a sniper rifle - the right tool - but they're using it blindfolded and they don't realize it.

You may as well be using a slingshot.

And yet, almost all traders I come across who backtest are like the people using a sniper rifle blindfolded.

This series of emails will show you how to backtest so that you end up with a strategy that actually works and doesn't just trade market noise.

This is a wide-ranging topic, so here's how I'm planning to organize it.

First, we'll go over strategy creation in general, then we'll move on to specific backtesting software.

After you have a working strategy (according to a backtest), we'll go over the next steps and how to implement it.

Tomorrow I'll go over the first step, before doing a backtest or writing any code.

This is the step where traders put the blindfold on without even realizing it.

-Dave

Interview with Jared Tendler

2025-04-28T19:30:00-04:00

On this week’s episode of Line Your Own Pockets, we interviewed Jared Tendler, a leading expert in how your mental game affects performance.

I've known about Jared since I got heavily into poker a few years ago. He's since branched into trading, coaching traders in their mental game.

He's written an excellent book called The Mental Game of Trading: A System for Solving Problems with Greed, Fear, Anger, Confidence, and Discipline.

Trading and poker? I knew I had to get Jared on the podcast to talk about two of my favorite topics!

This was a wide-ranging interview where we discussed:

The mental side of systematic trading
How poker and trading are similar and different
What traders can learn from top performers in other fields

Find more info about Jared on his website: https://jaredtendler.com/

LISTEN NOW »

Thanks for coming on Line Your Own Pockets, Jared!

-Dave

Beware Magic Numbers

2025-04-25T19:30:00-04:00

Yesterday, I described how using nice, round numbers accomplishes nothing. Today, I'll discuss a related concept called magic numbers.

One of the products I offer is a Trading Strategy Assessment, in which I analyze a trader's strategy and suggest ways to improve it.

After doing several of these, I started noticing a pattern. It's so common that now it's one of the first things I look for when I do a strategy assessment, because the instant I see it, I know there's very likely a simple way to improve the strategy significantly.

Here's an example from this past week to illustrate.

A trader came to me with a day trading strategy that was working ok, but he thought it could be better. (He was right.)

When I looked at his rules, the first thing I noticed was that he was using arbitrary thresholds for the minimum price and maximum price (say, between X and Y) for the strategy.

X and Y, in this case, are "magic numbers" - they came out of thin air with no real data behind why these values were chosen.

When you choose values like this for your rules based on your gut or some arbitrary process, there are trades you're missing.

And when you use magic numbers for filters based on price specifically, you're likely filtering out a LOT of profitable trades from your strategy.

And that was definitely the case here.

When we looked at a wider threshold for X and Y and normalized the values he was using in some of the other rules, we increased the number of trades in his strategy by 5x, without sacrificing average profit per trade.

Look at the rules in your strategy. Are there magic numbers there that are hiding profitable trades from you?

-Dave

P.S. Could your strategy be better? (The answer is almost certainly yes.) If you're interested in doing the same with your strategy as this trader did, hit reply and let me know.

Using Nice Round Numbers in your Strategy

2025-04-24T19:30:00-04:00

One approach I've seen traders take when developing a trading strategy is to use nice round numbers for their rules.

I understand the thought process, and I used to do this, but I've realized over the years that it accomplishes nothing.

Here's an example. Let's say you're trading a gap strategy. You run a backtest and find that the strategy is profitable above, say, a 5.8% gap.

A lot of traders will take that 5.8 number and round it to 6% - because they believe that using 5.8 "would be curve-fitting."

They apply the round number, thinking they've cleverly avoided curve-fitting by doing so.

It might make you feel a little better, but the market doesn't care that you've used that round number versus the more exact number you've proven is optimal.

It's not a serious mistake, but you can skip the song and dance of using a round number because it's not accomplishing anything.

Now think about a year from now when you're going back and looking at your strategy rules.

You see 5.8. That conveys a level of precision that serves as a reminder that you thoughtfully chose it rather than pulled it out of thin air. If you see 6, then unless you've documented your process really well, you're not going to remember exactly why you chose it.

Speaking of round numbers, tomorrow I'll share something I often see in traders' strategies that is a sure sign it can be improved.

-Dave

Why Curve-Fitting Gets Traders Stuck

2025-04-23T19:30:00-04:00

A few years ago, I noticed a phenomenon on Twitter.

A well-known trader was posting his results and described a recent change he had made to his rules that improved his strategy.

Shortly after that, in the replies, another trader chimed in, "Wait, that sounds like curve-fitting to me!"

Don't worry guys - everyone was safe - the "curve-fitting police" had arrived on the scene.

Here's the thing about curve-fitting: you always sound smart and prudent when you point it out.

Remember back to when you first learned about curve-fitting.

In that moment, you probably thought the person who pointed it out was one of the smartest guys in the world.

He had enough experience to know about the monsters lurking around the corner that you didn't realize existed.

Because it sounds so prudent and smart, you give it a little more weight than you probably should.

When you have a strategy that's working, the "curve-fitting sounds smart" bias, along with the "if it ain't broke, don't fix it" bias, is what starts to calcify traders in their status quo.

It's a big reason why so many traders get stuck with one working strategy and not more.

Remember - you are the only one responsible for your trading results.

When you make a boatload of profits from your strategy and wire money out of your brokerage account, there's no checkbox requiring you to certify that there wasn't any curve-fitting involved in the making of that money.

There's a question I like to ask traders who get themselves stuck in the curve-fitting morass.

Do you want to be statistically perfect, or do you want to make money?

-Dave

How To Segment Your Out of Sample Trades

2025-04-22T19:30:00-04:00

Last week, we reviewed a powerful technique for building confidence in your strategy called in-sample/out-of-sample testing.

There are two main ways to create your sets from your backtest: random sampling or by time.

If you come to trading from a different domain, like chemistry or data science, you're probably accustomed to creating your out-of-sample set using random sampling.

In trading, that's wrong - you should always segment your trades by time.

That is, choose a date that puts 80% of the trades in the backtest before that date, and the remaining 20% after that date. (or 70%/30% - people get hung up on the percent, but it doesn't matter that much).

I have a function in my code that I can call that automatically determines this date and segments the trade set appropriately.

So why is random sampling so inferior for our purposes when it's perfectly legitimate in other domains?

Every trading day is another sample that traders around the world look at, learn from, and adjust their own strategies based on.

When you choose to segment by random sampling, you'll have trades in your in-sample set that are more recent than your out-of-sample set.

Because of this, your model will appear to be more optimistic than reality because you'll be training it on "future data" and testing on previous data.

I was convinced this was an issue several years ago when I had a large backtest and tried it both ways and compared.

Although it was subtle, random sampling yielded a model that looked more optimistic than segmenting by time.

When your process is more optimistic than reality, it's like you're wearing rose colored glasses - you're setting yourself up for disappointment later.

Tomorrow, I'll go over one of the main underlying reasons traders get stuck when they consider curve-fitting.

-Dave

Should You Turn Off Your Strategies on Crazy Days?

2025-04-21T19:30:00-04:00

On this week's episode of Line Your Own Pockets, we discuss whether to disable trading strategies on days when the overall market is raging.

We're not talking about run-of-the-mill market movement - we mean the outlier days that, by definition, happen rarely.

Whether you should turn off your strategies depends on how you designed them to begin with.

A perfectly acceptable answer might be to simply turn off your strategies on these days, but you risk potentially missing out on the most profitable days your strategy could experience.

What's the right way to think about it?

LISTEN NOW »

-Dave

P.S. Do you use RealTest for backtesting? I'm testing something that's particularly valuable for RealTest users. If you're interested in helping beta test it, hit reply and let me know.

A Way To Predict The Future

2025-04-18T19:30:00-04:00

Of course, you can't really predict the future, and it's easy to accidentally set up a backtest that assumes you can (be careful!).

But there's a simple technique for simulating how your strategy would have played out "into the future."

It's called in-sample/out-of-sample testing (sometimes IS/OOS).

It sounds more complex than it really is (data scientists like to over-complicate things sometimes), but here's how I like to think about it.

When you create and optimize a trading strategy, you can never be sure it will continue to work. But wouldn't it be nice to look into the future and see if it does?

IS/OOS testing lets you do that by segmenting the trades in your backtest into two sets: a "training" set and a "test" set.

So instead of optimizing across your entire set of backtested trades, you only optimize on the training set.

Then, when you feel you're at a stopping point and you're happy with your strategy, you can see how it performs on the test set - the trades that you held out and therefore are "out of sample."

If you've overfitted your strategy, the performance on the test set is not going to match up with the performance on the training set, so it should be easy to spot.

This lets you pretend you went back in time and developed your strategy at a previous date with all the information you could have known at that moment, and then try to "predict the future" from that point.

This is exactly the situation you're in now - asking yourself how likely your strategy will continue to perform in the future.

I love this because it's a simple thing you can do outside of market hours that allows you to build confidence in your strategy before putting real money on the line.

Next time, I'll address how to create your training set and test set. There are two common ways of doing it, and, in trading, one of them is very wrong.

-Dave

The Easiest Way to Avoid Curve Fitting

2025-04-17T19:30:00-04:00

Yesterday's message was a thought exercise on the best ways to curve fit, hypothetically assuming that was your goal.

Now we return to the real world, where you're trying to minimize it.

The best way to steer clear of curve fitting is usually quite easy: add lots of trades to your backtest.

The more trades you have, the less chance you'll curve fit.

It's not impossible, but with many trades and a healthy dose of common sense, you can worry a lot less.

How do you add more trades to your backtest?

If your backtest has a small number of symbols, add more. (This is one of the main reasons I prefer equities to futures and day trading to swing trading - there are simply way more profitable trades to be had!)

If your backtest covers a certain window of time, explore increasing that window to a longer period that covers more market types.

If you've filtered your signal so it doesn't occur frequently, loosen the filters so it happens more often.

Remember, you can't eliminate the risk of curve-fitting, but you have a lot of control over how you set up your backtest to minimize the chance of it.

I'll focus soon on the exact steps you can use to set up a backtest to give you the best chance of finding a profitable edge from it.

(If you're like most traders, you're probably backtesting wrong!)

-Dave

P.S. Speaking of backtesting, there are still a few days left to beta test a new product I'm working on that helps you optimize your backtests (without curve fitting). If you're interested, hit reply and let me know which backtesting software you use.

Here's what one trader said about it:

"As someone relatively new to trading without a strong quant background, I initially struggled to build and refine a profitable strategy. That changed when I started using Dave’s optimizer. It has completely transformed my trading experience. It has made trading more accessible, significantly less time-consuming, and much more enjoyable—all while improving my results." - Brandon C.

How to Curve Fit

2025-04-16T19:30:00-04:00

One way to think about how NOT to curve fit when creating a trading strategy is to imagine your goal is the opposite.

Let's say your goal was to create the most curve-fitted strategy possible.

An insane goal, I realize, but how would you do it?

Here's what I would do:

Start with a backtest that has a small number of trades.

I would create that by making assumptions about what I thought the thresholds should be.

Apply the backtest to a tiny number of symbols. Preferably just one!

This allows you to restrict the number of trades in your backtest to a really small starting point. Ideal for curve fitting!

Next, sort the trades list by profit and look at the least profitable trades.

Tell yourself there's no way you'd make THAT trade in real-time, so just remove it from your backtest.

Next, look at the data and blindly follow what it suggests. Don't think about it too much - this is data, and data doesn't lie!

If it's an intraday strategy with short hold times and the data suggests a fundamental data point like earnings per share would improve it, just go with it!

If it's a swing trading strategy that holds for several days, find data points for the smallest possible timeframe that "improve" the system, and add a rule for them.

Any improvement by adding a rule, no matter how tiny, is great for curve fitting. The more rules, the better!

Stay away from data points that are normalized. For example, if you have a choice between, say, relative volume and just plain volume today, choose volume today.

Lastly, look at the equity curve for your backtest. Find the days when it performed the worst. Tell yourself you're smarter than that, and you wouldn't have traded that day, so just remove it from your backtest.

Your equity curve should look absolutely pristine at this point.

Oh, one more thing: get your hopes up - there's no way you can lose with this one. Tell your friends how well you're going to do - better yet, post it on Twitter/X.

OK, this is tongue in cheek obviously, but it should give you some good ideas about what to do to avoid curve fitting.

Did you notice anything you might be doing now when you backtest a strategy?

-Dave

Fixing Curve Fitted Strategies

2025-04-15T19:30:00-04:00

Last time, Mateo shared how he determined that his strategy was curve-fitting.

Most traders give up on their idea at this point, but there are several ways to improve a strategy once you've developed it enough to recognize curve-fitting.

Here's what to do if you find yourself in this situation, similar to Mateo's.

There probably wasn't a single rule you included in your strategy that caused all the curve-fitting.

More likely, it was a combination of rules that painted you into a corner, each contributing a different amount.

A good exercise here is to go back and start from scratch, that is, remove all your rules so you're starting from a large set of unoptimized trades from your backtest.

Then, test each rule in order, watching what happens to the equity curve after you apply the rule.

Consider how robust each rule is likely to be going into the future. In other words, how predictive is the rule on your original trade signal.

At every point, be skeptical of the rule - insist that it "tell a coherent story" with your system's trade signal.

If it doesn't seem robust, skip it and go to the next rule.

Your mindset should be less about getting your strategy trading live at all costs, and more like "the data fooled me once already, I'm not going to let that happen again!"

Tomorrow I'll explain the best ways to curve-fit, so you can do the opposite.

-Dave

Turning a Trading Weakness into an Advantage

2025-04-14T19:30:00-04:00

In this week's episode of Line Your Own Pockets, we discuss how one trader went from consistently losing money to trading full-time.

The turning point of this transition was converting one of his weaknesses into a source of new trading ideas.

We discuss:

The trading mistake he was making (it's very common!)
The frustration of continuing to make the same mistake even though he knew it was losing him money
How he turned this mistake into a productive source of new trading ideas
His transition to trading full-time
Much more

LISTEN NOW »

-Dave

Recognizing Curve Fitting

2025-04-11T19:30:00-04:00

In response to my initial question when I introduced the topic of curve-fitting, fellow list member and trader Mateo shared his experience when he recognized he had curve-fitted and what he did to verify and fix it (sharing with permission)

Mateo:

I lost money a few years ago on SPY, which I attribute to curve fitting, but I wouldn't have called it that back then. I had a great looking and producing backtest on SPY. I placed a long call that lost, and so I had an idea: test it on similar tickers! It was amazing on SPY but completely failed on VOO and SPX. I realized that I should get substantially similar results on something so correlated. I found I had filtered out all the bad trades too exactly.

I'm super interested to read your curve fitting insights because you often make me think and eventually change my perspective on market topics.

Dave:

This is exactly the kind of thing I was looking for. So, how long did it take you to figure out that you had curve fitted? And how big was the loss relative to what you were doing at the time?

Mateo:

I figured it out very quickly once I had the idea to try it on other symbols. I only recently learned the word "robustness testing," but I'd say within a couple of hours. In this case, it was a small loss, thankfully.

Thanks so much to Mateo for sharing his experience!

He highlights a great way to quickly recognize curve-fitting in his strategy, and he recognized quickly (a couple hours!) what was going on well before significant losses mounted.

If your strategy is well-designed and predictive, it should generalize to other tickers and markets.

If it doesn't (as Mateo discovered), it should give you pause. It doesn't necessarily mean you should abandon your idea, though.

Next time, I'll discuss ways to try to improve his strategy without completely giving up on it.

-Dave

Is Your Strategy Curve-Fitted?

2025-04-10T19:30:00-04:00

In my last message, I talked about the worst thing that can happen with curve-fitting.

Now I ask the question: Is your strategy curve-fitted?

Yes - to some degree.

Because there's a little bit of curve-fitting in every strategy.

Curve-fitting is not a binary metric - you can't use a curve-fitting ruler and measure to see if your strategy meets some standardized definition.

Think of curve-fitting as having a whole range of degrees rather than some black or white, true/false measurement.

Consider all the rules that make up your strategy. For example, relative volume needs to be greater than X for a signal to meet a strategy's criteria.

Even the most obvious, predictive rule that's highly correlated with profit has a little bit of curve-fitting.

That's because strategies, by definition, are inherently trying to predict the future - which, as it turns out, is hard. Things are always changing, and there's no guarantee a pattern you see will continue forever.

If you accept there's a little curve-fitting in every trading rule you apply, it shouldn't cripple you with fear. The fact there's a non-zero chance of injury or death when you cross the street doesn't keep you locked up in your house forever so you can avoid the miniscule risk.

Tomorrow, I'll discuss things you can do when designing your strategy to minimize curve-fitting so you end up with a robust strategy with staying power.

-Dave

P.S. If you're just getting started trading and you're not getting the traction you know you could be, take a look at the Get Systematic Roadmap. Most beginning traders make the same few mistakes over and over without ever realizing it. This custom blueprint gives you a solid foundation so you can create and improve your own trading strategies with real edge.

Curve Fitting - What's the Worst That Can Happen?

2025-04-09T19:30:00-04:00

Yesterday, I introduced this series on Curve Fitting.

Ever since reading articles years ago about the dangers of curve fitting and how "many a trading career has been shattered" from it, I've been skeptical of these claims.

It's not that I think it's impossible to lose money from curve fitting your strategy. You absolutely can.

But to lose a ton of money from it, you would have to be incredibly naive, have a reckless appetite for risk, and have a sloppy process for making changes to your strategy.

I haven't met a trader yet that I would describe that way.

You should have a default stance of skepticism - about the industry in general, anything you see traders say (especially on Twitter), and your trading strategies.

And if you're reading this, you probably already have it.

When you have a healthy dose of paranoia, a decent process for making changes, and don't aggressively size up, your downside should already be limited.

Even if you naively apply a rule that's egregiously curve-fitted and go live with it (YOLO!), a good process will be able to spot it quickly.

When you have a solid process and are reasonably careful, the worst case scenario from curve-fitting a halfway decent strategy is a flat equity curve that you thought would be up and to the right, not the "end of a trading career."

So work on your process, and the curve-fitting boogeyman should become a lot less scary.

Tomorrow, we have to talk about what curve-fitting is and isn't.

-Dave

P.S. Curve-fitting is on my mind based on the feedback of several traders who are beta testing a new product I'm working on - a tool that helps you create a trading strategy with edge. The window for beta testing is ending soon, so reply quickly if you're interested in a sneak peek.

Curve Fitting Series

2025-04-08T19:30:00-04:00

I'm going to do something a little different this week. Instead of a single email on Wednesday, I will send an email each day about a single topic: curve fitting.

In all my interactions with traders, I think there's no more misunderstood topic than curve fitting.

I've seen traders freeze up and not take action due to a fear of curve fitting.

Some traders bypass ways to improve their trading strategy that would clearly make them more money because they "fear it might be curve fitting."

And yet other traders do quite well by seemingly ignoring the topic altogether.

What's the right way for traders to think about curve fitting? That's what I want to explore in this series.

First - a question.

Have you ever lost money in your own trading due to a decision you eventually concluded was curve fitting?

Hit reply and let me know - I'm genuinely curious.

-Dave

P.S. When I started this newsletter, I wondered if I would have enough topics to write about. I quickly realized that was the least of my concerns. I keep a list of topics in Notion so I don't forget them. There are over 300 ideas on the list and counting!

I realize now I'll never get to all of them if I don't write more frequently, hence this experiment.

How To Trade When The Entire Market Is Moving

2025-04-07T19:30:00-04:00

In this week's episode of Line Your Own Pockets, we discuss how to prepare for trading days when the entire market moves.

When your strategy is looking for unusual moves, but then on the rare trading days where everything is "unusual," what do you do?

I revisit the first time this happened to me when trading gaps.

We discuss:

How to react in real time when you trade systematically
What you can do afterwards to prepare for the next day
How to zoom out and look at the bigger picture on days like these

LISTEN NOW »

-Dave

P.S. Interesting that we recorded this episode over two weeks ago, back when things were relatively normal.

Four Years of Practice

2025-04-02T19:30:00-04:00

My wife and I went to a concert over the weekend. She's always on the lookout for live music to go to, mostly at a storied local venue called the Cat's Cradle.

The band we saw was Palmyra, and they were great - fantastic energy, a cohesive set, and all-around fun to watch. They were very polished.

Partway through, the lead singer shared a little about their background.

And it became very clear how they had become so good.

They have been touring for FOUR STRAIGHT YEARS.

When they started, they played on the road in any place that would let them to play.

Imagine their process - all the mistakes, all the crowd reactions, all the tweaks to their performance and songs over time.

They put themselves in a position where they were forced to get better - with that much practice, how could you NOT get great?

Now imagine two traders.

One is talented but reviews their performance every once in a while when it's convenient.

The other isn't as talented, but meticulously reviews his trades every day, constantly brainstorming ways to get better and improve his strategies.

Which trader do you think will be better?

What about after four years?

-Dave

Do You Chase Trading Perfection?

2025-03-31T19:30:00-04:00

In this week’s episode of Line Your Own Pockets, we discuss some traders' quest for the perfect strategy and how this can stand in the way of trading success.

You don't need a perfect strategy to do well. Needing to be perfect is an impediment.

We discuss ways to untangle traders from this counterproductive mindset.

LISTEN NOW »

-Dave

Simple Ways to be a Losing Trader

2025-03-26T19:30:00-04:00

Here are some simple ways to be a losing trader.

Don't keep a journal - just eyeball your daily P&L number
Enter trades without a plan to exit
Place trades manually in the GUI (or even better, on your phone)
Use ballpark position sizing - size your positions based on feel
Watch other traders post their trades on X/Twitter
Whatever you do, don't backtest

Any other good ones that I missed?

-Dave

Make Things Real When Trading Is Going Well

2025-03-24T19:30:00-04:00

In this week's episode of Line Your Own Pockets, I describe something I do with all the traders I work with.

When your trading is going well, sometimes it can become removed from real life - just a number in your account that you're trying to increase.

To get to the next level, it's important to make trading real - especially if you're trading on the side - to make it more than a number in your bank account.

LISTEN NOW »

-Dave

The Best Way to Create an Awesome Trading Strategy Is...

2025-03-19T19:30:00-04:00

...to start with an OK trading strategy and improve it.

By far my favorite trading topic is how to improve a trading strategy.

I see so many traders get stuck in a drawdown because "my strategy stopped working."

But there are lots of different ways to make a trading strategy better.

The more you work on your process for adapting and improving, the more robust your strategies will be.

Here's a slide from the webinar I'm doing tomorrow for Interactive Brokers called How To Improve Any Trading Strategy that describes several ways to make your strategy better.

Ways To Improve a Strategy

Exclude the worst trades using a rule
Adding more trades to an existing system
Take your best trades with bigger size
Use what you’ve learned to create a new strategy

I'll discuss the specific situations to look for in your strategies that make each of these improvement paths viable.

The webinar is tomorrow, 3/20/2025 at 2pm ET. Even if you can't attend live, go ahead and register so you can be notified of the recording and watch it afterward at your leisure.

This is not a sales call masquerading as a webinar - this is practical advice to apply to your own trading.

I hope to see you there.

-Dave

Take Your Best Trades with Bigger Size

2025-03-17T19:30:00-04:00

In this week's episode of Line Your Own Pockets, I describe a free call I had with a fellow list member.

He has made money every year for over a decade but was thinking about quitting trading.

Why? He felt like he had reached a plateau that no matter how hard he tried, he couldn't push through.

After learning more about how he traded, I suggested two main ways to improve.

Automate his trades so he can add more trades to his system.

But the biggest potential for improvement was identifying his highest confidence trades and taking them with bigger size.

Although this is easier in some strategies than others, this is one of the best ways to improve a trading strategy.

LISTEN NOW »

Announcement: I'll be discussing this topic in a free webinar with Interactive Brokers this coming Thursday at 2pm ET called How To Improve Any Trading Strategy.

-Dave

How to Exclude Chinese Stocks Automatically

2025-03-12T19:30:00-04:00

Many traders recognize the unpredictable behavior of Chinese stocks and look to exclude them from their strategies.

Or specifically include them in a strategy.

Before I left Trade-Ideas, I implemented a feature I knew would be valuable: dynamic lists based on country.

In Trade-Ideas, you can use a symbol list to define the universe to your strategy.

You can create your own and manually add symbols to it and then include them in your strategy by pointing to it in the Symbol Lists tab in the configuration.

You can choose to restrict the strategy to the symbol list or you can exclude the symbols in the chosen lists.

There's a steady stream of Chinese IPOs, so if you try to manually maintain a list of symbols, it becomes outdated quickly.

This is where the new feature comes in.

If you go to the symbol lists tab in the Configuration window, you'll see a Countries item that you can expand.

These lists are dynamically generated and maintained on a daily basis, so they're always up to date.

You can add lists from any country and exclude/include multiple symbol lists in your strategy, even mixing dynamically generated lists and your own custom lists.

If you find this useful, hit reply and let me know - I suspect there are a lot of users unaware of this feature.

-Dave

Profitable Traders Keep A Journal

2025-03-10T19:30:00-04:00

Winners keep score. Period.

In this week's episode of Line Your Own Pockets, we discuss:

What a trading journal is and isn't
Mistakes most traders make when keeping a journal
What data points you need to keep track of and what you can ignore
Why keeping a journal helps you make money
How to be as efficient as possible

LISTEN NOW »

-Dave

P.S. I'm carving out time again for some free calls. If you're a trader and you aren't making money each month, I guarantee I can help. Click here to schedule a free call - no strings attached.

Automate Trade Exports from TWS

2025-03-05T21:00:00-05:00

Here's another lesser-known feature in Trader Workstation that I encourage traders to explore.

Getting a list of your trade executions in any trading platform can be a pain - especially when you should be adding your trades to your journal daily.

Because you should be doing it routinely, it's worth thinking about how to make this process as smooth as possible by removing as much friction as you can.

Most IB traders - if they track their performance with a journal at all - wait until the following morning for the daily execution report to become available in their IB account.

If you wait until then, you'll likely forget important details about your trades that you need to capture when they're fresh in your mind.

Here's where the Export Reports feature in TWS comes in handy.

The image above shows how to enable it. Once activated, every few minutes (I have mine set to 5), TWS writes a CSV file with all your executions for the day to a folder you specify.

You can control which fields are written, including the important Order Reference field which can be used in your custom program to specify which strategy the trade came from.

This lets you keep an automatic archive of all your executions so you don't have to remember how to generate the list in your IB account. (I always forget how to do it and have to relearn it every time!)

Here's a screenshot of the CSV files in my export directory - the oldest one is from 2016:

Not only does this provide a convenient archive, but you can use the files to easily enter trades into your journal.

I have a script that I run via an AutoHotKey shortcut that looks for today's file, formats it exactly the way TraderVue expects, and copies the content to my clipboard.

Then I just paste it in the TraderVue trade import field - no data entry required.

This will soon be coming to DAS Trader - I put in a request to them recently for this feature and they've confirmed they're working on it now.

What NOT To Automate In Your Trading Business

2025-03-03T20:30:00-05:00

In this week's episode of Line Your Own Pockets, we discuss a topic that might sound strange coming from me - what parts of your trading business SHOULDN'T you automate?

Shouldn't you automate everything?

This is something I've changed my thinking in over the years.

There are some things in your trading that you shouldn't automate even if it's technically possible to do so.

We discuss the realization I had recently about this and how you should think about this in your trading.

LISTEN NOW »

-Dave

Overriding Your Plan - The Right Way

2025-02-26T20:30:00-05:00

You've created a solid strategy by backtesting and you're trading it live.

You assumed you thought of everything.

But now you're in a trade and you realize it's a situation you didn't consider, so you decide to use your intuition and override your system.

You can guess what happens next - your decision to override your system ruined a perfectly good trade.

I worked with one trader who could not stop manually overriding his strategy.

And his results were inevitably worse than if he simply let his trades play out according to the system he designed.

"I just need to be more disciplined" he would tell me.

And I assumed that was correct - but the overriding continued.

Instead of cracking the whip on this discipline problem, I had him walk through an example of his thought process as he overrode his plan in a particular trade.

I realized this wasn't a matter of poor self-control - he wasn't overriding out of pure emotion.

There was sound reasoning for each of these override instances. The ideas here were the seeds that could turn into viable improvements in this strategy and even new unique strategies themselves.

So, instead of trying harder and harder to muster up enough discipline to follow the rules, we took a completely different approach.

We turned this lack of self-control into a process to generate new ideas.

Whenever he felt the need to override the plan, he would use that energy to document the situation - take a screenshot of the chart, make notes about his theory, etc.

Then after market hours, he would treat it as a new idea to backtest and track down an answer to.

Over time this turns into a steady stream of new ideas - potentially profitable ideas to test.

He turned his lack of self-discipline into an advantage.

Fast forward several weeks and this same trader mustered the courage to ditch his day job and trade for a living.

-Dave

Edge Erosion

2025-02-24T20:30:00-05:00

Also known as "the sky is falling."

In this week's episode of Line Your Own Pockets, we discuss a topic that's been around as long as strategies have existed: Edge Erosion.

We go over:

The definition of Edge Erosion
The inevitability of strategies decaying
Your ability to adapt is the most important thing
Whether or not your edge is eroding, your path to long-term success is the same

And much more.

LISTEN NOW »

-Dave

How To Prevent TWS Nightly Shutdowns

2025-02-19T20:30:00-05:00

If you're an IB user, you're probably familiar with Trader Workstation's (TWS) annoying nightly shutdowns.

I've been an IB customer forever, so until recently, I thought this was something you just had to live with.

If you wanted to trade the early pre-market starting at 4 am, you had to wake up and log into TWS first.

As some of you know, I'm an early riser, but not THAT early.

Somewhere along the way (not sure when), IB has added an option to control this behavior so that you only have to actually login once a week instead of daily.

In TWS, go to Global Configuration, then go to Lock and Exit.

You'll see the configuration screen below. The default is Auto logoff, but if you enable the Auto restart option, TWS will survive the night and you'll still be logged in the following morning.

Very useful (essential!) if you want to trade the pre-market.

I have a few users using software I've developed to trade automatically through DAS (including the short locates) and/or TWS.

If you're interested in hearing more about the software, hit reply and let me know.

-Dave

Position Sizing is Sexy

2025-02-17T20:30:00-05:00

OK, maybe position sizing isn't sexy, but it's certainly an underrated topic that a lot of traders get wrong. (For a real-life example, see this message I sent to the list a few months ago.)

In this week's episode of Line Your Own Pockets, we discuss all the position sizing techniques I've used in my strategies. Michael was shocked to hear I use constant sizing in a couple of my models, but despite his skepticism, I can assure you there's a good reason for it.

We discuss different sizing approaches:

Constant shares
Constant dollars
Percentage of account
Sizing by volatility (ATR, for example)
R-Multiple approach (sizing on distance to stop)
Kelly criterion
Martingale

And much more.

LISTEN NOW »

Why I Don't Trade Futures

2025-02-12T20:30:00-05:00

A lot of traders I talk to seem surprised when I tell them I don't trade futures contracts.

When I explain why, I can tell there are some a-ha moments in their responses, so I thought I'd share the reasons and see what you think.

It's not that I don't think I can find an edge in futures contracts (I spent time researching a few years ago and found an edge or two).

And I get that there's a lot of liquidity and leverage in the major contracts - all things being equal is a good thing.

But, when you trade seriously you need to have a path to the kind of confidence that allows you to trade with significant size.

I could see that path in futures, but I could also see lots more paths to confidence in lots more edges trading stocks. Here's why.

With Futures, Every Trader Is Looking at the Same Chart

Maybe they're looking at different timeframes, but everyone is basically looking at the same chart. Which is very easy to do. Anyone with an internet connection can look at the same chart (for free!) that every other trader is looking at.

With equities, there are at least 2,000 tradeable stocks each day. Scanning all those charts in real-time is a far more technically challenging problem to solve.

So by trading equities, you instantly reduce your trading competition to a much lower number.

It's Trivial to Backtest A Single Chart

Think of the number of tools out there that can "backtest" a single instrument. It's hard to find a tool that doesn't backtest because it's a relatively simple problem to solve.

My daughter created a backtester in a couple of days! That's not the hard part, though. The hard part is applying it to the entire market.

So, again, your ability to backtest across the entire market will reduce your trading competition still more.

More Opportunities - A LOT More

When you apply a trading strategy to futures contracts, what's the most number of signals you can generate in a day? Take a simple strategy like an opening range breakout.

With a futures contract, there is by definition at most one occurrence of an opening range breakout per day. Some days there will be zero. Of course, not all of them are going to have an edge.

So you're going to have to go back a long time to gather enough signals to construct a real trading edge.

Now think about how many opening range breakouts there are in the stock market every single day. It's a ton.

There's plenty of edge there if you know how to find it. (For reference, one trader I'm coaching on his backtesting process created a strategy with 3+ trades a day with serious trading edge.)

You might find 3 trades a month with that type of strategy in futures.

It's not that there's no edge to find in futures, there's just more edge in equities and it's easier to find with the right process.

So with equities, there is:

Less trading competition
More opportunities
More trading edge that's easier to find

Oh, and less curve fitting to worry about.

You Finally Have an Edge - Now What?

2025-02-10T15:00:00-05:00

In this episode of Line Your Own Pockets, we discuss how you should think about sizing up a strategy that you know has a trading edge.

We go over:

Why most traders size up too quickly
The math behind changing position size
The situation to avoid when you're sizing up

And much more.

LISTEN NOW »

Scaling Up a Trading Strategy

2025-02-05T19:50:00-05:00

Once you've got a trading strategy that's working - even a little bit - there are lots of ways to improve it.

Most traders simply increase size in their existing trades, but that's only one of many possible dimensions for increasing profits.

Raising your size leaves the underlying strategy unchanged (it's working - don't touch it!)

But you have so many options for improving the strategy itself:

Add a rule to remove poor trades (without curve fitting)
Find the subset of trades with the most edge and trade them bigger
Add more trades to your system that you're currently ignoring

One of the most overlooked approaches is the last one - adding more trades.

Think of it as scaling horizontally (adding more trades) versus scaling vertically (simply adding size).

In the next webinar on Monday, I'll be sharing how I did this and took a modest strategy that was trading 2-4 times per day and added a LOT more trades - all while significantly increasing the average profit per trade.

Bring your questions - there were several good ones in last month's webinar and the feedback was great.

I'm confident this one will be even better.

Don't worry - it's free - and it's not some thinly veiled sales call masquerading as a webinar.

I'll be sharing exactly what I learned during that process so you can get better, too.

I hope to see you there - if you can't make it, register anyway to get a link for the recording.

-Dave

Should You EVER Take Partial Profits?

2025-02-03T19:40:00-05:00

In this episode of Line Your Own Pockets, we discuss one of the most common suggestions from so- called trading gurus and why it's so bad.

We discuss:

Why taking partial profits is not all it's cracked up to be
The math behind taking partials in a strategy
One narrow situation where I DO recommend taking partials

And much more.

LISTEN NOW »

Shorter Drawdowns

2025-01-29T21:00:00-05:00

Think about your most recent drawdown.

How deep was it? How long was it before your next equity high?

Now imagine how it would have felt if it was half as long and half as deep.

Traders who have more manageable drawdowns didn't get there by accident.

Traders who are successful for decades didn't have a magical thought one day that created their success.

It was hundreds of small decisions over months and years.

They're trading strategies that are better than yours now, but...

They started with a strategy just like yours (or even worse) and improved it over time.

Sure, good trading is hard, but it ain't magic.

What can you do today to be the kind of trader in 6 months that has significantly shallower drawdowns?

Doing things today gives you a path to confidence which will eventually lead to trading with bigger size.

Why I Left Trade-Ideas

2025-01-27T21:00:00-05:00

In this episode of Line Your Own Pockets, I share the details about why I left Trade-Ideas several months ago.

I discuss:

Why I decided I had to leave Trade-Ideas
What happened to my trading immediately after
The power of focusing on one thing rather than spreading yourself too thin

And much more.

LISTEN NOW »

Smarter Custom Formulas

2025-01-22T21:00:00-05:00

Tom G., a client (name used with permission), came to me with an observation.

"I'm seeing a pattern with my strategy. When filter A, B, and C values increase, those trades tend to perform better. Is there a way to scan for that?"

The smart way to do this is to create a custom formula for A < B < C.

When the values increase, the custom formula is 1, and 0 otherwise.

And that's how most traders handle it - but there's a far more powerful way to do this.

When you reduce a situation to a yes/no boolean, you essentially remove valuable details in the process.

Consider two very different examples:

A = 1, B = 2, C = 3

A = 1, B = 2, C = 1000

In both cases, the value for the "increasing" custom formula would be 1 since A < B < C.

But, of course, these are VERY different situations - it doesn't make sense to reduce this to a simple boolean.

To simplify the example, let's consider a more common scenario familiar to traders.

How does your strategy perform when the price is above the 50-day moving average versus below?

You could create a custom formula for Price > 50DayMA that results in values of 1 or 0.

A better way is to use a continuous variable such as the distance from the 50-day moving average:

Distance from 50DayMA = (Price - 50DayMA) / 50DayMA

This allows you to use a single variable without removing important details unnecessarily.

Continuous variables are far easier to optimize than booleans.

Handling a Trading Mistake

2025-01-20T21:00:00-05:00

In this episode of Line Your Own Pockets, I shared the details of a trading mistake one of the traders I coach made and how he responded to it.

This situation is a very common scenario among traders - how would you have handled it?

We discuss:

How to respond to a trading mistake like a pro
The worst outcome is when you MAKE money from a mistake
Details about his trading setup which is a novel use of Trade-Ideas and Amibroker
How to tighten up your process so you don't make the same mistake again

And much more.

LISTEN NOW »

How To Get Feedback From The World's Best Traders - For Free

2025-01-15T21:00:00-05:00

You're backtesting a strategy.

You think it might work, but you're not sure.

If you just did a little more backtesting THEN it will be ready.

Wouldn't it be great if the best traders in the world would give you a direct and unbiased analysis of the trading strategy you're backtesting?

What if I said you can and the feedback is essentially free?

This is exactly what happens when you start trading a strategy live with minuscule size.

Most traders think their job is done when the backtest completes.

But that's where the real learning begins.

I wouldn't go live at any size with a crappy strategy, but I see a lot of traders get stuck in "backtest world".

Your strategy will never be perfect.

But the best way to create a great strategy is to start with an OK one and improve it.

Creating A Trusted Trader Group

2025-01-13T21:00:00-05:00

In the latest episode of Line Your Own Pockets, Michael and I reflect on last week's interview with Brett Steenbarger.

We discuss:

Successful traders cultivate relationships with other traders
How to create a trusted trader group
Givers are more successful than takers
How to structure a trading business

And much more.

LISTEN NOW »

Long/Short for 2025

2025-01-08T21:00:00-05:00

Long on systematic trading, short on traders who are exclusively discretionary.

Long on LLMs for improving your trading, short on LLMs for trading on your behalf.

Long on traders that take curve fitting head on, short on traders that use curve fitting as an excuse to be stagnant.

Long on traders that run out of buying power, short on traders that lack a path to confidence in what they’re doing.

Long on traders who love trading for its own sake, short on traders with hard P&L goals and deadlines.

Long on traders who use automation, short on traders who are still “click trading.”

Long on traders who trade multiple strategies, short on traders who make trades by following a trading room.

Long on traders who aren’t against paper trading, short on traders who spend too much time in “backtest world.”

Long on traders who trade strategies across many instruments, short on traders who trade a single instrument.

Long on humbly curious traders, short on traders who think they’ve found the answer.

Long on traders who share, short on traders who operate in silos.

Long on traders who have empty inboxes, short on traders who say they’re too busy.

Long on trading groups, short on trading rooms.

Long on genuine endorsements, short on affiliate programs.

Interview with Brett Steenbarger

2025-01-06T21:00:00-05:00

In our third interview for Line Your Own Pockets, Michael and I spoke with my friend Brett Steenbarger, a well-known trading psychologist and author of several excellent trading books.

It was a great conversation where we covered:

Brett's background, his worst drawdown, and how he responded
What academia and trading have in common
The psychology of systematic versus discretionary trading
His hybrid quantitative/discretionary approach to trades
What individual traders can learn from the team structure of hedge funds
Details about his upcoming trading book Positive Trading Psychology

And much more.

LISTEN NOW »

Trading Reviews

2025-01-01T21:00:00-05:00

It's a new year and a natural time to review your trading results.

Some of the most productive ways to improve come from periodic analysis of your aggregate trading results.

Here's a list of ways to improve your trading by doing a review.

Figure out how to make more trades from an already profitable system
Take fewer but more profitable trades from a system
Automate your reporting so you don't have to collect and parse a lot of data to get it in a format to make smart decisions
Review your best trades to figure out how to take them with bigger size
Review your worst trades to figure out how to weed them out or minimize their impact
Take more size in the strategies that are working well
Look at trades outside your strategy's trading rules - are there ways to trade them profitably?
Look at the time it took to create your most recent profitable strategy - how could you reduce that time by 75%?
What are the bottlenecks in your trading business? How can you eliminate them?
Did you make emotional decisions in your trading in the past year? Did they end up helping or hurting your results?
Is there tail risk in your strategy that you might not be considering?
How often did you run out of buying power in the last year? If the answer is not very often, then consider moving some money to allocate elsewhere
What would your results look like if you added a strategy that traded more often and had better results? Create it.
If you could go back and get a redo of the last year, what would you have done differently?

What else did I miss?

24 Hour Trading Is Coming

2024-12-30T21:00:00-05:00

The ability to trade 24 hours a day is coming to the US equities markets. In this week's episode of the Line Your Own Pockets podcast, we discuss this structural change and what it means for systematic traders.

How should you approach this change when, like pre-market trading, can take years for participants to adjust in meaningful ways?

What does it mean for the amount of data points your backtesting software will need to process?

Will it make things more or less volatile?

We discuss all these issues and more.

LISTEN NOW »

-Dave

Trading Rules from a Nun

2024-12-25T21:00:00-05:00

My wife, Joan, sent me this video that she knew I'd love:

Art + Life Rules from a Nun (Youtube, 14:21 - worth it!)

I've always been fascinated by the parallels between art and trading.

In both, success comes from thinking creatively and coming up with ideas nobody has ever thought of. (That's hard!)

It takes years of diligent, daily work to get great.

The video is about Corita Kent, a nun, artist, and teacher. It lists her 10 Rules for Artists and Teachers.

All of the rules are great but pay particular attention to #7 and #8, which would make great topics for the podcast.

Maybe the best concept is her idea of "plork" which will surely resonate with successful traders.

Which rule do you like the best? Reply and let me know.

Happy Holidays!

Evolving Over Time As A Trader

2024-12-23T21:00:00-05:00

One of the key takeaways from last week's interview with Marsten Parker on Line Your Own Pockets was his ability to evolve over time.

In this week's episode, Michael and I discuss reinventing yourself as a trader and why it's so important to anticipate having to adapt before the market forces you to.

LISTEN NOW »

-Dave

What's Your Most Frustrating Backtesting Problem?

2024-12-18T21:00:00-05:00

If you could wave a magic wand and solve your most frustrating problem with backtesting, what would it be?

Is there an issue you're running into that could unlock your trading potential if you solve it?

I'd like to hear it - hit reply and let me know.

-Dave

Interview with Marsten Parker

2024-12-16T21:00:00-05:00

On this week's episode of Line Your Own Pockets, we spoke with market wizard and long-time systematic trader Marsten Parker.

He's the creator of the RealTest backtesting software.

We discuss:

Trend following versus mean reversion
Over-optimization of trading strategies and how to avoid it
The role of discretion in automated trading
Reinventing yourself as a trader
Much, much more

LISTEN NOW »

-Dave

Notification Nirvana

2024-12-11T21:00:00-05:00

When you write code to execute trades, it's important to have a good framework for sending notifications.

If you send notifications for every little thing, you will become desensitized to them and risk missing the critical ones.

If you don't send any notifications, you risk tethering yourself to your trading desk waiting for an important event that might occur at any moment.

A well-designed system for notifications is an investment in your freedom.

I've tried several ways to send notifications over the years but nothing was perfect.

Slack seems like a nice choice, but it lacks flexibility in prioritizing notifications.

A trader friend suggested Pushover, so I gave it a try.

The API is super simple with code examples for any language (or even the Windows command line).

What I love about it is the ability to prioritize notifications and control how your phone responds.

Low-priority notifications can be silent, while high-priority notifications (like a rejected order) can be configured with a custom sound and escalating nagging if you don't acknowledge it.

So you can write your code once to send notifications with various priorities and then after the fact configure your phone to respond in the way you want (even overriding your Do Not Disturb settings when appropriate).

Give it a shot and let me know what you think.

-Dave

Charting Software Roundup

2024-12-09T21:00:00-05:00

What charting software should you use? How many monitors do you need?

When should you add an indicator to your charts?

Michael and I discuss these questions and other chart-related topics on this week's Line Your Own Pockets episode.

LISTEN NOW »

-Dave

The Wrong Way to Backtest

2024-12-04T21:00:00-05:00

If you spend a lot of time waiting for a backtest to complete, you're doing it wrong.

Imagine you're hunting deer.

You go into the woods.

But instead of a rifle, you bring a machine gun and fire it randomly in every direction hoping to hit a deer.

How effective do you think that strategy would be?

And yet that's what I see most traders doing when they backtest.

A random, haphazard process that will never yield results.

Backtesting with an organized plan is far more effective.

If your backtests aren't turning into real trading edge, I guarantee I can help.

Hit reply and let's talk.

Choosing Backtesting Software

2024-12-02T21:00:00-05:00

There are many choices in the market for backtesting software. In this episode of Line Your Own Pockets, we discuss the landscape of options for backtesting.

I rule out several of the most popular backtesters right away because they don't meet my strict requirements.

If you're interested in backtesting and don't know where to start, this is the episode for you.

LISTEN NOW »

-Dave

Risk of Ruin

2024-11-27T21:00:00-05:00

If drinking coffee in the morning doesn't wake you up, try shorting PGHL yesterday.

Halted most of the day and traded up 1000% after the close.

I didn't trade it but several did.

This is a good situation to study closely.

Yes, the S.E.C. should be doing more to prevent this, but that's out of your control.

Are there tail risks in your trading you're not considering?

What can you do to avoid disaster?

Using Regime Filters in a Strategy

2024-11-25T21:00:00-05:00

What is a "Regime Filter" and is it a good idea to use in a strategy?

Michael and I discussed this topic on the Line Your Own Pockets podcast after DayTradingZoo suggested it on X.

We take completely different approaches on this one.

Who's right? Reply and let me know what you think.

LISTEN NOW »

-Dave

"Expert" Opinions

2024-11-20T21:00:00-05:00

I was at the Laguardia airport during the recent construction project.

Walking towards my gate, I looked up and right in front of me was a man wearing a hard hat with this message on the back.

I had to stop and snap a photo.

"One test is worth 1000 expert opinions"

Just 1000?

What's true for this engineer's construction project is even more true for your trading.

Real power is the ability to do your own testing rather than relying on someone else's opinion.

Which at first generates more questions.

But eventually creates answers.

Which turn into actions.

Which becomes P&L.

Removing The Worst Trades from a System

2024-11-18T21:00:00-05:00

One of the most common and quickest ways to improve a trading system is to remove the worst pocket of trades.

In this week's episode of Line Your Own Pockets, Michael and I discussed a listener question about how to accomplish this with a system he's trading.

Several foundational steps must be in place before you can make these improvements to your strategy.

LISTEN NOW »

-Dave

Sizing Up

2024-11-13T21:00:00-05:00

Garrett Drinon of SMB Capital (used with permission):

"How do you determine when to increase the risk per trade on your model?"

A great question that deserves an entire book to address properly, but here is the short version.

Most traders increase their size too quickly.

There's no rule that says you have to scale up all at once - do it over weeks or even months.

Make sure you're set up to view your performance in a way that's normalized across your sizing.

That is, if you're only looking at raw P&L, then it's going to be heavily skewed toward the trades after you increase your size.

The important thing to avoid is sizing up enough such that normal losing trades push your equity curve into negative territory.

That can be demoralizing and unnecessarily puts you in a position to make mistakes.

Thanks for the question, Garrett!

We'll have a podcast episode on this topic in the future, no doubt.

Trading Well with Limited Time

2024-11-11T21:00:00-05:00

"How can I trade well when I only have a limited amount of time to dedicate to it?"

This is one of the top questions I get from traders.

In this week’s Line Your Own Pockets episode, Michael and I address this issue and discuss the early part of my trading career when I had a very restrictive schedule.

Can this situation be a good thing? No doubt it can!

LISTEN NOW »

-Dave

Fooled By Data

2024-11-06T21:00:00-05:00

One of my favorite quotes:

"If you torture the data long enough, it will confess to anything." - Ronald H. Coase

Coase didn't realize it when he said it, but it perfectly applies to systematic trading.

And it should keep you awake at night a little.

It's hard to tell if you've tortured your backtest too much or just right.

But here's one thing that is easy to do and I found out by accident helps a lot.

Among all the data points (a.k.a. columns, indicators, or features) in a backtest, add a column with random values.

Then continue with your analysis as you normally would.

If you find your random column appearing in your analysis as "important"

Then you know you're trying too hard and it's time to stop the torture.

This is something I include in every strategy assessment I do.

Here are the results of a recent strategy assessment (see image below).

This trader removed the trades in the red line and is left with the trades in the green line.

The average profit per trade is up over 50% while steering clear of the torture threshold.

If you're interested in learning more about making your strategy better, hit reply - happy to chat.

Using News in a Trading Strategy

2024-11-04T21:00:00-05:00

In this week’s Line Your Own Pockets episode, I go over several ways of incorporating news into a trading strategy.

Using the news doesn't necessarily mean manual trading.

Michael and I discuss several ways to use it in an automated strategy.

LISTEN NOW »

-Dave

Stop Caring So Much

2024-10-30T20:00:00-04:00

If you find yourself hoping and praying that particular trades become profitable...

If you've ever thought "If only this trade works, then I'll be able to sleep better tonight."

If, like a cheerleader, you root for your trades to score a basket.

...then you're too invested in the wrong thing.

It's great that you care about success.

But ironically, the more you prepare for long-term trading success, the less you should care about the success of any particular trade or day.

Zoom out and care more about your strategy rather than any trade within it.

Social Media

2024-10-28T20:00:00-04:00

In this week’s Line Your Own Pockets episode, we discuss social media and the implications for traders of the research we highlighted in the previous week.

If social media is so predictably wrong, how can traders use it?

Should they use it at all? How?

LISTEN NOW »

-Dave

Get More Systematic

2024-10-23T20:00:00-04:00

Many traders know they need to become more systematic, but don't know where to begin.

Depending on where you're starting, getting to full automation can be daunting and scary.

Try this simple thought exercise.

Think about your trading day.

Think about all the actions you take from the opening bell to the close.

Now consider every action you take as a failure of your trading process.

When you look at it in this light, everything you do becomes an opportunity to improve.

Are you scanning through dozens of charts to find your setup to trade? How can you cut that in half?

Are you making discretionary decisions during the trading day? How can you plan ahead to make those decisions ahead of time?

Are you doing math in your head to determine your position size? How can you eliminate that step entirely?

Treating everything as a "failure" can help you focus on your trading process.

And improving your process pays off forever.

Beware Financial Influencers

2024-10-21T20:00:00-04:00

In our first interview on the Line Your Own Pockets podcast, we spoke with Dr. Seyed Mohammed Kazempour about his academic research paper called Finfluencers.

If you follow any traders on social media, you are going to want to listen to this one!

Seyed's research shows that the more followers someone has on social media, the more edge you have doing literally the OPPOSITE of what they say.

LISTEN NOW »

-Dave

Looking Into The Future

2024-10-16T20:00:00-04:00

A trader recently approached me with a backtest that he thought had the potential to be more profitable than it was.

(He was right.)

But when I analyzed it I quickly realized he was overlooking a serious problem with his strategy.

And it wasn't a problem that would be nice to fix someday, but one that needed to be solved immediately before doing anything else.

Here's what I noticed. Can you see what the issue is?

It's subtle, but the problem is the optimal filter that my tools found was too good to be true.

Once glance at this chart and I realized that some of the data in his backtest was "looking into the future." That is, he was including data in his backtest that couldn't be known at the time of the trade.

For example, the value of an indicator just one bar AFTER the entry.

The dangerous part of peering into the future in your backtest is it's so subtle that it's very hard to notice.

I once traded a strategy every day for a couple of weeks before I noticed what was going on.

That was a big wake-up call.

From then on, part of my trading process is a simple check to make sure no part of the strategy looks into the future.

Every trader who gets the roadmap understands this pitfall and has a process to prevent it from ever happening.

Has this ever happened to you?

Strategy Drift

2024-10-14T20:00:00-04:00

What is Strategy Drift?

I learned it the hard way when I realized my strategy wasn't quite as systematic as I thought.

In this week’s Line Your Own Pockets episode, I go over what strategy drift is and why I completely changed how I approached the markets after I experienced it.

LISTEN NOW »

-Dave

A Bad Backtest

2024-10-09T20:00:00-04:00

Thomas Edison failed 10,000 times before he invented a light bulb that would work.

How many times have you had an idea for a trading strategy only to find out after testing that it didn't meet your high hopes?

Great traders understand this isn't a failure.

But a building block.

To a better idea.

Does your process turn "failed" ideas into building blocks?

Prioritizing Your Trading Work

2024-10-07T20:00:00-04:00

Successful trading requires a lot of work, including improving existing strategies, reviewing performance, adding new strategies, etc.

Given your limited time and resources, how do you decide what to work on next?

What's likely to give you the biggest payoff?

In this week’s Line Your Own Pockets episode, we discuss a framework for deciding what to work on that will give you the highest ROI.

LISTEN NOW »

-Dave

Handling Blank Values

2024-10-02T11:14:00-04:00

Fellow reader and longtime trader Justin Flynn wrote me recently (shared with permission):

Is there an option of including stocks that have no data showing up on your Top List scans? For example, let's say I want to filter out on my gap scan all tickers over 500m in market cap. Well if I do that and a stock is not reporting a market cap then that stock will not show up on my Top List. Because of that I often times leave out key filters because I dont want to miss those stocks.

This is a common predicament; luckily, a convenient and powerful way to handle this in Trade-Ideas is to use a Custom Formula.

Here's how to set it up. In your account, go to Tools, then Formula Editor. That will bring up the Custom Formula editor.

Add a new Custom Formula with the following code:

[MCap] ?? -1

The ?? operator will use the normal value for Market Cap if it exists, but if it's null it will use the value on the right side of the operator, in this case -1.

Here's a screenshot showing the custom formula:

This ensures that your custom filter for Market Cap will always have a value and you can use it in your filters as you would any other filter.

Notice I used the label Market Cap with default -1 for the Description field. This ends up in the header anywhere I use this filter and serves as a descriptive reminder of the exact behavior.

Here's a screenshot of a Top List I just created to demonstrate this concept. Notice MSTY has a blank for the Market Cap field but shows -1 for the custom formula I created.

Of course, this has uses beyond just Market Cap. There are plenty of instances where this comes in quite handy.

Are there other cases where you use this?

FYI, for the developer types on the list, the ?? operator is also known as the null-coalescing operator and is supported in any modern programming language. More info here.

Keeping Track of Your Trading Ideas

2024-09-30T20:00:00-04:00

In this week’s Line Your Own Pockets episode, we discuss keeping track of trading ideas.

Traders must have a regular flow of new ideas for strategies and ways to improve existing ones.

Michael and I discussed our systems for tracking trading ideas and organizing them.

LISTEN NOW »

-Dave

Win Rate

2024-09-25T10:11:00-04:00

Think of the strategy you're trading now.

Is it in a drawdown?

Is it crushing it?

Either way, if you're like almost every trader I've talked to, there's almost certainly a way to improve it.

Probably multiple ways.

Of all those ways to make it better...

...none of the gains will be from focusing on the win rate.

A Process for Generating Ideas

2024-09-23T20:00:00-04:00

In this week’s Line Your Own Pockets episode, the topic is generating ideas for trading strategies.

Great traders aren't born with the ability to develop trading strategies - they create a process for coming up with ideas that they're constantly improving.

Michael and I discussed what that process should look like for you to ensure that your trading business gets better and better over time.

LISTEN NOW »

-Dave

Your Trading Business

2024-09-18T09:12:00-04:00

You're probably aware of the well-known statistic that the majority of small businesses fail within 10 years.

But did you know there's one category with a much higher success rate than your typical business?

Franchises fail at a far lower rate than average.

Why is that?

A franchise, by definition, has systematized the business.

There are dozens of ways to make a hamburger, but there's only one way at McDonald's.

Everyone knows traders fail at a very high rate.

Can you guess the type of traders that fail at a much lower rate than average?

How can you "franchise" your trading business?

To Paper Trade or Not to Paper Trade...

2024-09-16T20:00:00-04:00

In this week’s Line Your Own Pockets episode, we discuss paper trading - a topic where there's surprising disagreement among traders.

Should you paper trade when you first create a system or trade it with really small size?

Even small losses can add up over time, but many traders need to have a little money on the line to stay focused.

We discuss the issues around paper trading and how my thinking has evolved.

LISTEN NOW »

-Dave

Unpack Your Trading Day

2024-09-11T10:31:00-04:00

Think of the last time you took a vacation.

Maybe you drove to the beach or the mountains. You had a great time.

Now think about the end of that trip. You arrive home and park in your driveway.

If you're like me, the last thing you feel like doing is unpacking the car.

But do you know what makes me feel even worse?

Driving around in a half-unpacked car a couple of days later.

A reminder of something I should have done but didn't.

Over the last decade, I've developed a habit that I love.

When I turn off the car in the driveway - before doing anything else - I unpack the car completely.

Everything in its place, dirty laundry in the washer, chargers in their original location, etc. - no exceptions.

A total reset and it feels great - no baggage left to unpack (literally).

Your trading is the same way.

You may have had a great trading day or your worst day in months.

Either way, the last thing you're going to feel like doing is a daily review.

But daily reviews are what turn ok traders... into truly great traders.

Advanced Order Types That Matter

2024-09-09T20:00:00-04:00

In this week's Line Your Own Pockets episode, we build on last week's topic of order types.

There are so many order types available on trading platforms that it can be overwhelming for traders, so they often just use the simple ones that are "good enough."

I give examples of specific situations where non-standard order types are useful and how they can make your trading day less stressful and more systematic.

LISTEN NOW »

-Dave

A Rule to Avoid Follow Up

2024-09-04T10:54:00-04:00

Last week I showed a chart with two equity curves A and B.

(Click on the link to view the full message.)

The two equity curves come from a strategy I'm working with a trader on.

The goal is to get more P&L from this already profitable strategy.

One way to do that is to remove poor trades using a rule.

Curve A represents trades in the system where the value for a certain indicator is above X while curve B represents trades where the value is below X.

Curve A looks so attractive at first glance compared to curve B, so it's tempting to apply this rule to the system.

But I do not recommend this and I asked readers why.

Here are some responses I got.

Garrett Drinon of SMB Capital said, "Because they’re both good and we want more trades and hence more PNL."

Romoi said, "Is it because there are only a few big wins separating the curves? Meaning it could be curve fitting and bringing anomalies?"

Yaping said, "Is it because it is not a steady trend that has a big swing at the beginning and the end of the curve? The middle curves are almost the same between both. For those big swing up, it likely to associate with big swing down some time down the road."

Berker T. said, "I speculate that curve A seems to have some rules specific to trades that occurred on dates corresponding to jumps of the graph. The first 3 jumps are roughly 4 bars in height, and the graphs are roughly 3 bars apart, so probably without considering the first 3 jumps, curve a would be lower than curve b. We have only 3 instances of jumps, so they may be just luck as well. In the future, those jumps may not happen, or worse the jumps may be to the downside."

All of these are great answers.

When I consider a rule to improve a trading strategy, the rule needs to identify a highly predictive split between good trades and bad trades.

When you look at the chart, notice that aside from a handful of days in curve A, both curves are basically the same. (See chart below)

If you took those 4 days out of curve A, curve B would end up even higher than curve A.

If you applied this rule to the strategy, you would be giving up a lot of P&L for no good reason!

Here's the thing...

If you only look at the overall stats (total profit, win rate, profit factor, etc), curve A appears to be better in every way.

This is why it's so important to look at equity curves to understand the full picture, otherwise these profitable details will slip right under your nose.

A Rule To Avoid

2024-08-28T20:00:00-04:00

First, look at the equity curves in this chart.

Would you prefer to trade A or B?

The answer seems obvious, right?

This came from a strategy assessment I'm doing for a trader.

We're looking at making this already profitable strategy even better and considering this rule.

All trades where $FEATURE is above the value $X are in curve A, and everything below $X is in curve B.

It's tempting to look at these curves and say, heck yeah, let's apply this rule and improve the strategy.

But this is NOT a rule I recommend applying.

Can you tell me why?

Reply and let me know if you can spot it.

--Dave

Become Your Own Neutral Observer

2024-08-26T14:00:00-04:00

In this week's Line Your Own Pockets episode, we discussed a simple exercise you can do to identify dozens of ways to improve your trading.

The key is to take a video of your screen during your trading session. Then go back after hours and honestly review what you did.

Pretend you're a neutral observer. I guarantee you'll identify concrete ways to improve.

LISTEN NOW »

--Dave

Lessons Learned

2024-08-21T09:33:00-04:00

Think back to when you first started trading.

You probably had assumptions about trading that you realize now were silly.

In fact, I bet some of those naive thoughts turned out to be 180 degrees wrong.

(This was definitely true for me.)

Now think a year or two into the future.

Which of your current assumptions are going to be completely wrong when you have more perspective?

Motivation for Becoming More Systematic

2024-08-19T18:54:00-04:00

In this week's Line Your Own Pockets episode, Michael and I discussed why getting more systematic with trading is so important.

I shared a story about missing big winning trades and why, frankly, it pissed me off.

As frustrating as it can be, missing out on good trades can be incredibly motivating to get better.

LISTEN NOW »

Did you enjoy this episode? Consider sharing it with a few friends who might find it useful. Thanks!

-Dave

Trades Not Matching Backtest

2024-08-16T09:46:00-04:00

A quant trader came to me recently with an issue.

He was backtesting and optimizing his strategy using Python, but then writing code in TradingView to execute the trades.

His trades in TradingView weren't matching his backtest and he couldn't figure out why.

You often run into thorny situations like this when backtesting, especially when optimizing in one platform and executing trades in another.

Here's the advice I gave which I think applies to trading data issues more generally:

Compare The Most Recent Trades

Find a recent trade where the backtest doesn't match. Starting from recent trades is easier since you save yourself scrolling back in your chart to find the applicable data points. Note the symbol and entry date.

Add Debugging Statements to your Code

In the platform that's easier to work with (in this case it was Python), add plenty of debugging code to log the important bits - OHLC data, volume, any indicator values that apply to your strategy, etc.

Run Backtest on Just The One Symbol with Debugging Enabled

Try to write your debugging statements to a separate file rather than the console. It's easier to examine the data when it's in a text file since there are so many tools you can use to search and parse them. (I mostly use Vim for this purpose, but use grep, findstr, sed, or Python too.)

By running the backtest on just one symbol, you end up with less data to have to sift through.

Dig Into the Nitty Gritty

The devil is in the details in situations like this, so you can't avoid getting your hands dirty. Dive in and figure it out.

You'll often learn something unrelated that will come in handy in unexpected ways in the future.

Traders HAVE to be detail-oriented and while this process usually isn't fun, it's a necessary part of being successful.

The quicker you become comfortable with it the better.

Buying Power

2024-08-15T13:30:00-04:00

What would need to be true for you to trade big enough to use ALL your buying power?

Every single trading day.

You'd need more confidence in your trading system.

True confidence - more than you have now.

Think about what would give you more confidence.

Make a list of things that would inch your confidence forward.

Start knocking things off that list and you'll create the confidence you need.

Line Your Own Pockets Podcast

2024-08-14T10:56:00-04:00

I'm excited to announce that I've started a podcast!

It's called Line Your Own Pockets and it's for traders who are sick and tired of all the trading gurus in this industry who are great at marketing and even better at pretending to be traders.

If you realize that the only way to be successful is to take responsibility for your own trading, then this podcast is for you.

If you're still looking for the trading holy grail or want to be spoonfed someone else's stock picks, then you're going to hate this podcast.

This is the podcast I wish had existed 15 years ago when I started backtesting and creating my own trading strategies.

For just a few minutes of your time each week, you'll learn the dos and don'ts of creating and trading strategies that have edge.

I've partnered with Michael Nauss of Stats Edge Trading to be my co-host.

Check it out! There are links to subscribe on Spotify, Apple Podcasts, and wherever you listen.

Line Your Own Pockets

Use The Best Tools For Your Trading

2024-08-08T13:30:00-04:00

My wife and I love going to Boone, NC for long weekends of running, riding, and relaxing which we've done for years.

It's at least 10 degrees cooler after you make the ascent from Wilkesboro on 421.

Time and time again we've made the trek up that climb.

Last year it dawned on me - if I find a decent route, Joan could drop me off in Wilkesboro and I could ride my bike the rest of the way - up the mountain - and meet her in Boone.

I asked my cycling friends if they knew of such a route and Fred responded with one that he heard was good, but had never actually ridden.

I studied the route closely - there were sections of gravel - but it looked like it would work.

Although I had never been on those back roads before - and didn't know anyone who had - I decided to take a shot.

I double-checked the route, then I loaded it onto my cycling computer.

Joan dropped me off at Kerr Scott Lake in Wilkesboro and I started my point-to-point ride.

It starts on a country road dotted with churches that had signs out front with slogans that you can't decide if they hit the mark exactly or miss it entirely. (e.g. one read: "If you think it's hot now, hell is a lot hotter!")

The directions were low-stress - I could simply glance down at my computer and see how far until the next turn.

The ride was brutal (in a good way!) ending with a monster climb in the last 5 miles.

I met Joan in Boone and our vacation weekend began.

Here's the thing - the first time I did this ride there was significant risk.

It was point-to-point and I had never done the route and knew nobody who had - if the directions were wrong or some part of it was unpassable or if I got lost, I would have been screwed.

Because I had a computer that could do turn-by-turn directions and planned the route thoroughly ahead of time, I could enjoy reading all those church signs along the way.

Your trading is no different.

Are there tools YOU can use to make your trading smoother and less stressful?

It might make sense to pinch pennies in other areas of your life, but not trading.

The Eye-Opening Way to Eliminate Trading Mistakes

2024-08-01T13:30:00-04:00

For the second trading day in a row, I had missed winning trades I should have taken.

Somehow I was just a bit too late to notice the setup in time... again.

With any trading system, the big winning trades make the system profitable.

The first day this happened I thought, "No big deal. This system has plenty of profitable trades - I'll get most of them."

After reviewing my trades after the second day it happened, it became clear this leak was not acceptable. I had to plug it!

So for the next few days, I recorded my screen while I traded.

After each market close, I watched the video of my session from that day.

What did I learn?

My trading routine wasn't nearly as systematic as I thought it was.

My chart layout could be improved.

The way I calculated position size for each trade took far too much time.

I was missing trades because there was all sorts of sloppiness in my routine I wasn't even aware of.

So here's a challenge for you.

For the next day or two, record your trading session. Then go back as a neutral observer and review it after the close.

I guarantee you will find multiple ways to get better.

Concrete changes you can make immediately.

Try this and let me know what you uncover.

How To Trade Half Days With Ease

2024-07-25T10:54:00-04:00

Years ago when I created a program to enter my orders, it made trading so much easier.

How hard can it be to enter an order manually? It turns out there are so many options to include on an order.

It takes way more time than you think, not to mention the mistakes that you inevitably make.

One of the biggest benefits was automatically including a time stop with my exit orders.

Several of my systems hold for the entire trading day, so I include an order that exits the position automatically just before the market closes at, say, 3:55pm ET.

My initial logic was to store a DateTime object and use the time part of it to determine the time of day.

It worked well - until the first half day, like last week before July 4th.

Since the market closes at 1:00pm ET on half days, I would be stuck in my positions well after the close.

This is not just annoying - it could end up being disastrous!

I quickly realized there's a far better way to implement this so you don't get caught off guard on half days.

Instead of storing the variable as a DateTime or a time of day, use an integer for the number of minutes before the market close.

Once a year check the list of half days for the upcoming year.

Store that list in a file or database that your code can check when computing the exit time to use in your orders.

If it's a half day, the market close is 1pm, otherwise 4pm.

In your code, subtract your number of minutes from the market close of the current day.

This way your code will work gracefully on regular trading days and half days.

And you will no longer panic at 1pm when you realize you've forgotten that it's a half day - something that's happened to me plenty of times. :-)

Often The Most Profitable Thing You Can Do Is...

2024-07-18T13:30:00-04:00

Wait.

And yet it's the hardest thing to do.

As humans, we're hardwired to take action - any action.

To do a task so you can check something off a to-do list.

It feels good to complete a task.

You've moved the ball forward a little.

But in trading, you very often get paid to NOT do anything.

Wait for a real setup rather than squinting hard enough to force one now.

Wait for an already profitable trade to become even more profitable.

Wait so you can collect more data to fully understand if your strategy has edge.

Wait to gain more experience before increasing your position size in a new strategy.

Wait just to ponder an idea with no deadline in mind.

Doing nothing IS an action.

Often the most profitable one.

My wife sent me a playlist to listen to on a recent trip.

Buried in it was this song which I couldn't get enough of - I must have played it on repeat for an hour.

Give it a listen to be inspired to... do nothing.

Hold On by Alabama Shakes

The Simple Truth About Becoming Profitable

2024-07-11T13:30:00-04:00

Here's a question I get repeatedly in some form from new traders.

I don't want to reinvent the wheel - can you just give me a strategy that's working?

It's a surefire signal that the trader hasn't yet internalized the mindset required to be successful.

Traders who become successful realize at some point along the way the fact they felt the urge to ask that question was literally what was holding them back.

That's the turning point - when they finally give up relying on someone else and build a process for creating their own trading edges.

And yet I still see traders looking for the smartest person in the class to cheat off of and get the right answers for the exam.

That might have worked for them in high school but it will get you nowhere in the stock market.

I recently came across more evidence that this is true.

A friend of mine sent me an academic paper that should convince you beyond any doubt of your path to success.

The paper is titled "Finfluencers".

Researchers from Berkeley and LSU examined financial tweets from people with various numbers of followers.

They measured the performance of a hypothetical portfolio that followed the advice given in social media from various influencers to determine which ones had real edge and which ones were spouting nonsense.

The researchers categorized the influencers as "skilled," "unskilled," or "antiskilled."

Skilled meaning their recommendations had some amount of trading edge, unskilled meaning they had no edge, and the most interesting: "antiskilled" meaning they have "negative edge" - i.e. you'd be better off doing the opposite of what they recommend.

You might have guessed that skill is pretty rare on social media.

But you probably didn't guess the most important conclusion from the paper.

The more followers someone has on social media, the more likely they are to be antiskilled.

Think about that.

The more successful someone is on Twitter, the higher the likelihood they're spewing nonsense.

And importantly it's not just random nonsense, but there's a slight edge in literally doing the opposite of what they recommend.

When you're ready to start lining your own pockets instead of some Ferarri-driving trading guru with antiskill, reply and let me know.

What Re-Reading Great Fiction Can Teach You About Trading

2024-07-04T13:30:00-04:00

My wife, Joan (who's well-known enough to have a Wikipedia page), is re-reading some of her favorite fiction books with our daughter, who is developing a taste for great literature.

Joan has always loved great fiction to her core. Everything else is a distant second (including me, pretty sure!)

So she's thrilled that our math-loving daughter has taken up this interest they can share.

Joan's absolute favorite book is Franny and Zooey by J.D. Salinger, one she consistently recommends.

I've read it once and I agree it's excellent.

It's been several years since she's read it, but she's rereading it now as my daughter is reading it for the first time.

Joan has read this book many, many times.

So many times you would think she knows the book inside and out.

And yet, as she's reading it now for the umpteenth time, she noticed an incredible detail she'd overlooked every time before.

She excitedly told me this is now her favorite detail in the entire book.

A brand new discovery in her favorite book she's read countless times.

(If you're interested in the details, hit reply and I'll share.)

What does this have to do with trading?

The same aha moment of discovery can happen when you look at a familiar strategy with fresh eyes.

I recently took a deep dive into one of the trading strategies I've traded daily for almost a decade - something I've done many times before.

But this time I found something I hadn't noticed before.

A new feature that has predictive power that I can apply to make the strategy better.

These seemingly random breakthroughs can happen at any time, as long as you regularly put yourself in a position to notice them.

Why I Avoid Overall Market Filters in Strategies

2024-06-27T13:30:00-04:00

When you're creating trading strategies, most traders eventually consider trying to improve the system's performance by adding an overall market rule.

For example, you have a system that trades stocks gapping up long and stocks gapping down short.

Instead of taking all the trades in the system, you consider only taking the long trades when the overall market is positive or only taking the short trades when the overall market is negative as determined by some metric.

(In Trade-Ideas, there are several of these overall market filters available. For example, S&P Change in 30 Minutes, S&P Change Today, NASDAQ Change Today, etc. See those links for the full details about how they work.)

While this might seem like a perfectly reasonable approach, I think it's a mistake to use these filters that measure the overall market in your trading strategy.

Here's why.

When you design a trading system, you identify an event as the impetus for your trading signal.

This event needs to be significant, strong, and unusual - otherwise, it's just random noise.

For most trading systems, the overall market behavior at the time of your trade should be irrelevant.

When you consider applying a rule based on the overall market, on some level you are admitting that your system's trading signal isn't as strong as it should be and that it "needs help" from a largely unrelated factor to function sufficiently.

When you think about applying an overall market filter, it's usually a sign that you need to find more significance in the trading signal itself.

But even beyond that, there's another important reason I avoid overall market filters.

Let's say you can apply an overall market filter that significantly improves the performance of your trading system.

By definition, this improvement will come from increasing the profit per trade and reducing the number of trades in your system.

In other words, you'll remove some relatively poor trades from your system when the overall market isn't favorable.

Unlike a normal trading rule, you'll end up with large windows of time where your system isn't making trades at all.

For example, let's say your rule is to skip short trades in your system when the SPY is above its 50-day moving average.

One look at a daily chart of the SPY and you'll see there will be weeks or even longer when your system makes no trades, just because of this one rule you applied.

This is a terrible tradeoff to me.

I want my trading systems to trade frequently and regularly, without large arbitrary windows of time when they're effectively disabled.

Instead of considering a market filter, use your effort to identify more power in your trading signal and your system will be more robust.

What I've Learned from Creating Strategies with AI

2024-06-20T13:30:00-04:00

I currently trade a variety of strategies, many of which use machine learning and AI as a significant component.

Some of the strategies were built using AI while others include AI directly in the execution of the trades.

In the decade or so of using these techniques, I've learned valuable lessons about how best to use AI in trading.

What surprised me, however, was how much the lessons apply to creating profitable trading strategies in general.

In this post, I'll share some of the lessons I've learned from creating these strategies you can apply to your trading.

Feature Selection is Everything

Feature selection, or determining which indicators should be included in your model, is the most important aspect of creating a successful strategy.

Most of your energy will be spent figuring out which indicators your model is allowed to consider.

The features you leave out are as important as the ones you include.

Features Should Be Minimally Correlated

When you add a feature to your model, make sure there is minimal correlation with another feature already in the model.

The model will get worse if you include features that are highly correlated with other features.

For example, let's say you include a feature for Distance from the 50 Day Moving Average which seems to improve your model.

Adding a feature for Distance from the 200 Day Moving Average will likely worsen the model. Even if it seems it's capturing something different than the 50 day moving average, those features will be statistically strongly correlated.

Having Too Many Trading Rules Is Terrible

When you add trading rules, you always risk significantly deteriorating the strategy.

This is how curve fitting occurs - adding a trading rule that doesn't tell a coherent story.

When deciding whether to add a trading rule to your strategy, pretend you have to justify it to an experienced and skeptical trader.

Does the trading rule truly make sense?

Even if it improves the strategy, does it pass the sniff test?

In my experience, most traders are too quick to add trading rules to their strategy that don't tell a coherent story.

As a result, their trading strategies are far less robust than they could be.

Add a Random Variable as a Control

One way to get better at creating strategies is a technique I accidentally stumbled upon.

Several years ago I was analyzing a backtest and decided to add a rule based on an indicator that seemed to improve the strategy significantly.

After trading the strategy for a while and reconciling my live results with the backtest, I realized that there was an error in the way I was collecting the data that this particular rule was based on.

As a result of this bug, the data for this indicator was just random noise.

And yet, when I originally examined the data it seemed to have a strong effect! I was fooled.

I realized, though, that purposefully adding a random variable to your backtest is an excellent quality check for your process.

If in the process of analyzing your data, your random variable starts appearing as being "important", then you know you're likely "torturing your data" too much.

A random variable has no predictive value to your strategy, so if it appears in your analysis it is a huge red flag.

Do you use AI in your trading or have you made attempts that didn't seem to work? Reach out and let me know - I'm happy to share notes and point you in the right direction.

Are Your Trading Charts Costing You Profits?

2024-06-13T13:30:00-04:00

Think about your trading performance over the last year. Now imagine those results with all the trading mistakes you made removed.

Your trading performance would be dramatically better if you could eliminate those mistakes.

Most traders set up their charts in such a way that guarantees they'll make the same costly errors over and over.

Adding too many indicators to your chart isn't just sloppy - it's costing you money.

I'll describe a simple framework you can use to make sure your charts are set up to make your trading profitable.

First, let's talk about driving a car.

When I turned 16, I bought my family's Mazda 626. It was a decent starter car and I loved the freedom that came with it.

Two main gauges on the dashboard took up most of the visible area.

One was a tachometer - a gauge that measures the rotation speed of the engine in revolutions per minute (RPM).

The other was a speedometer - a gauge that measures the current speed of the vehicle.

As a teenager, I remember thinking these gauges were pretty cool - they gave the driver's seat the feel of an airplane cockpit.

But over time you realize that one of these gauges is far more valuable than the other.

And for a very simple reason.

Although the tachometer is fun to look at, you make zero driving decisions based on its reading.

Compare that to the speedometer which you constantly check and adjust your driving to make sure you're not speeding.

(Dad - if you're reading this, rest assured that I never exceeded the posted speed limit - not even a single time!)

The fact that these gauges took up the same amount of space on the dashboard is insane.

Now look at your charts. How many "tachometers" do you have on them?

Any indicator that doesn't directly drive pre-planned trading decisions should be removed.

Why are they there other than to look cool?

If they can't be tied to a specific trading rule, then not only is it taking up space needlessly, but it's introducing an opportunity for you to make a trading mistake.

Make sure any indicators you have on your chart are speedometers, not tachometers.

When you're ready to take your trading to the next level, consider my Trading Success Roadmap. We'll dive into your trading to find all the tachometers and replace them with speedometers to make your trading business efficient and self-improving over time.

How To Make Your Strategy More Predictive

2024-06-06T13:30:00-04:00

Time and time again I see traders give up on a perfectly good trading strategy too soon because it "doesn't work anymore" or they aren't able to see a rule they can apply to make the strategy significantly more profitable.

It pains me to see a trader abandon strategies that have so much potential.

In this post, I'll show you one way to get more edge out of a trading strategy and gain more insight that you can apply to other strategies as well.

One common situation when developing strategies is ending up with too few trades in a backtest to draw significant conclusions from. The more trades that you start with in a backtest, the better chance you'll end up with a significant number of profitable trades after you optimize it.

Here's a technique I've used to add more trades to a backtest so I can be significantly more confident in the strategy than otherwise.

Let's say you're testing a strategy that looks for stocks gapping up over 5% and going long, but you're not finding enough trades to draw confident conclusions.

Most traders throw up their hands and give up, but here's a way to double the number of trades in your backtest.

Instead of looking at the long side only, combine the backtest with the equivalent strategy on the short side. In our example, that would mean adding stocks that are gapping down more than -5% and going short.

One problem to address is "normalizing" the data so you can analyze these separate trades together. For example, when you look at the gap, you'll have positive numbers for the longs and negative numbers for the shorts.

That makes it difficult to determine the best threshold to use for the gap percent.

To solve this, add another column for the absolute value of the gap. That value will be normalized across long and short trades allowing you to properly analyze the right threshold to use.

You've now effectively doubled the number of trades in your backtest giving you more data to examine - a big win.

What about a filter that a simple absolute value function won't work for?

Take one of my favorite filters to use: position in range.

It takes the high and low of some range (say, yesterday's trading range) and gives you a number corresponding to the trade's entry price position within that range.

For longs, you might be looking for trades in the top part of the range (values of around 100) but for shorts you might be looking for trades in the bottom part of the range (values of around 0).

A simple absolute value function won't work here.

For this situation, I create a column called "directional position in range". For longs, the value is equivalent to the normal position in range. But for shorts, the values are reversed by simply taking the value and subtracting it from 100. For example, a value of 1 for position in range for a short (meaning it was near the low of the range) becomes 99 (100 - 1).

This new directional position in range column allows me to treat long and short trades equivalently for the purposes of optimizing the strategy.

This simple technique can often be the difference between a dead-end because of limited data and a profitable insight that can be applied to a profitable strategy.

Humility in Trading Goes a Long Way

2024-05-30T13:30:00-04:00

Here's my favorite image from my free email course on Backtesting:

It's to reinforce the fact that most traders think it's time to start ringing the register as soon as their backtest is complete.

Nothing could be further from the truth.

It's easy to get overconfident when you see an equity curve like this (from one of my students - keep reading to learn more)

This step of going from a theoretical backtest to real-time trading is significant and you'll often find flaws or incorrect assumptions you made in your strategy.

You eventually WILL learn these lessons.

And you have two options for doing so.

One way to learn them is to trade with real money - in which case you'll pay for those lessons with "tuition." (Sometimes a LOT of tuition)

The better way is to learn those lessons for free - by paper trading your strategy first.

A little bit of humility goes a long way here.

Be skeptical - make your strategy prove itself to you.

Because traders so often overlook it, I include an entire section in the Trading Success Roadmap on this step.

The traders who have gone through the roadmap with me are fully aware of the trading pitfalls that can occur and have a plan for dealing with them ahead of time.

One trader I'm working with now, named Finith J., is incredibly patient (that's Finith on the left and me on the right):

He's developed two solid strategies that he's been paper trading (one is represented by the equity curve above).

He's learning all those pitfalls of trading now, so by the time he starts trading live he will have a huge head start.

A big part of the reason for his patience is his background in chemistry (he has a PhD).

Although chemistry and trading are separate fields, it turns out there are a lot of overlapping concepts that make him well-suited for trading.

He's getting ready to go live with these strategies now, but the best part is he now has a generic framework for testing any trading idea and turning it into a profitable trading strategy.

Have the patience of Finith!

What a Pushup Contest Can Teach You About Trading

2024-05-23T13:30:00-04:00

Some of you might know I'm a runner and cyclist (see P.S. below for a Strava link). This past weekend I ran a local trail race with friends.

After the race, the organizers held a pushup contest.

I wasn't planning to participate, but when several of my friends were doing it, I decided to jump in as well. There were several strong looking guys in the contest, so my expectations were low.

I was into upper body strength several years ago when I tried to achieve 50 pullups in a row (I did 38), but that's been ages.

This year, however, I decided to take a different approach. Instead of setting a lofty goal like doing 50 pullups, I set out to do a small amount of upper body exercises every single day.

For 6 months now, I've done 20-25 pushups and an ab exercise every day. There have been days I've missed (4 or 5 probably), but I don't sweat it - as long as I "make it up" by doing double the following day, my average is intact.

There is no complex workout routine here: after a week the pushups aren't hard and it only takes a couple of minutes to complete. The only real challenging part is doing it EVERY DAY.

Back to the contest last Saturday.

Much to the surprise of all my friends, all the burly participants, and most of all me - I won the contest.

I was shocked, but at that moment I realized my simple, daily routine provided a much broader foundation of strength than I imagined.

The same concept applies to your trading.

This is the first thing I help traders implement - a simple, efficient, trading review every single trading day.

It's not hard and doesn't take much time, but it works because you do it regularly.

But once you get this process in place, it creates an upward spiral where it's almost impossible not to significantly improve your trading.

Here's a photo of the pushup contest that my friend took. That's me on the right in the jacket (it was pouring down rain):

P.S. Here's my Strava profile if you're interested in following me there. If you do, reply and let me know and I'll follow you back.

You're Measuring Trading Performance Wrong

2024-05-16T13:30:00-04:00

In today's newsletter, I'll address the most common mindset that traders have and why that mindset is the exact thing holding them back.

When the market closes and you're done making trades, how you reflect on your trading day is a crucial part of continuously improving as a trader.

Most traders measure their success by simply glancing at their P&L in their trading platform. If they made money - great! If they lost money - bad!

I'm not denying that the goal of trading ultimately is to make money, but using P&L every day as a measure of success is the wrong mindset to have.

Here's why.

Your daily P&L number hides many of the details of your performance that will help you improve. Only reflecting on the overall P&L causes you to miss all those crucial details.

Here's a great example. A few days ago I ended the trading day with an above average overall loss.

And yet I was as optimistic about my trading as I'd been in months.

How could that be?

Well, one of my most mature trading strategies had a losing day. Because that strategy has performed so well for so long now, I trade it with a lot of size.

A modest loss for that strategy is significant in comparison to other strategies I haven't sized up that large yet.

So why was I so optimistic at the end of that day?

A new trading strategy I just started putting to work had an excellent day even though the size I'm using with it was small.

It had started proving itself in the real world. I had evidence that I'd be able to scale that strategy up and soon THAT would be a strategy contributing significantly to my daily P&L.

If I had looked at P&L alone, I would have missed this optimistic part of the trading day.

If P&L isn't a great measure, what is?

The question you should be asking yourself at the end of the trading day:

Did I follow my rules?

If you did, then the day was a success and you should be pleased no matter what your P&L happened to be.

If you didn't follow your rules, then you've got some work to do.

This is a far better mindset to have for the following reasons:

It forces you to clearly define what your rules are
It allows you to evaluate yourself in terms of what will impact your long term success
It creates optimism where there would otherwise be negativity

You should be shooting for profitable months, years, and decades.

This is the mindset that will bring those about, not whether any particular day is profitable.

Try this in your trading day reflection and let me know what you think.

Avoid This Huge Mistake When Backtesting

2024-05-09T13:30:00-04:00

In today's newsletter, I want to address the biggest mistake I see traders make when they start backtesting.

Backtesting is a superpower - the sooner you start backtesting the sooner you'll start realizing the benefits.

Backtesting is a lot of work, but when done properly the payoff is immense.

The problem is most traders start backtesting in a way that still requires all that effort, but minimizes the actual benefits.

If you're going to put in the effort, it's important to do it in a way that will maximize the benefits, otherwise all your work will be wasted.

Most traders begin with an idea for a strategy they apply to a single symbol, usually a well-known market index like SPY or QQQ.

Creating a strategy that trades a single symbol like this can work, but it's vastly inferior to a strategy designed to trade any stock.

When you backtest using a single symbol, you're competing against every trader with the ability to simply look at a chart. That's almost every trader on the planet.

But when you start with a strategy designed to trade any stock in the market, the pool of traders you're competing against drops dramatically.

It's a hard technical problem to create software that backtests all of the thousands of symbols that actively trade each day.

Creating software to backtest a single symbol is trivial in comparison.

That's why you see so much software in the industry that claims to "backtest", but only a small handful can tackle the more lucrative problem of backtesting the entire market.

Why is it so much better to create a strategy for the entire market? Lots of reasons:

There are far more opportunities - it might take a decade to accumulate enough profitable trades in a single symbol to be worth trading
More opportunities give you more flexibility to improve your strategy
The types of strategies that work are easier to come by when applied to the entire market
Because of the technical issues of scanning the entire market, your pool of competing traders is much smaller
Easier to create a statistically valid strategy you can have confidence in
Your strategies will have more "staying power" - that is, they'll deteriorate less quickly

When Is A Strategy Good Enough To Trade?

2024-05-02T13:30:00-04:00

(Note: this post is adapted from the Trading Success Roadmap.)

"What metric should I look at to determine if my trading strategy is good enough to start trading it?"

I get this question a lot.

Many traders go overboard here by looking at all sorts of fancy (i.e. complicated) metrics and trying to find the perfect one. It's easy to fall into analysis paralysis at this stage by obsessing over this metric or that.

The important thing to remember is any aggregate metric, by definition, hides many of the underlying details of a strategy.

When comparing trading strategies, I like to keep it simple. Here are the metrics I'll look at (in no particular order):

Profit factor (sum of winning profit / -(sum of losing profit))
Win rate (number of winning trades / number of total trades * 100)
Average Profit per Trade (total profit / number of trades)
Total Profit
Total number of trades and specifically trades per day

The Most Important "Metric"

By far the most important “metric” that I look at is a visual representation of the equity curve. This is a simple line graph with the date on the X-axis and the cumulative profit on the Y-axis. Here’s an example where I compared three different systems in one simple graph:

Notice all the details that you can see that are hidden when you only look at a single metric like Profit Factor.

You can see the drawdowns and when they occurred.

You can see the large spikes up and down.

In short, you can see what it will actually feel like to trade the strategy.

There is no substitute for examining the equity curve.

A strategy with a smooth equity curve will have different ways to scale up in size over time.

The Smart Way to Avoid Bad Ticks

2024-04-25T13:30:00-04:00

In today's post, I'll show you how to avoid bad ticks so you'll never have to worry about them again.

Friend of the list Maoxian sent me a DM the other morning:

Bad ticks this morning at 8am-ish. Lots of erroneous ticks in Trade-Ideas around 8am in HUBC, CADL, and AG.

Maoxian

Many traders just shrug their shoulders and live with them, believing that bad ticks are just part of the trading game.

But when you have trades triggered due to the bad tick, that's a problem because even if you recognize the situation and exit the trade quickly there are still fees, slippage, and unnecessary risk that can easily add up.

Instead of just living with them, there's a nice way to avoid these entirely using Trade-Ideas.

Take this example in HUBC that Maoxian pointed out to me. Notice the suspicious, wide-ranging bars that start appearing right at 8:00am:

How do you know these are bad ticks and not legitimate trades? Look at Time and Sales:

Notice how the last trade is so far from the current bid/ask price at the time. In this case, the last was 1.53 but the bid was 1.35 and the ask was 1.37.

If you had a limit order to sell at 1.50 at this time, it would NOT have been filled.

To set up Trade-Ideas to ignore these bad ticks, go to the list of filters here and search for Distance from Inside Market.

That filter allows you to control how far the last price can be from the bid/ask (that is, the "inside market").

That filter can be applied to any alert window.

Here's a screenshot of an alert window where I added the Distance from Inside Market filter as a column to show the value for the alerts that fired due to the bad ticks.

Add a max value for the Distance from Inside Market to filter out the alerts caused by these bad ticks.

If you're looking to get started with Trade-Ideas, here's a 25% discount you can use. When you check out use promo code TRADESMART25 to get the discount.

Think Position Sizing is Boring? Check This Out!

2024-04-18T13:30:00-04:00

"My strategy worked well for a while, but then one trade wiped out all my gains."

Some form of the above statement is probably the most common frustration I see among traders who come to me for help.

When you're trading a strategy it is incredibly frustrating to have success for a while, but then have it all evaporate in just a day or two.

The most common reaction to this is to blame the strategy and move on to another idea and then the cycle continues.

But in most cases, the strategy is not the problem.

The problem is inconsistent position sizing.

When you don't have a solid method for deciding how many shares to use for a trade, you end up with a big problem.

You use a relatively small number of shares for the winning trades and a relatively large share size for the losing trades.

You're almost mathematically guaranteed to end up in the "one trade eventually wiped out all my profits" situation.

A Real Example

I'm getting ready to go live with a new trading strategy and I'm finalizing the rule set using my standard process.

The first thing I do when going from an idea to an actual trading strategy is to determine the best position sizing approach.

Here's the before and after equity curve for the same set of trades. (image below)

The blue line represents the strategy's equity curve using a constant number of shares for each trade.

The red line is the same strategy with a thoughtful position sizing approach applied to it.

Same account size, same average money used per trade, you're just applying a coherent position sizing approach.

You can see the difference!

Imagine trading the strategy using the naive approach of the blue line - you get long periods of frustrating drawdowns.

Yes, you end up with a profit but it's a wild ride.

Compare that to the smoothness of the red line.

The drawdowns aren't eliminated, but they're shallower and shorter.

With this approach, the strategy will be far easier to trade and scale up over time.

It's not that the strategy is bad, it's that a poor position-sizing approach turns a perfectly good trading strategy into a loser.

You're Closer to Profitability Than You Think

2024-04-11T13:30:00-04:00

If there's one thing in common with all the traders I've worked with, it's this:

They were closer to consistent profitability than they realized.

Sometimes they've had some success but then a single trade wipes out a month of profits.

Sometimes their trading strategy just seems to suddenly stop working.

Sometimes they've given up on a perfectly good strategy that has edge that they didn't realize.

Sometimes they're deviating from their strategy rules during the trading day.

Sometimes they're not getting fills in what would be their strategy's most profitable trades.

There are lots of different reasons traders underperform their true potential.

The answer is never a dramatic overhaul of what they're doing.

Because that's not what's required.

Why?

Because you're closer than you think.

Two Identical Trades - Can You Tell Which One Is Better?

2024-04-04T13:30:00-04:00

(Note: this post is adapted from the Trading Success Roadmap product I'll be officially offering soon.)

A common mistake I see even experienced traders make is poor position sizing.

Sizing your positions thoughtfully is fundamental to any trading strategy. A poor plan for position sizing can turn an otherwise profitable trading strategy into a loser.

Take the following two hypothetical trades:

A) You go long 100 shares of AAPL at $186 with a stop price of $176. You exit with a profit at $190.
B) You go long 100 shares of AAPL at $186 with a stop price of $185. You exit with a profit at $190.

Notice how in both scenarios the outcomes are identical:

The same entry price
The same exit price
The same number of shares
The same profit of $400

But look closer and notice the important difference.

In A) your initial stop price was $10 away - if the stock went against you and hit the stop you would have lost $1000.

In B), however, your initial stop price was $1 away. In that scenario, if the stock went against you and hit the stop it would have been a $100 loss.

If you only evaluate the success of the trade based on profit, these trades look identical, but they are fundamentally different trades!

In A) you risked $1000 to make $400
In B) you risked $100 to make $400

B) was a far better trade even though the outcome was the same as A).

If you've ever had a big losing trade that wipes out the profits of several winning trades, there's a good chance you aren't sizing your positions properly.

The Trading Success Roadmap gives you a detailed blueprint for sizing your positions based on your risk.

Before I start trading any strategy, I have a required checklist of things to do to give the strategy the best chance for long-term success.

Proper position sizing is at the top of that list.

My Unique Backtesting Process

2024-03-28T13:30:00-04:00

When I first started backtesting, I set out to improve upon a strategy I was already trading manually.

(Spoiler alert - I was able to improve it immediately.)

That worked well, but I quickly realized how inefficient that process was.

I was essentially backtesting trying to find a particular tree in a large forest.

I eventually found the tree I was looking for, but it dawned on me that I was spending a lot of effort ignoring equally good and even better trees throughout the forest.

I realized that I needed to change my process to create profitable strategies from a backtesting first approach.

After a lot of trial and error, I ended up with an efficient process I call: Backtest Wide but Trade Narrow.

This is the opposite of what most traders do when they backtest.

When I have an idea for a strategy, I create a backtest that finds every instance of the signal with very little filtering.

I end up with a backtest with sometimes tens of thousands of trades in it.

When you try to apply rules to your strategy at this point in the backtest, it's cumbersome. You make uneducated guesses. Stabs in the dark.

The smart way to apply rules is to take your trades list and use Excel or some statistical software to determine the rules.

So my backtest becomes very easy to generate.

The valuable part of my approach is determining what subset of the tens of thousands of trades I'll end up trading.

If you're familiar with SQL, imagine querying a large database table without an index applied.

Your query will eventually return results, but it could take hours or even days to return. Heck if the table is large enough it might NEVER return - your query might be effectively impossible to run.

But, of course, if you apply the right index to the database table your query will run INSTANTLY.

It's the same with my Backtest Wide but Trade Narrow approach to creating trading strategies.

To learn more, sign up for my newsletter below where I teach the process of creating your own profitable trading strategies. 👇

Using Excel to Improve Your Trading Strategy

2024-03-21T13:30:00-04:00

One of the most valuable things I do with traders I coach is give them simple rules to eliminate losing trades from their existing trading strategy.

This is typically the quickest and easiest way to improve a strategy without curve fitting.

Here's an example of a rule I gave to a trader I've been coaching for a few months. (The actual filter and value are anonymized, but the equity curves are real.)

The green line represents the equity curve of the trading system after the rule is applied.

The red line represents the equity curve of the trades that would be excluded.

This rule got rid of 30% of the trades in the strategy and increased the profit per trade in the system by 50% - a huge improvement.

When I deliver a rule like this, I always encourage the trader to independently verify it and not just blindly take my word for it.

There's a convenient way to verify it using Excel, so I thought I'd create a video showing the process.

If you're not aware of the auto-filter feature in Excel, it's worth watching and working into your backtesting process - it's a huge time saver.

The Biggest Time Saver in Developing Trading Strategies

2024-03-14T13:30:00-04:00

First, a story about my history as a coder.

When I began writing code in the late 90s, I used the default text editor in Windows: Notepad.exe.

At some point, one of my managers at the time told me how powerful a different text editing software called Vi was.

If you've ever used Vi (as I'm doing now to write this post) you immediately understand two things:

The learning curve is steep
Once you learn it, Vi is an incredibly powerful and efficient text editor

I took my manager's advice, bought a book, and became obsessed with learning the Vi editor and incorporating it into my workflow.

I knew it would be hard to master it, but what happened almost immediately took me by surprise.

Even well before becoming even modestly proficient with Vi, instantly my productivity increased.

Just learning the very basics - maybe half of a percent of what Vi can do - made my process of writing code way faster.

I thought I was pretty fast before, but I had no idea how much faster I could go until I started.

I've since mastered Vi (if you can ever REALLY master it). It's the first piece of software I install on any new machine.

I often think about those early productivity gains and the compounding that's happened since then.

It's not an exaggeration that my career went at least 33% faster as a result of that decision - maybe even more.

So what does this have to do with your trading strategy?

Backtesting is to your trading as Vi was to my coding productivity.

Backtesting has a steep learning curve, just like Vi.

Backtesting is incredibly powerful once you learn it, just like Vi.

But here's the underappreciated fact about backtesting - just like Vi, you'll immediately start realizing the benefits by just learning the basics.

I was reminded of this just a few days ago when a reader emailed me out of the blue saying he started backtesting after reading one of my articles.

In less than a week he gained an insight from it that took his trading in a completely different and more productive direction!

Imagine being able to make progress at a rate 50% faster than what you're doing now.

There's no telling what type of trader you'll be in just a few months. Now imagine compounding those gains over a few YEARS.

What's stopping you?

I Threw Away My First Profitable Strategy - Here's Why

2024-03-07T14:30:00-05:00

The first strategy I traded was a gap strategy and a continuation play.

Gap up? Look to get long. Gap down? Look to get short.

It was straightforward: easy to follow and manually trade when I had limited time to dedicate to trading.

Luckily, it worked and I was well on my way.

So why did I want to change things? If it ain't broke, don't fix it, right?

As I mentioned last week, I had a strong sense that some of the rules were arbitrary.

I didn't think they were wrong, but I thought a data-driven approach would point me to better values.

To get started, I took one of my recent gap trades and wrote code to backtest the strategy for that single symbol.

This is a great way to start since backtesting the entire market from the beginning is more difficult and time-consuming.

That recent trade was fresh in my mind - it wasn't theoretical since I had just traded it live.

Once I got the backtest working so it would match my single recent trade, then I ran it across the entire market.

I made some adjustments, but finally got it closely mimicking what I was doing with my manual strategy.

That was great but the next step was a game-changer.

As I traded my original strategy, I would often see gapping stocks that almost met my trading rules but didn't.

I wouldn't budge on my rules - so I would let these go without trading them.

But I noticed there were a lot of these that I was intentionally skipping.

Statistically, there had to be many of those that were worth trading.

I decided to place parameters in my backtest to loosen my tight rules - so much so that many more trades ended up in the backtest. Probably 3-4 times the original number of trades.

My plan wasn't to trade all of them but to use the data set to find better rules to filter for the most profitable trades.

I didn't realize it at the time, but this planted the seeds for my systematic process of finding and improving trading strategies.

What this allowed me to do was find a much larger subset of trades where the average profit per trade was HIGHER than my original manual system.

There was some overlap but not as much as I was expecting.

To visualize it, look at this Venn diagram.

More trades each day with a larger profit per trade on average.

That's a huge improvement but the real breakthrough here was the beginning of my workflow for creating profitable trading strategies.

Why I Started Backtesting

2024-02-14T11:18:00-05:00

I began serious trading in 2005. My first strategy was purely manual and an imitation of what a well-known blogger at the time was doing.

He had more trading experience than I did and I learned a ton from him. (He's no longer blogging these days.)

Luckily my imitation strategy worked pretty well - enough to keep my attention and make some money.

I was an automation nerd at the time (and still am!) so when I learned that you could create code to backtest a strategy, it appealed to me.

When I asked my trading mentor about backtesting, he pooh-poohed it. "It's not real trading - it's all simulated. Take real trades and learn what works."

So I put off creating a backtest - for a good while based on his advice.

Until I could no longer ignore the potential benefits.

Here's what I realized backtesting could do for me.

While my trading strategy was making money, several aspects of it were completely arbitrary.

For example, I used a minimum relative volume filter of 3 in my strategy.

Why 3? Because that's what my mentor used and I was imitating him.

It dawned on me that imitating others is a great way to start, but I was never going to be truly successful by copying someone else.

I had to be able to make my own decisions and not rely on anyone else for my trading edge - not even a good friend.

So I created my first backtest.

And I quickly learned just how arbitrary some of my trading rules had been.

That minimum relative volume value of 3? It wasn't terrible, but lowering that while adding another filter was way better.

How much better?

It allowed me to increase the number of trades in my trading system substantially AND increase the profit per trade.

An enormous improvement.

As valuable as that was, it wasn't even close to the most important benefit of backtesting.

I now had a process for gaining confidence in my trading.

A path to increasing my position size to generate meaningful profits, knowing that I had an edge.

At that moment I was no longer an imitator but a real trader.

Your Stop Loss Is Too Tight

2024-02-07T14:42:00-05:00

Here's a note from a fellow reader replying to my post on backtesting without stops. (I always get permission before posting.)

Dave - just to follow up on your backtest comment, I have done some tweaking of my crossing above resistance alert and generated the following results.

Crossing Above Resistance Scan, 2 hour timed exit

Stop Loss Percentage/ Return Percentage
--------------------------------------------------------------
None/ 9%
3% / -0.3%
5% / 3.5%
8% / 7%

So this scan proves your point that the lower stop loss hurts the result.

Regards,

Tim Welch

Notice the returns for this strategy and how they vary with different stop levels. No stop loss at all had the highest return. The tighter the stop loss the worse the return was.

A well-designed trading strategy will typically exhibit this behavior.

Does this mean you should trade without a stop loss at all?

Wouldn't that be optimal?

Technically yes that might be theoretically optimal in this case but I never recommend trading a strategy that way.

Why? In systematic trading, you often come across theoretical numbers that suggest a mathematically perfect approach to trading a strategy.

But (and this is a big but), there's a difference between theoretically optimal and what normal humans can realistically tolerate.

A stop loss gives you an anchor upon which you determine your position size, so you can control your risk appropriately.

It's also important to remember that a backtest is a simulation over a finite window of market behavior - not a complete picture of everything that can and will eventually occur in the market.

It turns out that predicting the future is hard. (Who knew?)

Using a stop loss is a safeguard against future market behavior that hasn't been exhibited yet.

For a good example of a situation that would have been impossible to anticipate ahead of time, look at the market action of ZJYL on 12/18/2023.

So how do you choose what stop loss to use for a strategy knowing that whichever one you choose is going to make it worse?

Dealing with these tradeoffs is hard, but it's a great exercise to examine the worse trades in your backtest and visualize what you would have experienced trading it with a certain size and stop loss.

Now imagine you have traded the strategy for a while, gained confidence in it, increased your position size significantly, and then you have a worst-case scenario. Then imagine you have a few of those bad trades in a row.

It's not fun to think about, but it's important to anticipate how you'll feel and react to this type of scenario.

This will help you visualize what stop loss will make sense to use given the imperfection and tradeoffs.

Want To Trade With Less Emotion? Here's How...

2024-01-31T10:12:00-05:00

One of the common themes among traders who come to me for help is a desire to eliminate trading with emotion.

They often believe that their emotions are to blame for some big losing trades that have wiped out weeks or months of trading gains.

Once we dig into their trading process, I have good news and bad news for them.

The bad news is that they're wrong about their emotions being the main issue.

The good news is the root cause is fixable, but takes some time.

Emotional trading is not the root cause, but a symptom of the underlying issue.

The real problem is the trader having to make decisions during the trading day that they're not fully prepared for.

The trader is putting themself in a situation where they're not confident they have an edge.

When there's money on the line, that situation is very stressful.

When you're unsure what to do, you're pretty much gambling and you have to resort to what your gut says or just guess what the most profitable thing to do is.

This usually doesn't end well and in the rare cases you do get lucky and end up with a profit, it sets a bad precedent for the future.

How do you fix this? It's pretty simple.

Any time you find yourself having to make ANY decision during the trading day, that should be a big red flag. Take detailed notes about it.

Then, after the trading day when real money isn't on the line, research all the historical instances of that situation using a backtest or a manual chart review.

The goal here is to do whatever research it takes to be confident that you know where your edge is when it happens again.

The next time it occurs, you'll decisively follow the script you've created for yourself instead of making an uninformed guess.

Repeat this process for any moment of indecision, and you won't have to worry about taming your untameable trading emotions.

Why I Backtest Without Stops

2024-01-24T10:53:00-05:00

First, look at these two charts each with a trade plotted on each:

Both of these trades were long and came from a system designed to hold all day and exit before the close.

Both hit the stop and therefore exited with a loss.

But, study each chart closely and notice what happened after the stop for the remainder of the day in each situation.

Now imagine you weren't trading with a stop and you simply held each of these trades all day.

In the EDR trade, you'd end up with a strong profit.

In the LAES trade, you'd end up with a large loss.

Very different outcomes. Polar opposites!

Here's the thing: when you backtest with a stop, you're treating both of these situations as if they are equivalent.

But they're not! Far from it.

This is one of many reasons I backtest without using a stop loss as part of my routine.

I want to make sure the rules I apply to a trading system are highly predictive and NOT dependent on any particular stop level.

Solely using a stop in your backtest hides these important details.

Here's an exercise to try with your own backtest.

Run it with a stop as you normally have done.

But then run it once more without a stop, that is, with just a timed exit (e.g. exit at the end of the day, exit after X minutes, exit after X days, etc).

Save a list of trades from each backtest.

You should have the same number of trades in each file.

Now examine the trades that had the largest profit difference (either positive or negative) when using a stop versus not using a stop.

This will show you trades like the two examples shown earlier. (EDR would show a large positive difference while LAES would show a large negative difference)

If you've never tried this before, I almost guarantee you'll learn something about your system that you can directly apply that will make it more profitable.

Give it a try and let me know what you uncover.

The Important Step Most Traders Are Missing

2024-01-17T12:08:00-05:00

I work with more and more traders on creating their own "upward spiral" - a process unique to the trader they can use to continuously improve.

It's modeled after the system I created for myself years ago at a low point in my trading career.

I realized I didn't need another idea for a strategy, I needed a process that, if I followed it, would make trading profits inevitable.

As I spoke to a trader recently about his process, it dawned on me that there was a critical piece of the puzzle that he was missing.

He had traded with a lot of emotions and wanted to get more systematic in his trading.

He started keeping a journal which is the foundation of any successful trader.

He had a coherent strategy and was executing it.

He started seeing definite improvement.

So far so good.

But I realized though that he could be so much better if he added just one important step to his process.

It's something that has been second nature for me - something that I internalized so long ago that it seems obvious to me.

But he was completely missing it.

What is it?

A feedback loop for finding trades that you didn't take, but you should have.

Simply journaling all the trades you DO take won't give you any information on the trades you DON'T take.

Without a process for identifying the trades you didn't take, you're only seeing a small part of what you have to see to get better.

Once you work this step into your routine, light bulbs will start going off in your head.

"Wait - how did I miss THAT profitable trade?"

That feeling can be frustrating at first, but when you start doing this regularly it becomes motivating.

It's exactly the kind of motivation that will eventually yield profitable trades.

You Don't Need a Perfect Idea - You Need a Process

2024-01-10T11:55:00-05:00

First, a quote:

"It is amateurs who have one big bright beautiful idea that they can never abandon. Professionals know that they have to produce theory after theory before they are likely to hit the jackpot."

Francis Crick - the molecular biologist that helped discover the structure of DNA

When I first started trading, I thought great traders were just born with a magical innate ability to come up with profitable trading ideas.

You can't learn it - you're just born with it. I thought.

I realize now that the entire industry is set up to take advantage of people who believe that.

If you just learn to trade the strategy that "trading guru X" trades - by joining their trading room and relying on them forever - then one day YOU might be able to drive a Ferrari just like they do.

If you're reading this, you should already know how this is such BS.

I love it when I see people come to this realization because this is the point where they can finally carve out their own path to trading success.

It doesn't come from asking for stock tips at your neighborhood barbecue.

It doesn't come from blindly following what some guru is trading.

It doesn't come from someone giving you a trading strategy.

It comes from taking full responsibility for your trading.

To do that you don't need the perfect trading idea.

You just need a decent idea and a process to improve it.

Trading strategies come and go, but your trading process will pay off forever.

Work on perfecting your process.

That's how you screw the Ferrari-driving trading gurus.

Case Study: Helping a Trader Improve Their Strategy

2024-01-03T13:21:00-05:00

One of the most common questions I get from traders is something along the lines of:

"Can you share one of your trading strategies with me?"

It's so common that it's easy to see why the trading industry is full of gurus who sell access to their specific trading strategy.

Buy here, sell here.

This model has never resonated with me.

Not because I'm "selfish" and want to hoard the strategies that I've created for myself.

It's because to have any chance of success in trading for the long term you have to rely on your own intuition - not someone else's.

You might have some success trading someone else's stock picks, but I can assure you the quicker you are able to generate your own strategies from your own observations, the more long term success you'll have.

And it will be way more fun and fulfilling for you than taking trades based on tips from some trading guru.

It's my mission to have as many traders as possible create and improve their own strategies from their own ideas.

How do I do that?

One way is through a Trading Strategy Assessment, a service I'll be publicly launching soon.

This is the exact same process I've used for over a decade to create and improve my own trading strategies.

Here's a case study showing how it worked for one trader recently. Let's call him Ted (not his real name).

Ted approached me with a problem. His strategy had worked well for a long time but had started tailing off recently. See this chart of the equity curve and notice how the strategy was strongly profitable but recently the profits had dropped off:

This is a common situation if you've traded for any length of time. It's frustrating!

I described how the Trading Strategy Assessment would work and Ted was on board.

At the end of the process, Ted gets a custom, 20-page PDF with full details about various ways to improve his strategy.

Here's an example. We found that he was trading quite a few losing trades that could be avoided by adding a simple rule to his strategy.

Here's a chart of what it looks like in the assessment:

The red line represents the trades that would be filtered out with the rule. The green line is what the remaining trades in the strategy look like.

This represented a 52% increase in profit per trade for the overall system.

The assessment includes a variety of different rules to apply that Ted can pick and choose from, all without curve-fitting or over-optimization.

So instead of frustration, Ted now has a roadmap for several ways to improve his strategy, all of which are simple, quick changes to his strategy, not a huge overhaul to the way he's trading.

The PDF also includes a long-term roadmap section. This outlines several ideas for tweaks that could improve his strategy significantly over time.

For example, areas of research for adding more profitable trades to the strategy or a change to the position sizing logic to generate more profits.

What I love about doing these assessments is that not only did Ted walk away with an immediately improved strategy (52% better profit/trade), but a roadmap for continuous improvement so Ted never has to rely on some Ferarri-driving trading guru again.

If you like trading rooms and following the crowd, that's fine.

But if the idea of relying 100% on yourself for your trading success appeals to you, let's talk.

I'm looking for a couple of people to help with the final beta testing of this assessment process.

If you're interested, reply and let me know.

A Smart "Time to Trade" Phone Notification

2023-12-20T11:40:00-05:00

As I mentioned last week, I have been waging war on my trading workflow after I completely missed the market open one day because I was distracted and deeply engrossed in a CTO task.

I get pissed when I miss profitable trades that I know I should have and could have been in.

In fact, nothing in the world may be more motivating to me than when I miss a trade in a way that could be easily prevented.

Around the same time that I missed this trade, a friend of mine sent me a text in the middle of the night. No biggie - my notifications are turned off.

But he apologized, saying that he meant to schedule the text to be sent later.

Interesting - schedule a text? I asked him what exactly he was doing and he sent me a link to the iPhone's now built-in Shortcuts app and the Automations section.

Holy crap. How did I not know about this feature?

I immediately thought of 3-4 things I could do with this nerdy feature.

Here's the smart notification I came up with that works great.

For one of my trading strategies, I need to enter orders before the market open. This strategy is quite profitable, so it's really important that these orders go in and the right time.

If I'm distracted and forget to enter them, that costs me money.

So I created an Automation on my iPhone that does the following:

If I'm at home
and it's a weekday
and the time is 9:20am ET
use the Speak Text function to say "Time to Trade the Open"

If I'm not at home, I'm not trading that day, so no need to interrupt me with a useless notification.

Here's what the notification looks like in the Shortcuts app:

And here's what it looks like when you tap the Do item:

Stable is the name of the street where my house is.

This works great for me.

But I want to take this one step further.

On Christmas morning (a Monday this year), this notification will tell me it's time to trade the open - even though it's a market holiday. Not ideal.

The next step will be to create a simple API for market holidays that the notification can call. If it's a market holiday, skip the notification.

Super geeky and super cool.

Do you use the iPhone automations to do cool trading stuff? Let me know - I'd love to hear about it.

The #1 Technique for Systematizing Your Trading

2023-11-29T12:04:00-05:00

Several readers had the same question after my email on systematizing your trading: where is the best place to start?

Everyone agrees that systematizing your trading is a great idea but it's hard to know what things are worth streamlining.

If you're still pointing and clicking to enter your trades, there are a slew of things you can do right away.

The easiest and most common things traders can do to start systematizing are:

Automatically calculating your position size (use a formula in Excel or Google Sheets)
Set up and start using hotkeys in your platform to enter orders (here is the documentation for TWS)
Configure strategies in Brokerage+ in Trade-Ideas (more here)
Use AutoHotKey to create keyboard shortcuts for common tasks (my personal favorite!)

Every trader's routine is a little different, so the highest priority thing for you to systematize is going to vary widely.

So what's the #1 way to determine what to start with?

Here's an exercise I did for many weeks that opened my eyes to just how much more money I could make in my trades by systematizing.

Every day I would record my screen as I traded. After my trading day was complete, I'd save the file and then review it as par of my end of day review.

This was incredibly revealing.

Watching these videos was a window into everything I was doing wrong that I had no way of realizing during the trading day in real time.

All of a sudden every day I had multiple insights into very tangible things I could do to get better.

Ways to tweak my layout.

Tasks that took longer than I realized.

Inefficiencies that added up to just barely missing profitable trades.

Looking over your own shoulder as a neutral observer allows you to see and understand things that you don't even realize as you trade - things that translate into real profits that you're leaving on the table.

Here's a challenge for you.

Do this for a month.

Pick just one thing a day to streamline.

Systematize it.

Repeat each day.

After a month I guarantee that you'll be a completely different trader than you are today.

Focus on Trading Work with a Big Payoff

2023-11-22T12:50:00-05:00

I recently worked with a systems trader who was completely obsessed with the fact that his backtesting software did not perfectly reflect the reality of his actual trades.

He was so fixated on this difference that he was planning a total rewrite of his backtesting software to use an algorithm he believed would be closer to reality. (A combination of bid/ask, depth of the order book, and other fancy logic.)

What this trader was missing was that no matter how good your backtesting software is, there will still be significant differences between your simulated results and your live trades. No amount of software engineering can overcome this fact of life.

Just because it's technically true you could eke out some improvements by jumping through a lot of hoops doesn't mean you should go through the effort.

This is a common pattern in people who come to trading from a technical field like software development.

They often focus on work that is technically possible but has a tiny payoff.

Lord knows I've gone through a lot of these wild goose chases myself in my trading over the years. Having developed many strategies I know what things will pay off and what will be a waste of time.

One of the most fulfilling things for me as a trading coach is helping traders focus on the things that will have a big payoff and avoiding the things that sound appealing but will ultimately be a waste of time.

How I Choose Stops

2023-11-15T12:12:00-05:00

I'm in the process of refreshing one of my trading strategies. It's one that I've traded without making a single adjustment (aside from using a larger position size) for 8 years.

This is always my goal in designing strategies: optimize for longevity and staying power. If you have to re-optimize a strategy every few months, it's really difficult to scale it because you can never achieve the level of confidence required to trade the strategy with a substantial position size.

This is my primary focus as make decisions when building a strategy. I don't just want something that works, it needs to make money for a substantial length of time.

One of the ways I design for longevity is by analyzing stop levels for what works across a large number of trades.

Stops are really important in your trading strategy and most traders end up choosing them arbitrarily.

The distance to the stop determines the position size I use - that is, the farther away the stop is, the smaller the number of shares I use. This lets me risk a certain amount of money per trade.

This means, though, that the stop distance matters a lot! It has an enormous impact on how it feels to trade a strategy day to day.

I've created a great tool for myself to analyze stops. It's very flexible and I can analyze stop distances in lots of different ways.

Here's the output from the tool. I ran it in percent mode, and had it start at 2% and go through 12% (see the X-axis on each chart).

The three charts are lined up horizontally, so I can easily see how a certain stop level performs across these three dimensions: stop hit %, win rate, and total profit.

So why wouldn't you just choose the level with the highest total profit?

Notice the huge variation in how often the stop is hit as the stop percentage increases. A strategy where the stop is hit almost 60% (with a tight 2% stop in the graph) of the time is going to be very difficult to trade psychologically.

Total profit is important, of course, but you need to look at the entire picture to create a strategy that you can actually trade.

The Big Payoff of Systematizing Your Trading

2023-11-08T12:21:00-05:00

When in doubt, automate it.

I think of that as my personal slogan that has served me well over my career.

Nowhere is this more true than in trading.

Over the last week or two, I've been extremely busy with non-trading stuff. I'm temporarily in a situation that requires my total focus and 100% of my time. I haven't been able to think about my trading at all.

And yet I was able to take 11 round trip trades yesterday and make a profit.

I was only able to do that by spending countless hours ahead of time systematizing my trading.

Sure it was a lot of work to get to that point - there were dozens of decisions I had to make to automate aspects of my trading and research routines. Many of these decisions would from the outside seem like a waste of time.

That simple calculation you do to compute your position size - it's not hard - in fact, it's trivial. So why go through the effort to automate that? Why not just do it in your head?

In the short term, all of these decisions seem like a lot of work compared to the benefits you'll receive.

But every aspect of your trading that you are able to systematize will start to pay off immediately and then continue to compound over time.

And the payoff will be in ways that you can't imagine as you're doing the grunt work.

When in doubt, automate it.

Handling a Large Loss

2023-11-01T15:31:00-04:00

I had a large losing trade last week that wiped out my profit for the month.

Of course, big losses suck but depending on how you respond to them they can be significant turning points that can lead to positive progress.

Here's my routine for handling them.

On normal trading days, I never display my current P&L for the day (looking at your own or anyone else's P&L is toxic).

But when I have a large trading loss, I make an exception to this rule.

In fact, I do exactly the opposite of my standard routine: I display the loss so prominently on my screen that it's front and center all day long.

I do NOT want to take losses in stride.

I want the large, red, negative numbers staring at me for the rest of the day.

I want to fully internalize the pain that comes with the loss.

I want it to be unavoidably uncomfortable for the remainder of the day.

I want to create a situation where I CANNOT avoid thinking about it.

I do this not because I'm a glutton for punishment, but because I know this sense of pain and frustration plants the seeds for future trading success.

Why I Never Move My Stop to Breakeven

2023-10-18T10:24:00-04:00

As I briefly alluded to in my article on exits, I never move my stop to breakeven.

But this wasn't always the case. When I started trading, I would move my stop to breakeven if my trade reached a certain level of profitability.

When you move your stop to breakeven, you change the potential outcomes of your trades. Here are the three scenarios that might occur:

Nothing - the price never returns to your breakeven stop so there's no effective change in your trade.
You get stopped out at breakeven and the price continues to go against you so your original stop would have been hit too.
You get stopped out at breakeven but the original stop wouldn't have been hit and sometimes the price reverses back to profitability without you.

Scenarios 1 and 2 are good - you directly save a little money in 2 and in 1 you create some psychological comfort for yourself.

This is all well and good except when you consider scenario 3. Which is terrible.

Nothing is more frustrating than missing profitable trades.

You've done all the work: you've researched and meticulously tested a strategy, and now you're trading it, and you're missing some of the most profitable trades in the system.

Not only are you missing them, but in this scenario, you've guaranteed that you'll miss more profitable trades than you otherwise would by moving your stop.

It doesn't take too many trades in scenario 3 to completely overwhelm any benefit you might get from scenarios 1 and 2.

I got stopped out of enough trades that would have been profitable that I had to backtest it.

I tried waiting for X minutes before moving my stop to breakeven.

I tried waiting until the price reached a certain level of profit before moving it.

And what did I find? No combination improved the overall profitability of the system. They all made the system perform worse.

You can, however, improve your win rate a bit by moving your stop a little beyond breakeven.

Remember - a good win rate might make you feel good, but you shouldn't be optimizing on that. You get paid by optimizing the total profit of your trading system, not the win rate.

If you want mediocre trading results by taking orders from some Ferarri-driving trading guru, stop reading.

If you’re ready to say “screw the gurus” and rely solely on yourself for your trading success, then look no further than my free weekly email newsletter.

Every week I send one actionable tip that you can apply to your trading to create a process for continuous improvement.

Screw the Ferarri-driving trading gurus by signing up below.

The Ever-Increasing Returns of a Trade Journal

2023-10-11T12:16:00-04:00

I hear from a lot of traders asking various questions about how they can improve. Very often my first question in response is "Do you keep a trade journal?"

It's always surprising to me that so many people who claim to be motivated and ready to do the work to rely on themselves for their trading aren't able to take even the first step towards it.

When I first started keeping a trade journal I used Excel.

There weren't any online trading journals at the time, so I created the first called StockTickr, and eventually sold it to Trade-Ideas.

My trading journal was critical to my early trading success, but it wasn't until years later that I realized the cumulative returns that a journal provides.

As my trading continued to improve, eventually I created my own strategies and the dutiful maintenance of keeping a journal really began paying off.

The value of a journal escalates as you transition from a newbie trader following others to a self-reliant DIY trader.

Beginning traders benefit from a journal because it forces you to make the transition from trading aimlessly with no real plan to trading a system.

The daily ritual of recording your trades makes you confront your tendency to trade out of boredom rather than trading with intention.

A journal doesn't lie - its brutal honesty allows you to honestly assess your trading performance.

As your trading improves and you transition to relying solely on yourself to trade, a journal becomes even more valuable.

Your backtest is theoretical, but your journal reflects reality. This is immensely valuable!

Your journaled trades contain all the messiness that comes with live trading that can't be captured in a backtest:

Partial fills
Missed trades
Trading mistakes
Slippage (entry and exit)
Locate costs

When you're backtesting, these trading realities can't be accurately accounted for and are therefore big unknowns.

That's exactly the opposite of a trade journal which reflects your ACTUAL performance, warts and all.

This makes your entire trading process better, from idea generation to backtesting to live trading.

Over time your journal becomes a bigger and bigger database of your actual trading experience.

Are you ready to ditch the sleazy trading gurus and rely solely on yourself for your trading success?

My free email newsletter will show you how so you never have to line the pockets of some Ferarri-driving trading guru again.

What Do Traders That Are Successful for a Long Time Have In Common?

2023-10-04T12:27:00-04:00

List member Don Brady asked me to give a presentation to the local traders' meetup group in the Raleigh/Durham area and I jumped at the chance.

We all know that most traders fail, but there are a few who make it for a short run and even fewer who make it over a long period of time. I was excited to share a window into my trading and present what it takes to be successful in the long term.

Here is an overview of what I presented to the group:

Common Traits of Successful Traders

They Keep Score

They keep track of their performance by trading strategy in a trading journal
I can easily identify a losing trader: they don't keep a journal
This habit encourages you to define the reason you take a trade

A Process to Test Strategy Ideas

Successful traders aren't "born that way"
They develop a constantly improving process to backtest ideas
Functions as a BS detector
The foundation for all of their trading

Not Primarily Motivated by Money

Important word "primarily"
They like money of course but they also love the process of trading

Driven to Constantly Improve

After successful trades, others celebrate, but they ask "How could I have made more?"
"Are there more trades like this I can find and incorporate into my routine?"

Systematize Everything They Do

From simple systems for entering trades faster all the way to full automation
Systematizing what you do improves accuracy and increases capacity

Share Ideas with Other Trusted Traders

"Networking is a trading skill." -- Mike Bellafiore
Develop relationships and trust over time with other motivated traders

Ability to Adapt Over Time

Change is a constant that successful traders acknowledge and embrace

When you're ready to be a successful trader, I can help.

What A World-Class High Jumper Can Teach You About Trading

2023-09-13T17:50:00-04:00

Nicola Olyslagers is an Australian high jumper who won a silver medal in the Tokyo Olympic Games in 2021.

But unlike every high jumper or even any world-class athlete I know of, she has a very peculiar habit.

It's a habit that's extremely visible and obvious with every attempt she makes to clear the high jump bar in a competition.

After each jump, every other high jumper might wave to the crowd, take a drink, get in the shade, and prepare for the next attempt.

But not Nicola.

After every attempt, she immediately goes right to her bag, pulls out a green book, and spends several moments writing something in it.

When she misses a height she immediately writes in her green book.

When she clears a height she immediately writes in her green book.

Even when she cleared the height that guaranteed her the silver medal in the Olympics, she immediately, and through tears of joy, wrote in her green book.

As you can imagine, as she rose in the ranks, this habit went viral because EVERYONE was so curious about what she could possibly be writing in her book after every single jump at the sport's biggest stage.

So what DOES she write in her book?

The high jump is an incredibly technical event - there are multiple phases to every attempt that have to be orchestrated precisely to maximize your chances of clearing the bar.

Nicola has created a structured process for herself where she grades her performance from 1-10 on every one of the 7 phases of the attempt.

Here's a screenshot of her journal from the Tokyo Olympics when she won silver:

Some Takeaways

There are several key aspects to her process that traders can learn from.

It's simple, structured, and repeatable
Each entry is short - there's not enough time to write a novel between jumps, so while she could likely write more, she's distilled it down to what's important and nothing more
Whether she clears the height or not, it's the same format
There's not even a check mark for whether she cleared the height or not!
She writes one (just one!) simple message for herself to focus on for the next attempt

As a trader, you should be grading yourself on whether your trade was well-executed and according to plan - the profit of the trade is secondary.

Bottom line: Be more process-oriented rather than results-oriented.

When you focus on refining your trading process, the results will come.

The Exact Moment I Became a Quant Trader

2023-09-13T11:22:00-04:00

In the mid-2000s, when all the wise people in my life were telling me it was a bad idea, I started day trading.

I had done mounds of research so I was totally prepared to trade my strategy. My days were busy so my trading options were limited, but I was convinced I could make it work.

And it did. I watched for signals, dutifully placed trades in my broker, and patiently waited for them to play out.

I wasn't making FU money with my strategy, but I had set very realistic goals for myself and I met them.

I could reasonably tell someone I was a "consistently profitable trader" at a social gathering with a straight face and mean it.

For the next few years, I focused on improving my strategy, scaling up my position size, growing my account, and learning as much as I could.

The intuition I developed over these years was incredibly valuable and couldn't possibly be distilled into a set of rules to backtest.

And I believed that with every ounce of my being.

Meanwhile, at AT&T where I was working at the time, there were oodles of manual processes and as a systems guy, all I could see was inefficiency. Everywhere.

I was automating the crap out of every process I could, and becoming a dang good programmer as I was doing it.

Could I apply what I was learning about automation to my trading strategy? Maybe.

But the nuances of it and my discretion were the key to my strategy's success. Perhaps I could cobble together a crude backtest for my strategy, but could I create something that would improve upon it? Impossible.

Or so I thought.

I finally decided "Why not?" I'd learn a ton just creating the backtest and I'd likely learn something to eventually apply to my manual strategy.

So I coded it up, ran the backtest, and exported the trades to Excel.

It took less than 5 minutes of very rudimentary analysis in Excel to realize my precious trading discretion was not nearly as precious as I thought.

It actually sucked compared to my very first backtest.

From that moment on I knew was a quant trader.

Be Prepared for Rare Trading Scenarios

2023-08-30T11:35:00-04:00

First, a story.

I'm a huge track and field fan having run at UNC back in the day (Go Heels!) and coached high school cross country and track for many years with my wife Joan.

So a couple of months ago, we were both glued to the coverage of the U.S. Outdoor Track and Field Championships when the most incredible story unfolded.

During the steeplechase, a 3000m race over barriers and a water jump, a relative unknown named Kenneth Rooks fell early in the race.

What terrible luck for someone who has worked for years (perhaps their entire life) to prepare for this moment. It's a rarity - I never fell in a race in my entire racing career - so to have it happen at the national championships really sucks.

But that's not what I want to draw your attention to.

When most runners fall during a distance race, their immediate reaction is to panic and SPRINT back to the lead pack as quickly as possible. But that never works. The energy you expend doing that leaves you with nothing for the finishing sprint when you need it most.

Instead, over the course of the next 3 laps of the 7.5-lap race, Kenneth steadily and methodically clawed his way back to the leaders.

But that's not what I want to draw your attention to.

Despite this enormous stroke of bad luck, Kenneth Rooks ended up winning the race (the national championships!) and ran a lifetime best - an outcome that nobody was expecting even if he HADN'T fallen.

But even THAT is not what I want to draw your attention to.

What I DO want you to focus on is his post-race interview where he is asked about the fall.

Kenneth calmly explained that he had actually prepared for this incredibly rare event, even visualizing before the race exactly how he would react if it happened.

My jaw hit the floor.

I'm bullish on Kenneth Rooks - anyone who goes to this level of detailed preparation realizes what it takes to be great at something and will be really hard to beat.

How can you apply this to your trading?

Here are similarly rare trading scenarios that you should prepare for and visualize your plan of action for each:

Your power or internet goes out during a trade and stays off for an extended period
Your hard drive or some other component fails on your trading computer
Your broker has an extended outage and you can't access your account
Heavy market action brings you 10X the number of signals as normal and you don't have the buying power to take all of them - how do you decide what to trade?
Your trading strategy has 10 losing trades in a row and the next signal comes - what do you do?
You receive signals from two different trading strategies for the same symbol in the same direction
You receive signals from two different trading strategies for the same symbol but one is long and one is short (it's happened to me!)

Every good trader has a plan for specific trades, but the great ones think about the risks of extremely rare events just as Kenneth Rooks prepared for his national championship.

Kenneth Rooks Steeplechase Race (starting at 3:03 mark)

Why Use a Stop Limit Order?

2023-08-23T09:53:00-04:00

I remember the moment it became painfully clear to me why you would want to use a stop limit order.

It was around 2010 and I was trading a gap system, an earlier version of one that I still trade today.

It involves waiting for a pullback pattern to appear in a stock that's gapping down, and then entering on a break of the pullback. I was using a sell stop order for the entries.

This worked fine for a couple of years.

Then one day I submitted my sell stop order to enter a trade just as I had done hundreds of times before.

As I watched the chart, waiting for the anticipated move, it suddenly dropped and I heard the familiar ding from my trading platform indicating that I got a fill. Sweet!

But when I looked at my positions for the symbol I was sitting on a huge loss. What the heck?!?

10R of slippage! That's right - I didn't get a fill until the price reached a level well beyond what my target was. Ouch.

In that one instant, I realized I needed a better way to enter positions for this strategy.

I now use stop limit orders for the entries for this type of trading strategy.

Here are some tips for using stop limit orders:

I calculate the limit price for the order as a percent of the distance to my stop (R). I use 0.24R for the limit price. For example, if the entry price is 50.00, stop price is 49.00, my order goes in with a stop price of 50.00 and a limit price of 50.24 (for a long order). The 0.24 number is not scientific - just a number that seems reasonable.
There's a trade-off using this order type: I sometimes miss profitable trades. That's the trade-off I'm making to avoid unlimited slippage.
I don't miss as many profitable trades as I thought I would - I was surprised how often the price blows through my limit price without a fill but then eventually comes back to get filled.
Because the fill is not guaranteed, I need to have a plan for how long to keep the order active if it goes through my limit price without a fill. This adds some minor, but manageable complexity to the workflow. Experiencing this exact situation was the basis for this article on what to do if you missed a trade.
Once I settled on the length of time I wanted the order to be active, I use the Good Until Time on the order in IB so it automatically cancels if unfilled or partially filled.
Automation comes in very handy for entering these orders since I have two prices to compute per entry order instead of just one.

Using a stop limit makes 10R slippage a thing of the past.

Using automation for the entries gives you the option to make the orders as complex as necessary without changing your trading workflow.

Trade Like Vingegaard Won the Tour de France

2023-08-16T13:45:00-04:00

As a cyclist, I avidly follow the Tour de France each summer. This year's event was an instant classic that provided a riveting storyline and if you were paying close attention, a lesson to apply to your trading.

From the beginning, you could tell it was going to be an epic battle between the two race favorites: last year's champion Jonas Vingegaard versus the two-time winner from 2020 and 2021, Tadej Pogacar (whose name the announcers especially enjoyed pronouncing at every opportunity).

The Tour is a long and grueling event: 21 stages over the course of 23 days.

You don't win the Tour in the first few days - it's only after the course of several stages that the race starts taking its toll and the race for the General Classification (the overall winner) heats up, and this year was no exception.

During the middle stages when all eyes were on the two favorites, although Vingegaard had a slight advantage, it seemed clear Pogacar would be the eventual winner.

He was being patient, riding very aggressively at what seemed like just the right moments, and steadily cut into Vingegaard's slim lead. Everyone assumed it was inevitable that Pogacar would take back his crown.

That is, until stage 16.

During this individual time trial stage, Vingegaard handily whooped Pogacar and built a huge lead, followed by stage 17 where he destroyed Pogacar and made the gap insurmountable by any measure.

Though he won just a SINGLE stage in the entire event (Pogacar won 2 and another rider won 4 stages), Jonas Vingegaard won by one of the largest margins in 30 years.

He was certainly consistent throughout the tour, but Vingegaard didn't care about winning individual stages. He was biding his time and waiting for the exact right moment when he had a huge relative advantage over every rider in the field.

And when that moment came he was decisive and confidently put it on the line.

The best traders I know trade like Vingegaard rides the tour.

How to Create a Profitable Trading Strategy

2023-08-09T13:04:00-04:00

I'm going to let you in on a little secret.

All trading strategies work and all strategies don't work.

Once I fully understood this, I was able to create a process to quickly determine what rules to apply to a strategy to trade it profitably.

Think of it as a lightning-fast statistician that can tell you the optimal way to trade a strategy.

I use this process to convert so-so or even poor strategies into profitable ones by layering it onto a backtest which allows me to:

Quickly establish whether a trading strategy is worth pursuing
Go from an idea to a profitable trading system
Create new rules for my existing strategies to make them even more profitable

The key is determining the move that your trading system is capturing and then being able to quantify everything about it.

What makes the move unique? Are there instances where a setup is CLOSE to a match for the system but not quite? Could your "excluded" trades be added back to the system to increase overall profit?

I have a library of data points that gets applied to all my strategies automatically through the backtest. Then, for each strategy, I set up additional indicators that quantify every detail of the setup. For example, the range, the volatility, the position in the range, the recent market action, etc - basically everything that can numerically describe the entry signal that could possibly affect the profitability of the system.

I can then instantaneously determine which rules to apply to trade each system.

Is it a magic bullet? No - it can't create a strategy out of thin air or turn a really awful strategy into a golden goose.

But it does allow me to turn a much higher percentage of my trading ideas into actual profitable strategies without curve fitting.

If you're interested in creating your own profitable trading strategies, you'll love my free newsletter where I show my exact process for creating them every single week.

Exiting Your Trades - What Works Best?

2023-08-02T12:29:00-04:00

New traders are always interested in how to enter trades, but they'd be much better off spending more time focusing on how to exit their trades.

Successful traders spend far more time examining their exits because they know that's where the money is. Small changes in how your strategy exits trades can make an enormous difference in your strategy's profitability.

Of all the 15+ strategies I trade, here's a list of the exit types I use for each of them in order of importance with advice for each of them to apply to your strategy. Your backtesting process should allow you to test all these exit types.

Time Stop - Used in 100% of My Strategies

If no other exit orders execute, when do you call it quits because too much time has elapsed? I include this exit in all my strategies.

Tips for time stops:

Use the Good After Time order property in IB if you can.
Understand the move your strategy is trying to capture and give it the required time to play out.
Find a way to automate this so you can enter it right after you enter your trade - or better yet AS you enter your trade.
Don't be tempted to adjust the exit time during a trade. Instead, make a note and backtest a different time stop outside of market hours.

Stop Loss - Used in Almost All of My Strategies

A stop loss is a stop order that is set at a certain distance below your entry price for longs and above your entry price for shorts. This is a fundamental exit that prevents catastrophic losses and you should use it in your strategies unless you have a really compelling reason not to. If you're reading this, you should be using a stop loss in your strategies.

Tips for stop losses:

It's tempting to make them tight - too tight. This can cause serious slippage.
You should size your position based on the stop-loss distance.
Your stop should be based on some measure of volatility rather than price or percentage.
Do I move my stop to breakeven? Never.

Target Order - Used in Just Under Half of My Strategies

A target order is a limit order that's placed above your entry price for longs and below your entry price for shorts.

Tips for target orders:

Similar to a stop, a target should be based on volatility, not price or percentage.
Consider using multiples of your stop distance for your target. For example, if the distance to your stop is X, try a target distance of 3X or 4X.
For your strategies without a target order by default, consider placing one very far from your entry. It won't get hit a lot but every once in a while it will!
Review your most profitable trades - would using a target somewhere have made you even more money on them? It's quite possible.
I don't scale out of trades (except for certain circumstances) since you end up paying for the privilege with trading profit.

Trailing Stop Order - Used in Zero of My Strategies

A trailing stop is easily the most overrated of all the exit types. The trailing stop gives you the worst of both worlds - a premature exit of a profitable trade on a pullback - a great way to minimize your profits! It seems like a clever idea but I've done enough backtesting to realize it never works, at least for me.

It's so reliably bad that I'm highly skeptical of any short-term trader that says they use them. Swing trading or longer-term investing is a different story. The longer your strategy hold time the more a trailing stop might make sense.

But this is where your backtesting becomes your superpower - test it for yourself and if it works for you, use it!

Choosing a Backtesting Platform

2023-07-26T12:31:00-04:00

A trader on Twitter posts a chart with a winning trade along with arrows for their entry and exit points. It seems like a great trade - but are they showing you all the trades they took that day, even the losing ones?

Of course, there's no way to verify that - you'll have to take them at their word.

Can trades like the one tweeted be used as a profitable trading strategy?

A well-tuned backtesting process allows you to test the strategy yourself. The better your process is, the quicker you can test the trading strategy.

But a well-designed backtesting process yields benefits well beyond just answering a single question. When set up correctly, it allows you to:

Transform almost any strategy into a profitable one that you can trade
Create a roadmap to continuously improve a strategy in the future
Have a powerful BS detector so you never have to wonder if a strategy works or not

These benefits compound over time. Even if you run into a dead end with a particular trading strategy you still learn a lot about the markets and what works and doesn't work. That knowledge accumulates and even when something you learn seems useless today it can become very valuable when applied to other ideas you'll have in the future.

Backtesting is as close to a superpower as a trader can have.

Required Backtesting Features

There are a lot of platforms out there that claim to have backtesting, but there are only a few that have the features required to be a part of my backtesting process.

Ability to Backtest the Entire Market

If the package cannot test across the entire market then it is not worth using. A lot of software can test on single symbols or a basket of symbols, but there's a reason only a few can test across LOTS of symbols: it's a very hard technical problem to get right.

This requirement alone eliminates the vast majority of backtesting platforms from my consideration.

Add Custom Columns to the Backtest Trade Results

This critical feature is one that most traders ignore. You need the ability to determine how certain indicator values affect the profitability of your trading strategy. This is fundamental to any effective backtesting process. Without this ability, you'll never be able to have the confidence to take some of the trades in your system with full position size.

Extensibility

Successful traders understand that although profitable strategies usually have surprisingly simple logic, they are very much unique to the trader. Mimicking someone else's strategy might work in the short term, but if you are going to have long-term success in trading you need a process for generating your own strategies from your own unique ideas. That means your backtesting platform needs to be infinitely extensible by writing your own code.

Longevity

If you want to trade for the next year or two, pick whatever platform you want. If you want to be trading successfully for the next couple of decades, then pick a platform that has been around a while and is actively being developed.

Backtesting Platforms I Recommend

I have used several backtesting platforms over the years and I have settled on two for my trading workflow.

Trade-Ideas OddsMaker

As the CTO of Trade-Ideas, I admit I'm biased here, but I use the OddsMaker for some of my short-term strategies and for quick strategy prototyping. It's lightning-fast (I guarantee nothing on the market is faster!) and easy to customize without writing code. You can add filter values to the trading results and it's extensible through custom formulas.

The nice thing about the OddsMaker is that it fully integrates with your real-time alerts - so it's trivial to backtest a strategy that you already use.

Amibroker

I'm a long-time Amibroker user and while it's not perfect, it works well for backtesting and it's fully extensible. It also has a nice charting platform that you can customize with code. It has been around for a long time and has a steady stream of improvements.

Here are other platforms that I recommend to traders depending on their situation:

Python

If I were starting today, I would probably use a combination of the OddsMaker and Python for backtesting. For clients I work with that have strong technical chops and coding skills, this is what I recommend. It's completely customizable down to every aspect. The backtesting library I recommend for Python is backtesting.py, although there are others that work as well.

NinjaTrader

I tried NinjaTrader a long time ago and didn't really vibe with it but it's a good platform and checks all the requirement boxes above. If you're comfortable with C# then you should strongly consider it. From the looks of their current marketing, they focus mostly on futures trading for some reason.

(Are there other platforms that I should add to this list? Let me know.)

The Day I Almost Quit Trading

2023-07-19T15:57:00-04:00

It wasn't a single day, it was more like a week of wondering if I should quit trading.

At the end of 2012, I focused on getting the most out of my trading system. It had performed well up to that point and after my annual trading review, I knew what I had to do to size it up. And that's what I was trying to do.

Trade the same system just bigger. No major changes - just sizing up what I was already doing. It had worked for 4-5 years at this point - if it ain't broke don't fix it, right?

Midway through 2013, though, I was staring down the barrel of a major drawdown which for weeks I'd convinced myself was just temporary. It wasn't. So, on one final day of particularly poor performing trades, I had to face the music and reduce my position size substantially.

I desperately examined my trading journal, looking at every single trade I took. Had I veered too far from my trading plan without realizing it? Was I losing out on significant profits to slippage with the increased position size I was taking? Some missed trades are unavoidable and out of your control, but was I missing out on a lot more than the previous year? In short, what were my avoidable mistakes? I was on a mission to find out.

I'd always been able to do this type of deep dive into my trading results and figure out what the problem was and address it, but this time there was no obvious path to fixing it.

If it wasn't something that I was doing wrong, what could it be? My only conclusion after tossing and turning (literally losing sleep!) for several days was that my tried and true strategy had just... stopped working.

The Abyss

This was devastating to me. It's hard for me to even write about this because of how difficult it was to grapple with. I had done all the recommended things to be a good trader. I started trading with small size, set reasonable goals for myself, and slowly sized up over time. I methodically logged all my trades in a journal at the end of each trading day. I regularly reviewed charts for my trades and looked for ways to improve.

That stable game plan had served me well for many years and turned into solid trading profits. I was a trader - and not only that: I had been a successful one. And now this was happening to me?!?

I knew there were no guarantees in the market and that it's constantly changing and traders have to adapt. I thought I had the foundation I needed to adapt to anything.

I was out of ideas with no hope for my trading future. I hated this feeling of helplessness more than anything.

It wasn't simply that I was in an ordinary drawdown; I was in a drawdown of working solutions - a trading malaise, so to speak - completely out of ideas for how to improve my strategy.

A Better Process for Creating Trading Systems

I spent the next several months building a trading process from the ground up to avoid this situation.

A backtest alone was not going to cut it.

A trading journal was not going to be enough.

All the discipline in the world doesn't matter if you can't adapt.

Strategies that work for other traders weren't necessarily going to work for me.

I needed to devise my own unique trading strategies and nimbly recalibrate as the market is ever-changing.

And that's exactly what I did.

I've spent years refining my process and reduced the amount of time it takes to create a viable trading strategy by 20-fold. I've used this process to create 15+ profitable, robust trading strategies and continuously improve them.

If you want mediocre trading results by taking orders from some Ferarri-driving trading guru, stop reading.

If you're ready to say "screw the gurus" and rely solely on yourself for your trading success, then look no further than my free weekly email newsletter.

Every week I send one actionable tip that you can apply to your trading to create a process for continuous improvement.

Screw the Ferarri-driving trading gurus by signing up below.

A Daily Trading Goal is a Terrible Idea

2023-07-14T12:17:00-04:00

In Annie Duke's book Quit, she describes a study of the behavior of 2000 cab drivers in New York City.

The authors of the study analyzed the data and realized that drivers could make significantly more money by working longer on the good days when the fares were plenty and driving fewer hours on the bad days when demand was low. Why were the majority of drivers not recognizing this shortfall?

They interviewed several of the drivers and realized the problem...

It's human nature to set benchmarks and track them, and most cab drivers do just that. They have a revenue amount in mind that they're trying to achieve each day. When they hit the number, no matter what time it is, they quit for the day and go home.

As you might imagine, on some really good days they hit their number very early in the night. On other days when there's less demand, they might drive long hours and still not make their personal daily goal.

The study found that cab drivers could increase their earnings by 15% by working the same hours but, instead, allocating them based on demand - working longer hours on the good days and fewer on the bad ones. Their daily goal-setting, which feels productive, actually causes reduced earnings.

Daily Trading Goals are Counterproductive, Too

If you're similarly setting a daily profit goal for your trading, you should rethink that immediately. Opportunities in the stock market don't come at a constant rate - some days will be flush with more great trades than you can take while other days the market will feel like a ghost town.

You have no control over the rate of these opportunities - there's no way you can create them, all you can do is be ready when they arrive. That means having the discipline to sit on your hands and not force any trades when they don't exist. If you don't trade with a system, you'll always be able to squint hard enough and find a trade to take.

If you look at a successful trader's results, one thing immediately sticks out: almost all the profit comes from a small percentage of trading days. I just checked my journal for the best-performing of my 15+ trading systems. Of the 101 trading days so far in 2023, there are just 60 days where it took at least one trade, 41 of those trading days ended up with a profit, and 19 of them ended up with a loss. Of the 41 profitable trading days, a lot of them had a marginal profit. All the heavy lifting that makes this strategy profitable happens on less than 10% of days. If I had imposed a daily trading goal on those days, this strongly profitable strategy would be the opposite: a loser.

Trading success involves tremendous discipline and sitting on your hands when conditions aren't favorable.

Daily trading profit goals cause you to take the exact opposite approach from what's required for success.

Shooting for a Certain Number of Trades is Just as Bad

There's a related line of reasoning I've heard from traders that sounds accurate on the surface. They don't have a daily profit goal per se, but they have a goal of a certain number of trades to take. They correctly recognize that although it's bad to overtrade by taking some subpar trades, it's much worse to undertrade and miss out on big winners. That fear of missing big winning trades causes them to take marginal trades on slower days in hopes of capturing as many big trades as possible.

This is wrong for the same reason that a daily profit limit is - there's not a quota for trading opportunities. The profitable situations for your strategy are independent and not related to each other. A daily "number of trades" goal treats them as if they are.

A Daily Trading Goal That Works

Define your trading rules and stick to them.

Then your daily trading goal becomes really easy: follow your rules.

One Question to Identify a Profitable Trader

2023-06-23T01:00:00-04:00

If you've traded for any length of time you'll quickly realize that there are a lot of traders that give the appearance of robust profitability but when you scratch the surface they don't quite live up to what they outwardly project. This is especially true on Twitter where would-be traders start with a flurry of activity and then fade away as time goes on.

This reality makes it difficult to find other successful, creative traders to collaborate with. As Mike Bellafiore said in this tweet, "Networking is a trading skill."

So how do you find other serious traders to collaborate with and share trading ideas? Building trust with other traders takes time and effort, so you need to choose wisely.

Imagine you're at a networking event for traders where you don't know anyone. There's not enough time to have in-depth conversations with every attendee, but you can ask everyone individually a question they'll answer. (Like speed-dating.)

What's the ONE question you ask that you believe gives you the best odds of finding the successful traders in the group to spend your valuable time conversing with?

I sent this scenario to my newsletter subscribers a few weeks ago and got some great responses. Here they are:

How much was the borrow? - Anonymous

It's easy to conveniently forget to include borrow costs when looking at your trading performance. The answer to this question would tell you a lot about how transparent someone is about their trading track record and how sophisticated their strategy is.

What broker do you use? - Isaac H.

I wasn't sure about this question at first but the more I thought about it the more effective I think it would be. These responses would give me an indication of the type of trading they do:

a prop trading firm
Robinhood
Interactive Brokers
E*TRADE
Schwab
Cobra
Multiple brokerage accounts

Do you rely on your trading income to live? - DMactrades

Trading for a living is surely a good indicator. Perhaps not as effective as it used to be prior to Covid when remote work was rare. I suspect the rate of serious part-time traders worth collaborating with has been increasing over time.

What is the one thing you can do this month that will have the most impact on improving your performance? - Mike Bellafiore

This is a very direct question that gets to the heart of long-term success. The best traders are ALWAYS improving. Your answer to this question should be well thought out and change from month to month as you implement your improvements.

What do you look for in your Grade A setups? - T. S.

I like this question because it gets to the heart of how traders should be thinking about their trading systems. I encourage traders to not think about every setup in their trading system in the same way. The biggest leap I made in my trading was to go from a binary yes/no thought process to thinking in ranges. That is, to what degree do I think this trader will be profitable relative to other traders in this system? Great question!

How do you avoid losing trades? - Anonymous

The answer to this question will tell you a lot about how someone thinks about their strategy and whether they have one at all.

Do you use a trading journal? - Dave Mabe

This is the question I've had in mind ever since my StockTickr days. It was clear that if you're not keeping score, you're just not going to be successful. I remember discussing this with a well-known poker coach in Las Vegas a few years ago.

He said the correlation is 100% - for all poker players he came across if they aren't keeping track of their sessions then they simply aren't profitable. At that time he knew of no exceptions. I'm pretty sure the same goes for trading. Do you keep a journal?

Take Your Best Trades with Bigger Size

2023-06-16T10:20:00-04:00

Imagine you're playing poker and one of two scenarios plays out.

Scenario A: you're dealt a pair of Aces and the flop comes out Ace, Ace, King. You've got four-of-a-kind.

Scenario B: you're dealt a pair of sevens and the flop comes out Jack, six, three. You've got a pair of 7s.

Would it make sense to allocate the same amount of money in each scenario? Of course not - in scenario A you have a much stronger probability of winning the hand.

Yet this is what I see most traders doing with their trading strategies: they use the same position size for all of the trades in their system. It's a reasonable approach for getting started: as you gain confidence in the system, you can easily size up by increasing the amount of risk you're taking per trade.

But this assumes that every trade in your system has the same trading edge. Of course, that can't possibly be true: there's a huge variability in the likelihood that your trades end up being profitable and to what degree. Using the same size for all your trades is like betting the same amount with your four-of-a-kind versus your pair of sevens in the poker example. You're missing out on a lot of profit doing it that way.

You can simply increase size across all your trades, but ultimately, the best way to improve your trading strategy is to identify the subset of trades with the highest trading edge and trade those with more shares than your normal position size. Find your four-of-a-kind scenarios in your trading system and use that to your advantage.

When you use an increased size you will have some larger losses, but if you are able to identify the right subset of trades, the outsized gains from the profitable trades will easily overwhelm the losses. After all, a four-of-a-kind in poker sometimes loses the hand, but that doesn't mean it's not an overwhelmingly profitable situation!

Here's an example of going through this exercise with a trader that's working with me to improve his strategy. We were able to identify a solid subset of trades in his system that were contributing most of the profits and reasonably trade them with larger size. Here's the equity curve of the original system with consistent sizing for all trades (the red line) compared with the same system but taking trades with the strongest edge with bigger size (the green line).

The benefits go well beyond just the increased profits. Soon you might be able to shed some of the weaker trades in the system and free up buying power for additional strategies.

Can Limited Time for Trading Be - A Good Thing?

2023-06-08T13:44:00-04:00

Fellow reader Sashi N. (posting with permission) contacted me with this trading concern:

Hi Dave - my biggest issue with trading right now is time!
Being a senior pro at my organization, I am unable to dedicate serious time towards trading, and actually get to spend just a few hours every weekend.
I need a good process to organize my time (charts, scans, learning, coding, testing - and so on)

Sashi N.

I immediately thought back to when I first started trading. I was working full time at AT&T and had recently finagled the ability to work from home after my youngest daughter was born. Residential broadband was just becoming widespread, so I converted our toolshed into an office that was almost habitable (there were plenty of mornings when I started my day in a 40 degree "office" with blue skinks joining me for coffee). Working remotely gave me an extra 2.5 hours a day (commute time + lunch) to do more outside-of-work activities: exercise, spend more time with my family, brew beer and, of course, trade.

Despite this newfound flexibility, time to dedicate to trading was still very much at a premium for me. Regular meetings, ad-hoc conference calls, actual work, and a newborn baby consumed my days and left precious little time to think about the markets at all, let alone day trade!

My Extremely Time-Constrained Trading Routine

I found a way, though, by carving out a routine that was just barely feasible. I religiously set aside 30 minutes every weekday morning to closely observe the market and trade. Starting with the open at 9:30 am, I'd watch the market action specifically looking for my predetermined setups in gapping stocks.

I'd enter my trades and then immediately submit my exit orders. At the time it was trendy to use "mental stops" - that is, some traders wouldn't enter explicit stop orders for their exits, but they'd have a price in mind that they would watch and then manually exit when the price was reached. With my extremely limited schedule, I didn't have the luxury of casually monitoring my positions all day - my only option was to use explicit stops and go on about my day job.

Once the clock reached 10 am, the conference calls and meetings began - I had to stop trading. And there were plenty of days my boss would call me during that first half hour (the nerve!) and I'd have to cut my trading short and skip some profitable trades.

In the moment, I recall being very frustrated with my situation. If only I had more time, I could have entered more profitable trades after 10 am, managed my positions more responsibly by watching the intraday action, traded more strategies throughout the day, and created a plan to trade the lucrative market close.

I could have made so much more progress more quickly!

My Time Crunch was an Advantage

Looking back now, though, I realize that these constraints instilled some valuable trading habits that still benefit me to this day, 22 years later.

I HAD to Trade a System

Because of the severe schedule constraints and distractions, I had to execute a pre-planned strategy. There was no time for concocting hypotheses on the fly - the setups either met my criteria or they didn't. I didn't second-guess myself. If there were potentially profitable situations I noticed that weren't captured by the system I was trading, I would take note and do research on the weekends to determine if they were feasible to trade.

Overtrading was Impossible

I didn't HAVE the ability to take trades willy-nilly; I barely had time to take the trades in my existing trading strategy! Taking off-the-cuff boredom trades was off the table.

No Exiting Too Early

If I'd had time to stare at my positions' P&L all day, there certainly would have been plenty of instances I would have caved and exited a position earlier than planned because it "felt right" only to have it continue without me. My schedule allowed me to unknowingly avoid what I realize now is an extremely common trading mistake.

Forced to be Ruthlessly Efficient

My situation forced me to think hard about systematizing my trading. I wasn't auto-trading at that time but I may as well have been: I had to create a plan to trade a fast trading system in a short amount of time.

That meant removing distractions: using Trade-Ideas to alert me for the EXACT situations I wanted to trade and nothing else, having a predetermined game plan, and confining myself to the types of strategies that were realistically possible for me to trade.

Look closely at your own situation - those seemingly frustrating constraints might very well help your trading in the long run.

What Manual Traders Can Learn From Systems Traders

2023-05-23T12:57:00-04:00

A reader (Chris, posting with his permission) emailed me recently to ask how he could improve his trading:

I am a part time swing trader and I only trade breakout strategies leaning on Qullamaggie style. I have been doing this for 2.5 years. Although I am not profitable, my winners are larger than losers. My entries have been sometimes a little bit late. But what draws me down: my win ratio is too low. My timing is a bit off. Shouldn't be trading when markets are below EMA10.

Chris

I responded:

If you're not already keeping a trading journal, you should start immediately. Start reviewing your journal to search for patterns in the trades you've taken. Are there trends you pick up on that you couldn't see in real-time?

Me

It turns out Chris kept a workable trading journal a year ago, but had gotten lazy about updating it (his words, not mine). After Chris and I had some back and forth, he reviewed his recent trading history and identified several problems:

Needs more consistent tracking of trades in his journal
Overtrading - Chris sees something moving and sometimes can't resist the urge to trade it
Mid-day entries are almost always losers
Chris trades too many lower price stocks; the higher priced stocks turn out noticeably better
When trading more than one setup, he hasn't consistently categorized them as such in his journal

While this may seem sloppy to systems traders, I feel optimistic when someone frankly identifies ways they can improve. Honest post-trade reviews almost always yield a list of concrete steps to profitability.

Sure enough, after a few more questions, we identified several rules Chris could follow that would have made him profitable over the last 12 months. He now has a roadmap to eliminate his over-trading, improve his low win rate, and avoid his biggest losing trades. On top of that, his initial assumption that he shouldn't be trading when the market is below the EMA10 (10 period exponential moving average) turned out to not have any effect on the profitability of his trading system.

Tips for Manual (Discretionary) Traders

I've worked with several discretionary traders and systems traders over the years and while there are substantial similarities between them, manual traders can learn valuable lessons from their systematic cousins.

Keep Score

If you're not keeping meticulous records of what and how you're trading, you're just not going to be profitable, plain and simple. If you're trading to brag to your friends or post your winning trades on Twitter, then you don't need a journal. If you want to actually make money, though, keeping a trade journal is an absolute requirement. The most effective breakthroughs you'll make in your trading career will come from analyzing your journal and seeing in no uncertain terms which elements of your trading suck.

Categorize Your Trades By Setup

Although you may call yourself a breakout trader, a swing trader, or a low-float short trader (like everyone on Twitter these days), you are probably taking different styles of trades within these broader categories.

Systems traders are ruthless at identifying modified setups and systematizing them. If you're taking trades in a single system for multiple reasons, even if the differences might seem insignificant, it's critically important to identify distinct categories and start tracking trades in your journal accordingly.

The more precise you are, the more money you'll be able to make by analyzing specific subsets of your trades. Chris was able to create a simple rule based on price that will improve his trading, but this is setup dependent. This price rule wouldn't make sense if naively applied to other setups he's trading, that is, it's only useful in the context of this particular setup.

Systems Traders Challenge Their Own Assumptions

All types of traders have assumptions about how the market works, but systems traders have the ability to challenge their own preconceived ideas and quickly verify their accuracy.

Take Chris' assumption about the 10EMA - he presented this theory as fact (he was certain it was true!) until he actually looked at the numbers. Systems traders have a finely tuned process for verifying claims and testing their trading theories. Should you take trades when the price is above the 50 day moving average? Systems traders don't assume - they efficiently determine the answer using their own personal verification system which they constantly improve over time.

Clearly Define Your Rules Prior to the Trade

It's very common but always strikes me as a little odd when someone tells me they're "overtrading" and asks what they should do about it. My first instinct is to say "Just stop doing it" but I realize now this is my inner systems trader talking.

When discretionary traders say they're trading too frequently, this usually means they've looked back at some of their trades and realized they shouldn't have taken a lot of them. Yes, this is technically "overtrading" but it really points to a bigger problem: they haven't defined their rules well enough to know whether, in the moment, a trade meets their criteria or not. With hindsight it's easy to see, but in real-time deciding to take a trade is far more difficult, especially when there might be two or three setups that materialized simultaneously and compete for your attention.

Predefining your rules for the setups you're taking will make this process far easier.

Learning from systems traders doesn't have to mean completely automating your trades. Discretionary traders can look over the shoulders of systematic traders and borrow plenty of their good habits, just as Chris did.

You're Probably Backtesting Wrong

2023-05-11T10:44:00-04:00

I've worked with a lot of traders over the years, many of whom are quite smart and able to backtest their ideas to generate successful trading strategies. But when I look at their backtesting routine, almost all of them completely ignore the most productive step for creating profitable models with a strong and durable trading edge.

Backtesting this way is like riding a horse compared to walking while not realizing that airplanes exist: you can travel a long way on horseback (even across the entire country, in theory) and you'll leave mere walkers in the dust. However, if you're unaware of air travel then you may as well be a sloth who has no idea that he can travel at least 100 times faster by plane.

Here's a standard backtest workflow that I see traders doing over and over:

Trading strategy idea generation
Code the backtest
Run the backtest
Analyze aggregate metrics and equity curve
Decide to trade it or return to step #1

Let's look at these steps one at a time in detail.

Trading Strategy Idea Generation

Generating ideas is the hardest part of trading for most since it starts off like a chicken and egg problem: ideas come from experience but to have good ideas you first need to have some experience. With enough practice, though, this becomes the easiest aspect of the whole process. I know some readers will find this hard to believe, but the more you're able to exercise your "trading idea muscle," the stronger it will be.

Because it takes regular practice and hard creative work, this step weeds out a lot of would-be traders.

Code the Backtest

For most traders, coding the backtest ranges from difficult to impossible. Even high-level traders who are excellent at coding have a hard time context-switching from trading (or other tasks) back to writing code. This is exacerbated by the fact that running the backtest takes so much time. You can't stay in a productive coding zone when you get interrupted by a backtest that takes an hour or more to run.

Run the Backtest

Depending on the markets and instruments you're running a backtest on, this part will likely be the most time intensive. If it does NOT take a long time to run, you're probably not scanning the entire market, thereby missing out on profitable trading opportunities.

If your backtesting platform doesn't have the ability to scan the entire market, then - back to my analogy - you're on horseback. Better than walking? Yes, and certainly faster than a sloth, but you're not really in the same game as successful systems traders.

Analyze Aggregate Metrics and Equity Curve

A lot of traders get tangled up here in deciding which aggregate metrics to focus on. There are plenty to choose from and it's tempting to try to find the "fanciest" one that supersedes all others. Rather than trying to find the perfect single metric, I look at a handful of metrics in this phase. (While important, how I choose my metrics is beyond the scope of this post. I'll outline my exact process in a forthcoming message to my newsletter.)

Decide to Trade It Or Return To Step 1

Using whatever criteria you've settled on, you either move forward and trade the strategy as is, or you start the process over at step 1.

Here's this workflow in visual form - note that the pink boxes represent particularly time-consuming parts of the process:

The Step You're Missing

This workflow is... fine. You're on horseback competing against walkers. But there's a very important phase of my routine that is completely missing from this workflow. How important is it?

I call this the Filter Phase and I literally spend 95% of my overall backtesting time in this phase. It allows me to reduce the time I spend creating a strategy from days and weeks to minutes and hours. It's the reason I've been able to create and trade 15+ (and counting) profitable strategies.

The Filter Phase

In order to add this step to your workflow, you'll need to be able to make a couple of small adjustments to your overall routine. Your backtesting platform must have the following capabilities, otherwise, you're stuck on horseback:

Export a trade list from the completed backtest to a CSV file
Add a custom column to each trade in the backtest

These features are not available in most backtesting platforms.

Let's say you have a strategy based on an 8 and 20-period moving average crossover. Or maybe you've created a basic strategy using ChatGPT as I did. It works ok, but you want to improve it. You have a theory that, say, volume relative to average volume (a.k.a. Relative Volume) has an effect on the profitability of the strategy.

Most traders at this point will "guess and check" - that is, pick a number that seems reasonable to them for relative volume and then they'll code it into the strategy such that the trade set you end up with in the backtest is a subset of the original. This is a subtle mistake that costs traders a ton of time and resources.

Here's what you NEED to be able to do in your backtesting platform. Instead of modifying the original strategy, you simply add a column to the trades that end up in the resulting trade list. When you do this, the number of trades in your backtest DOES NOT change - you're only adding additional columns that capture the numerical value of different filters that you MIGHT decide to filter on later on in your process.

For example, let's say your original backtest produced a trade set like this:

Entry Date	Symbol	Entry Price	Profit
2023-05-22	MSFT	306.94	100.00
2023-05-21	META	231.96	50.00
2023-05-20	AAPL	172.78	-75.00
2023-05-19	TSLA	170.14	25.00

After you add your column, your new backtest looks the same as the original, but with a new column added that corresponds to the filter that you want to examine (see the column called Relative Volume).

Entry Date	Symbol	Entry Price	Profit	Relative Volume
2023-05-22	MSFT	306.94	100.00	1.50
2023-05-21	META	231.96	50.00	0.47
2023-05-20	AAPL	172.78	-75.00	2.55
2023-05-19	TSLA	170.14	25.00	0.24

The important thing to note here is that you're still including all the original trades even when you're confident you'll be filtering some of them out when you eventually go live with the strategy. It's not at all important to remove them from the trade list in the coding phase. When you have a Filter Phase in your backtest workflow it's a piece of cake to remove them in this step.

OK, So What's the Big Deal?

So you've got some extra columns in your backtest. How does that help?

Because you have the entire range of values for Relative Volume in your trade set, you can determine the optimal filter value without having to run a bunch of time-consuming backtests to find your answer. You've gone from a brute force "guess and check" with at least hours between the guesses to learning and iterating on the knowledge you've gained in seconds.

The effect on your workflow is MASSIVE. This allows you to reduce the number of times you have to code and run a very time-consuming backtest from oftentimes several dozen to just... one time. What once took days and weeks in backtesting, can now be accomplished in minutes and hours.

As you can imagine, this opens up entire worlds of trading strategies to test (and learn from!) really, really quickly.

Rapid, Continuous Learning

When you add the Filter Phase to your routine, you'll get better and better at efficiently learning what makes a trading strategy tick. It allows you to go from answering a very simple question:

Should I trade this strategy? Yes or no?

to a much more powerful and profitable question:

Under what circumstances should I trade this strategy with full size?

To answer that question, you must thoroughly understand your trading system. If you're not using some form of the Filter Phase in your backtesting workflow, you're riding horseback in a world of airplanes.

***

To learn more about how you can use this concept to create your own trading strategies, sign up for my free newsletter below where I regularly share my techniques for doing so.

Reader Question: How to Stop Getting Into Trades Too Early?

2023-05-03T12:07:00-04:00

Fellow list member Thomas S. wrote in with the following trading problem (shared with permission):

I am a full-time stock and futures trader for about 9 months now. Been trading 2 years. I have a subscription to Trade-Ideas.
My most frustrating problem is getting into stocks or futures too early. Being impatient. Think I just get excited.

Thomas S

This is a really common problem - I suspect that almost every trader has experienced it. I've seen a couple of different forms of this situation.

The Trader "Front Runs" the Setup

You see a setup forming and the candle hasn't quite finished yet to solidify the signal. But you go ahead and enter the trade anyway because you're almost certain it's going to trigger when the bar closes. You might even get a better price than if you wait to be sure the signal is valid. How clever of you!

But the candle finally completes and... it turns out the signal wasn't actually valid. The price didn't quite close above the moving average, but just below it. Or maybe the low of the bar dipped quickly just below the bar closed which, according to your rules, invalidates the signal.

Whatever the situation - you ended up anticipating the trade instead of waiting for it. Now you're in a position that your system didn't think you should be in. It was close, but it didn't quite match the rules. That's ok, you think, it's close enough and you just treat it as if it was a valid signal. It's probably ok since you got that nifty price improvement on the entry. In your mind maybe that will make up for the barely imperfect nature of the setup.

Of course, you know what happens next. The trade ends up being a loser - that you shouldn't have been in to begin with. Your trading system worked just fine - you just shot yourself in the foot.

Often this habit starts forming when you front run the entry on a trade and it actually ends up being profitable. Nothing is more dangerous than a profitable mistake when you're trading. Be very careful when this stroke of undeserved good luck occurs.

The Trader Hasn't Fully Defined the Trading System

Another situation where I've seen this occur is when a trader believes they are trading a system but the clearly defined rules for the system aren't... so clearly defined. Losing trades are rationalized after the fact with a generic "I was too early on that one" excuse.

The question I always ask here is "How do you know you're too early?" You need to be able to define what "too early" means just prior to entering the trade. If you can't do that then you're not really trading a system. If it's clear after the trade that you were too early, then work on defining exactly what that looks like just prior to entering the trade.

Don't be fuzzy with entry rules - clearly define them ahead of time in a way that allows you to follow them in the moment during the trading day.

If you're trading a really fast system with a lot of trades, one thing that's really helpful is to take a video of your screen as you trade and then review it after each day. Several years ago when computers weren't super powerful I would set up software that would take screenshots every few seconds since a full video wasn't technically feasible at the time. Reviewing these was very helpful in figuring out what I could do in the heat of the moment to better follow the system I was trading at the time. This allows you to become a neutral observer of yourself and creates a process of improving your trading workflow.

The Solution to Entering Trades Too Early

The best way I've found to convince yourself to stop entering trades too early is actually pretty simple: keep a trading journal.

Start keeping track of your trades in a journal and categorize them by the trading system you're using. Use an additional category for trades you entered too early. Then run a report on the too-early trades. It should be very clear exactly how much your too-early trading habit is costing you. When you see data like this in such a stark form, it will be screaming at you telling you exactly what you need to do to get better. It should be very, very motivating to change the habit.

If it's not convincing enough and you still knowingly enter trades too early, then I would take a big step back and revisit your trading goals. Why do you trade? What is it going to allow you to ultimately do and what are your steps for getting there?

Next Steps

If you want mediocre trading results by taking orders from some Ferarri-driving trading guru, stop reading.

If you're ready to say "screw the gurus" and rely solely on yourself for your trading success, then look no further than my free weekly email newsletter.

Every week I send one actionable tip that you can apply to your trading to create a process for continuous improvement.

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How to Handle Outliers in Your Backtest

2023-04-24T13:30:00-04:00

Outliers are a tricky problem with backtesting. It's not uncommon to see a backtest consisting of nice, consistent profits and reasonable losses but then a tiny handful of trades that are way, way out of the range. Take this backtest which I'm using a scatter plot to visualize which is one of my favorite ways to view a backtest.

There are several thousand trades in this backtest, and 99.8% of them are within a very, very tight range and can be considered "in line" with my underlying premise for this trading strategy.

But look at the tiny sliver of trades that are in the top part of the plot:

Those outsized profits are very much outside of the norm compared to the other trades in the backtest. How you handle these can make a huge difference in your trading results.

For example, if you're coming up with a model to apply to the strategy and determining which levels to use for certain parameters by an optimization process, including outliers in your training set could yield very different thresholds than excluding them.

An Extreme Backtest with a Huge Outlier

In fact, I remember a rather extreme example of this. I was testing a really promising trading strategy that I was really excited about trading live as soon as I could. The backtest looked great and I had all my filters dialed in (or so I thought). This thing was ready to go live and I was just putting the final touches on what sizing I would use. Then I look at the scatterplot and noticed a single outlier. It was WAY out there, but it was just a single trade. No big deal right? Just out of curiosity, I took one final look at the model but excluding that one outsized trade and... uh-oh. Picture that same scatterplot above, but with a single trade ten times as profitable as the largest trade at the top of the chart.

It turns out that if I included that single outlying trade, one of my predictive variables was strongly positively correlated with profit, but then when you excluded that single trade in the backtest (just that one!) from the training data, that same variable was negatively correlated with profit! Talk about frustrating!

So what do you do in this case - exclude or include the outliers? When I looked closer into this extreme case, this one single trade was accounting for a large portion of the trading profits. It was still profitable without the trade but from my modeling perspective, it was fundamentally a different trading strategy without the trade.

A Gift Disguised as a Problem

As you gain more experience with trading and backtesting, you start to recognize these frustrating conundrums as really great learning opportunities in disguise. They force you to confront your assumptions head-on and dig deeper. Why is this trade in the backtest? Is it fundamentally in line with my original trading thesis about why this strategy works? Or is it just randomly happening to match my entry criteria? The bigger question, though: if this outsized "happy accident" appeared in my backtest, could there be an "unhappy" accident in the future with a very large loss?

This situation forced me to confront these hard questions for this particular strategy, but it also gave me a path toward coming up with a framework for handling this situation going forward.

My Framework for Outliers

Take the original scatterplot:

Notice that in this case, there are several outliers and they're all profitable. The fact that there are several AND they're all in the same direction is a good thing. If there were just one that would worry me a bit more.

Take the same backtest, but let's say that some of those outliers are negative and some are positive.

Now let's compare the equity curves for the two strategies:

They're essentially the same. The other thing to note here is that ANY metric you happen to be using to compare strategies would look essentially identical. Profit factor, win rate, CAGR, total profit, equity curve quality, expectancy, Sharpe ratio, Sortino ratio - they all would tell you that the strategies are basically the same.

In general, though, I'd be a lot more worried about this situation. Why? My concern is that maybe my underlying thesis isn't as strong as I thought it was. There's a good chance there's something I'm missing and that's what would keep me up at night until I solved it.

I would really think hard about whether these negative outliers violate or nullify my original trading thesis about why the trading strategy works. In general, I'd be worried that I didn't have a deep enough understanding of the trading edge for this particular strategy and that I was just "blindly following the data" on some level, which can be dangerous.

What's the Big Deal?

You might wonder: why be so concerned? The equity curves are so similar - what's the big deal about the negative outliers? They're dwarfed by the winning trades - so much so that they're barely a blip on the radar when you step back a bit.

It could be a legitimate response when you confront these outliers to still go forward and trade the strategy as-is. But it's important to think about them and expect them going forward. It's much better to confront these before going live with a strategy rather than after.

Imagine the difference between knowing what outliers are possible beforehand, versus trading it unknowingly, sizing up significantly over time, and THEN having an outsized losing trade that you weren't prepared for. That situation could be catastrophic.

Create a Profitable ChatGPT Trading Strategy

2023-04-17T13:16:00-04:00

Unless you've been hiding under a rock for several weeks, you're probably aware of ChatGPT, the chat-based AI service from Open AI. It can do some pretty powerful things, and I use it a lot in my daily tasks. For example, I've replaced 60+% of my Google searches with queries of ChatGPT and it's been a huge time saver.

But can it create a trading strategy? And not just any trading strategy, but one that's actually profitable?

I'm currently trading 15 strategies live that I've created outside of ChatGPT and I've helped dozens of traders create their own profitable trading strategies. After using ChatGPT to create another strategy which I'll show below, I'm convinced it can be used to:

Reduce the amount of time and work it takes to create a trading strategy
Give solid directions to help you improve your trading strategy

Read on to see how I used it to create a simple, profitable trading strategy and be sure to subscribe to my free email newsletter that teaches you how to come up with your OWN trading strategy.

Initial Prompts to Create a Trading Strategy

I first asked ChatGPT a very simple question:

My Prompt: Can you help me come up with a trading strategy to backtest?

It responded in its typical enthusiastic fashion and suggested a Moving Average Crossover trading system:

ChatGPT: Of course! I'll provide you with a simple moving average crossover strategy to backtest. This strategy is based on two moving averages: a short-term (fast) moving average and a long-term (slow) moving average.

Here's the basic outline of the moving average crossover strategy:

Choose a financial instrument: Pick a financial instrument to trade, such as stocks, ETFs, or currency pairs.
Select time frame: Choose a time frame for your analysis, such as daily, hourly, or minute-by-minute data.
Define the moving averages: Select the lengths of the two moving averages. A common choice is the 50-day (short-term) and 200-day (long-term) simple moving averages (SMAs).
Entry and exit signals:
a. Buy signal: When the short-term moving average crosses above the long-term moving average, it's a signal to buy (go long).
b. Sell signal: When the short-term moving average crosses below the long-term moving average, it's a signal to sell (go short or exit a long position).
Risk management: Define your risk management rules, such as setting stop losses and position sizing, to protect your capital.
Backtesting: Use historical price data to simulate the performance of your strategy over a specified period. This will help you evaluate the strategy's profitability and risk.

You'll notice that although the first attempt is a very common strategy that isn't unique at all, the overall plan here is not that bad. All the steps are things that you'll eventually need to do to create your own trading strategy. I wanted something a lot more unique than this though. Here was my next prompt:

My Prompt: That one seems a little simple. Can you suggest another entry signal that is more unique?

ChatGPT Response: Sure, I can suggest a more unique entry signal using the RSI (Relative Strength Index) indicator combined with Bollinger Bands. This strategy aims to identify potential overbought and oversold conditions for better entry and exit points.

Here's an outline of this trading strategy:

Choose a financial instrument: Pick a financial instrument to trade, such as stocks, ETFs, or currency pairs.
Select time frame: Choose a time frame for your analysis, such as daily, hourly, or minute-by-minute data.
Define the indicators:
a. Bollinger Bands: Typically, Bollinger Bands are calculated using a 20-day simple moving average (SMA) and a 2 standard deviation range. You can adjust these parameters based on your preferences.
b. RSI: The Relative Strength Index is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100. A common setting for RSI is a 14-day period.
Entry and exit signals:
a. Buy signal: Look for a situation where the price touches or goes below the lower Bollinger Band and the RSI value is below 30 (oversold condition). This may indicate a potential buying opportunity.
b. Sell signal: Look for a situation where the price touches or goes above the upper Bollinger Band and the RSI value is above 70 (overbought condition). This may indicate a potential selling opportunity.
Risk management: Define your risk management rules, such as setting stop losses and position sizing, to protect your capital.
Backtesting: Use historical price data to simulate the performance of your strategy over a specified period. This will help you evaluate the strategy's profitability and risk.

This suggestion is a lot more unique and uses a combination of two indicators to form an entry signal, a break of the Bollinger Band in addition to a relatively extreme value for the Relative Strength Index. At this point I'm still skeptical, but I decided this was good enough for my purposes, so I decided to continue with this basic strategy.

Backtesting the ChatGPT Trading Strategy

As instructed, I chose my financial instrument to trade. My specialty is trading in US equities, so my plan would be to eventually trade the strategy there, but at this stage of my research into a new strategy, I test it on SPY to get a rough sense of how many trades the system will take, how profitable the trades are, etc. This saves time and you can iterate quickly before applying the strategy to a larger universe.

I mostly trade intraday, so I started on the 5 minute timeframe but after some quick testing decided to move to the 15 minute timeframe for this type of strategy. I chose to focus just on the long side for now. How long will I hold the trades? This type of mean reversion trading system needs some time for the trades to play out, so the idea would be to watch for these entries at the beginning of the day, enter the trades, and then hold until just before the close. Here's the first version of the strategy. It has 628 trades with a profit factor of 1.1 and a win rate of 50.6%. While it is technically profitable, it's nowhere near anything that I'd like to trade.

So I asked ChatGPT how I could improve it.

Improving the Trading Strategy

My Prompt: OK, I'm looking at the Bollinger Band/RSI system you suggested. I'm getting in early in the day and exiting just before the close. It's not really profitable. What filters do you suggest I use to take fewer but more profitable trades?

Here's how ChatGPT responded:

ChatGPT: It’s essential to fine-tune your trading strategy to achieve better profitability. Here are some filters you can consider adding to the Bollinger Band/RSI system to increase the likelihood of more profitable trades:

Trend confirmation: Add a moving average or another trend-following indicator to confirm the overall trend direction. For example, you can use a 200-day simple moving average (SMA). Only take long trades when the price is above the 200-day SMA (uptrend) and short trades when the price is below the 200-day SMA (downtrend).
RSI level adjustment: Adjust the RSI overbought and oversold levels to increase the selectivity of your entry signals. For example, you can use 80 and 20 instead of 70 and 30. This way, you’ll only enter trades when the market is more extremely overbought or oversold.
Bollinger Band width filter: To avoid trading in sideways or consolidating markets, you can add a filter based on the width of the Bollinger Bands. Calculate the Bollinger Bandwidth as the difference between the upper and lower bands divided by the middle band (20-day SMA). Only take trades when the Bollinger Bandwidth is above a certain threshold, indicating higher volatility and stronger trends.
Volume confirmation: Add a volume filter to confirm the strength of the price movements. For example, only take trades when the volume is above the 50-day moving average of volume. This helps to filter out potential false breakouts or weak price movements.
Time of day filter: Limit your trading to specific hours of the day when the market tends to be more active and have higher liquidity. For example, you can focus on the first two hours after the market opens and the last two hours before the market closes, as these periods often experience higher volatility.
Support and resistance levels: Incorporate support and resistance levels into your trading strategy. Look for price action near key support and resistance levels, as they can act as a confirmation for the Bollinger Band/RSI signals. For instance, a bounce off a support level combined with an oversold RSI signal could strengthen the case for a long trade.

The trend confirmation suggestion is probably the best route to take, but for simplicity's sake, I chose the RSI level adjustment. Its original suggestion was to use an oversold threshold of 30 for the RSI. I took its advice and changed the threshold to 20 which should yield fewer trades since the oversold value would be far more extreme.

ChatGPT Trading Strategy Version 0.2 of the strategy at first glance looks worse, but it's actually quite a bit better. There are over 90% fewer trades and the trades that remain are more profitable. When you start applying this to a larger universe that's going to make a big difference.

That's exactly what I did next. Instead of just SPY for my proof of concept, I applied it to one of my lists of 450 symbols. Here are the results for the RSI threshold of 30 which I'm calling TradeGPT Trading Strategy version 0.3:

Starting to look not bad. There are a TON of trades in there though, so let's use a more extreme level of RSI to get rid of a lot of the noise as ChatGPT suggested above.

Here's the same strategy with a threshold of 20, ChatGPT Trading Strategy version 0.4:

While this strategy is not quite tradeable yet, it's pretty impressive progress for just a few minutes with ChatGPT! Some traders won't ever get to even this point with a trading strategy and now you can get to a very good starting point really quickly.

Trend Confirmation Filter

Trends, of course, can mean different things to different traders. My goal here is to come up with a strategy as quickly as possible, so I chose a filter that would be quick to implement and test. The filter is ATRs away from the 200 period moving average. So in pseudocode:

(Entry - MA200) / ATR

Where MA200 = 200 period moving average and ATR = average true range. Why use average true range and not just distance? Imagine a high priced stock like $META (currently $239) versus a low priced stock like, say $PTON (currently $9.26). A $1 move in $PTON is going to be a lot more dramatic than a $1 move in $META. Using ATR like this normalizes that movement. When I looked at this filter, I found that the further away the price was from the moving average, the more reliable the signal seemed to be:

And remember, the dark line is lower, but it has a lot fewer trades so the strategy is significantly improved. In general, I'm looking for a smoother equity curve and more efficiency so although the dark green curve is lower, it's FAR better than the top one because it has almost the same amount of profit with just a third of the trades.

Time Of Day Filter

Another suggestion from ChatGPT was to look at the time of day that the signal occurred. I know from experience that this is typically a good suggestion. Entries too late in the day won't give the trade enough time to play out before the close and I suspect that entries too close to the open could easily turn out to be false positives.

Sure enough, it looks like skipping the first bar of the day makes sense as predicted by ChatGPT - notice the dark green curve continuing to smooth out:

RSI Level Adjustment

ChatGPT suggested looking at the RSI (Relative Strength Index) level for the signal. Let's see if a more extreme level makes sense. Again, at first glance, it doesn't seem that different but it's almost the same profit with only 25% of the trades. The quality of the equity curve is getting better and better.

Support and Resistance Levels

Like "trend", support and resistance are often in the eye of the beholder. It would be impossible to identify exact, custom support and resistance levels for each of the hundreds of trades remaining in this backtest.

I want to be completely automated, so what I would normally do at this point is to start reviewing a lot of charts to try to detect a pattern of general support and resistance that could be tested across all the trades. That won't work for the purposes of this experiment - I'm trying to come up with a profitable strategy using ChatGPT as quickly as I can.

To capture a lot of what ChatGPT is suggesting here with as little time as possible, I decided to look at the range of the previous day. For example, if the entry is below yesterday's low then it might be beyond any support. If it's near or in yesterday's range, it could be more likely that it's running into support which would make it more likely to revert to the mean. To quickly see this in aggregate across a backtest, I created a new data point in each trade to examine. I'm calling this Position in Yesterday's Range:

(Entry - Yesterday's Low) / (Yesterday's High - Yesterday's Low) * 100

A value of 100 means it's right at Yesterday's High. A value of 0 means it's right at Yesterday's Low. A value of -100 means it's below Yesterday's Low by an amount exactly equal to Yesterday's Range (Yesterday's High - Yesterday's Low).

It turns out there is a threshold that makes sense. The entry price needs to be beyond the low from yesterday, but not by an excessive amount.

The equity curve is smoother still - more trades without sacrificing that much overall profit. It's starting to look like something that might be worth trading.

To learn how to create your own trading strategies, sign up for my free trading course.

The Only Time Taking Partials Makes Sense

2023-04-14T15:08:00-04:00

Many of you know how I feel about taking partial profits in winning trades (you probably shouldn't!). To put it more mildly, you should recognize the tradeoff you're making when you take a partial profit. It's not free.

If more traders acknowledged what you're giving up, I believe you'd see a LOT fewer of them taking partials. Since writing that post I've thought a lot about it as I trade and I've found that there's one important situation where I actually ENCOURAGE traders to TEMPORARILY take partial profits.

So when do I encourage it? When you're stepping up your trade size. Some traders have a really difficult time sizing up even when all their results tell them they should be. There's usually a psychological barrier that's hard to break through. That level is different for almost all traders. Some traders will simply never get past it.

If a trader is having difficulty sizing up like they know they should, I'll often suggest temporarily taking some partial profits in some of the winning trades. This can be an important step that allows them to move through the psychological barrier that accompanies trading with bigger size. I always include the caveat that this should be treated as an isolated part of a bigger plan to trade with more size and quickly return to more efficient partial-free trading.

Should you EVER take Partials?

My Approach to Trading with Bigger Size

What's the Trading Equivalent of "Playing Up"?

2023-04-12T18:38:00-04:00

I went cycling recently on what's generally known as the fastest and most challenging ride in town. I used to be a regular on this ride but for various reasons it's been several years since I've done it. Although I stayed with the group for the whole ride, I spent the last half trying as hard as I could to stay attached to the group. There were plenty of moments when I didn't think I'd make it to the end.

At the finish, the first thing I thought was "This is exactly what I needed." A good friend of mine who was an excellent cyclist used to say "It's good to get your teeth kicked in every now and then." He meant that it's always good to ride with people who are way better than you. It will be uncomfortable and you'll be at your limit the whole time, but your fitness will improve dramatically if you make a habit of doing this. You'll achieve a fitness level that's simply not possible to reach alone. This is generally known as "playing up."

Note that this only works when the people you're playing with are in the same ballpark as you. That is, the current gap between their abilities and yours can't be too large or this dynamic won't work for them or you. It's important that the gap be not so large that you don't believe you can hang if you work hard enough.

How does this relate to trading? The first thing to point out is that if you trade in isolation, you can improve but unless you find a way to interact with better traders, then you will improve at a much slower rate.

What's the equivalent of "playing up" for traders? I'd like to hear how readers approach this and I'll add to a future post.

Earnings Season Starts Soon - Are You Ready?

2023-04-11T13:18:00-04:00

How much attention do you pay to earnings season? For years I basically ignored it as it was too close to "news" for my liking. I've changed my tune in recent years after doing some research on earnings announcements and how they affect some of my trading strategies. For some of my models there was no effect but on others, especially some of my gap models, the effect was pretty strong - enough to start incorporating some logic to modify them.

One thing that's always struck me about earnings season is that unlike a hunting season when there's a defined start and end date, there is no general consensus on when earnings season starts and finishes. The other surprising thing about earnings is just how much the frequency of earnings announcements changes throughout the year. Here's a chart for the distribution of announcements. The differences are pretty staggering.

Once I realized that earnings were worth looking at for some of my models, I now incorporate them into what I do and it's one of the things I look at for each new model I research. In fact, I now try to schedule my vacations around earnings seasons.

How much do you use earnings announcements in your trading? Do you ignore earnings or is it a vital part of your trading edge? I'm interested to hear what you think.

The Best Way to Visualize Your Backtest

2023-04-10T15:12:00-04:00

When backtesting, it's easy to get lost in the data. What parameters lead to the most profitable overall strategy? Win rate? Profit factor? Expectancy? All these are, of course, important values to consider and often the most efficient way to backtest is to quickly compare these aggregate metrics.

While these summary stats are important, they necessarily hide a lot of the details about what's contributing to your strategy. The best way to truly understand your strategy is to examine every trade on its own stock chart. With hundreds of trades in a backtest, though, that can be time-consuming and wasteful since most of the trades won't yield any new insight.

You can use an equity curve to visualize these by looking for bumps in the curve, but it will be far more subtle and harder to identify. If there are a lot of trades in your backtest, these bumps might be impossible to detect.

A better way to very quickly visualize all your trades in a backtest is using a scatterplot chart. This allows you to see the outliers at a glance - your eyes are quickly drawn to them. Instead of looking through every chart, you can focus on the trades that are most likely to lead you to insights to improve your trading strategy.

Now that you've identified the outliers, it's time to figure out what to do about them. More on that soon.

What are your Piano Scales?

2022-08-31T12:13:00-04:00

In Talent: How to Identify Energizers, Creatives, and Winners Around the World recently penned by Tyler Cowen and Daniel Gross, Cowen suggests a simple interview question that I’ve been obsessed with ever since I read it several weeks ago:

“What is it you do to practice that is analogous to how a pianist practices scales?”

The answer that immediately came to mind was from much earlier in my career as a budding developer and equities trader in the 2000s: I switched to a computer keyboard without labels on the keys. This change forced me to become a better and faster typist because I was wasting time glancing at the keyboard to find a key. This decision has paid off: the efficiency gains have compounded over the years by, I believe, permanently tilting my productivity curve upwards.

Although I still use the keyboard, that response no longer seems sufficient. Now that I’m managing developers and not writing a ton of code, what are my current “piano scales” that I practice to get better at leading teams? It’s a puzzling question for my present role.

As my obsession persisted, I started presenting Tyler’s question to various folks that I interact with regularly to see how they answer it. I started by giving my team of developers a few days to prepare before we discussed it in our weekly meeting. I asked my good friend Dallas, a successful high-end custom jeweler; the eccentric CEO that I report to at Trade-Ideas; the co-founder and trading coach of a proprietary trading firm; a partner in the private equity space; the lead engineer at a sports technology company; and, of course, I asked Tyler Cowen himself. The responses were as varied as they were interesting.

Tyler Cowen

In classic fashion, Tyler Cowen responded to my email within a couple of hours. “Writing every day. Debating arguments every day. Shooting basketball when the weather allows!” Having followed Tyler’s work for some time I could have guessed the first two, but shooting baskets was a surprise. He said basketball was physical activity and a way to clear his head, but “it also teaches me that I can be doing something for a long time and still be bad at it!”

Dallas Pridgen

I was particularly looking forward to hearing Dallas’ response. Although he downplays his success, Dallas Pridgen Jewelry is well known and he often is commissioned to make custom pieces for movie productions where a trinket plays an important role in the plot. His response to the question was immediate and confident: “I don’t do anything like that: I just do it.” At first, I thought he was skirting the question - surely he practiced countless hours over the years to master his craft. The more I talked to him and thought about the unique projects he’s told me about over the years, I realized that the real value that Dallas provides is not the literal metalworking in making a piece of jewelry - it’s his original design for each piece that uniquely commemorates a moment or relationship. The “piano scales” for Dallas’ work is the process itself and the experience of designing each project continually expands his capacity for future designs.

Joan Mabe

My wife is a vigorously competitive person having coached herself to a long career as a professional runner culminating in an Olympic team. She’s now a prominent high school coach in Chapel Hill with multiple state titles. I was particularly interested in her unique “piano scales” during her time as a competitive runner. She quickly responded with “a running log with the red miles highlighted.” What she described was very different than the modern, automated process of tracking runs with a GPS watch on Strava. Each day she kept precise details of all aspects of her hard workout days and easy recovery runs. The “red miles” were the intentionally hard miles - an interval workout or race - and were tallied separately. The real meat of the log, though, was recording how her body responded to the red miles, constantly gauging the tradeoff between maximal fitness and injury. She credits her extreme attention to her body’s reaction to workouts to her long, injury-free, successful running career.

The Development Staff at Trade-Ideas

Programming software lends itself well to the piano scales question so I was looking forward to this discussion at our team meeting. Phil, the most senior developer in the group, described doing small programming tasks using newer languages that he wanted to be more proficient with. He regularly creates small demos for no other purpose than his own practice and learning. For example, he created a Javascript demo of a ball bouncing around in a room in three dimensions. Another developer, Tim, enjoys “pair programming” where one developer partners with another to share screens and simultaneously code in the same file. Seeing how another proficient developer tackles a technical problem is often very enlightening and the learning goes both ways even when one programmer in the pair is significantly less experienced. Ron, an experienced developer, regularly enters programming contests online to keep his skills current and sharp.

Todd Bolon

My friend Todd is a partner at a private equity firm. He took an uncharacteristically long time to respond to my email - further evidence of the difficulty of the question.

“I think I don't like to practice - I like to learn by doing and will do the minimum of practice (e.g., school) to get where I want to be. Maybe that has influenced where I have gone with my career - things that you can get good at by doing is where I ended up.”

Although Todd has deep technical experience, he has long since leveled up to consulting with leaders of companies who are managing technical organizations. This is several layers removed from a specific craft that would lend itself to improvement by the direct, deliberate practice of piano scales.

Mike Bellafiore

Mike is the founder of SMB Capital, a successful proprietary trading firm in NYC. I know from my years as an automated strategy trader that if there is ONE group that has internalized deliberate practice as a requirement for success, it’s traders. Having mentored many traders over the years in his firm, Mike made an interesting observation:

“The scales probably should be different based on experience. Experienced traders would have a shorter list of scales that take less time. Newer traders would need to do more thorough scales and more of them until they build more skill.”

I can confirm this idea as I think back on my improvement arc as a trader over the years. I’ve kept a thorough trading journal to keep score of my trading strategies for years and it’s been critical for success. Mike also rattled off several other routine practices he recommends for new traders: pre-market prep, a daily report card, categorizing trades by style, mindfulness training, optimizing workflows with technology, and collaborating with other traders.

Brett Steenbarger

Brett is a long-time trader and trading coach and has worked with some of the biggest names on the street. He’s written several popular books on trading performance, all of which easily made the cut for keeping as I culled my bookshelf recently (it was a high bar!). For traders, he recommends reviewing the trading day with not just a simple summary but a bar-by-bar replay. Similar to a football team reviewing game film, he suggests recording your screen and replaying it after hours. You’ll discover things you didn’t notice in the heat of the moment and you’ll start to understand ways you can improve that just aren’t possible without this extremely detailed approach.

Hans Weber

Hans is the VP of Research and Development at SMT, a sports technology company in Durham, NC. Although it took him a while to respond, his answer resonated with me. He makes a point at least twice a year to sit alongside each person involved in the company’s product flow. As he does this he’ll mentor people, see how interactions with clients might be changing, and understand how various workflows are working and if there are opportunities to improve them. Becoming truly in tune with all the pain points in the organization allows him to create ways for R&D to make things more efficient and enjoyable for everyone in the company.

Anonymous CIO

I asked a CIO of a large software development firm in the Research Triangle. She leads an organization of over 1000 software developers. When I asked her about her piano scales, she paused for a few seconds to think of an answer. She decisively responded that the most important part of managing a large organization is listening and having empathy. Having realized this early on, she focuses on this skill every day to cultivate and improve it in herself and the people that work for her.

What Should MINE Be?

I love this question because, like me, so many feel like they should have an immediate and ideal answer but the more you think about it the more puzzling it becomes. Asking others has helped me examine my own systems of improvement in different ways than I otherwise would have.

Should you EVER take Partial Profits? (Scale Out)

2020-11-02T15:14:00-05:00

What is a Partial Profit or Scaling Out?

Taking a partial profit or scaling out of a trade is to exit some portion (but not all) of a profitable position. It is typically used as a sort of compromise: the trader wants to capture some profit but still wants to participate if the position becomes even more profitable in the future.

What a Partial Profit Prevents

You had a plan, you sized your position appropriately, you entered the trade at the right time, and your prediction was quickly realized by the trade heading in your direction. The inspirational sports movie theme music starts playing in your background. Ah the emotional satisfaction of being right! (Cue the music stopping abruptly.) Then the trade pulls back and you're at breakeven. That's ok - probably just a pullback. You have the will power to tolerate pullbacks like these. Then your stop gets hit and a nicely profitable trade turns into a loss. A very different theme music now plays in your background. You did everything right and still took a loss. If only you would have exited the trade while it was still in the green.

This is an especially difficult situation that all traders have experienced. Traders of all levels go through this routinely.

The "Great" Compromise

You're in another profitable trade. You've done everything right and once again you find yourself with a tidy profit - but now you're remembering the earlier trade that was in the exact same situation only to be stopped out for a loss. You know that exiting the trade now would be bad in long run, but you don't want to suffer a similar loss when the trade has come this far. What do you do?

Early on in your trading career, someone made the very reasonable sounding suggestion that you should take half of your position off and let the remainder ride. Now you're playing with "house money" as they say.

What an amazing compromise. The best of both worlds! Take a little here by taking a partial profit and let the rest ride. So sensible! Right?

Partial Profits Cost You More Than You Think

With any trading decision you make there are trade-offs. When you take a partial profit in a trade and it eventually hits your target you'll have less size in the trade and therefore smaller profits relative to not taking a partial.

At what point do you take a partial profit? Is half of the position the right amount? Maybe you just do what feels right in the moment or maybe you have a solid plan to follow.

It's easy to look at a single stock chart for a trade and imagine what strategy would make the most money, but it's much harder to determine what works in aggregate across a lot of your trades. Any single trade is irrelevant - the big picture is far more important.

Here's a backtest for one of the strategies I trade. I ran two backtests - one with no partial profits (the red line) and one with exiting 50% of the position when the trade reached a certain level of profit.

For this particular strategy taking a partial profit results in almost half of the total profit evaporating! This is a devastating chunk of your profits. All trading strategies are unique so they'll be affected differently by including partial profits at different levels - but almost all of them will result in lower total profits. So does this alone put the nail in the coffin of a partial profit strategy? Not necessarily.

Those partial profits are buying you something of value: peace of mind. The psychological comfort of experiencing fewer of the difficult trading outcomes described earlier definitely has SOME value. How much do you value that peace of mind?

Psychological Comfort Has Value - But How Much?

Each trader is different and everyone has a different risk profile. Taking on risk is a personal decision - what makes sense for you might seem insanely reckless to another trader.

How should you think about the value of the emotional comfort of taking partial profits? Let's look at the most common reason: you don't want a profitable trade to turn into a loss.

As traders we love being right - sometimes even to the detriment of making money in the long run. There's something valuable about making SOME money - literally anything above zero - even $0.01 - on a trade. This is somewhat irrational the more you think about it. The profit you make or lose on a trade is a continuous variable - that is, there's a whole range of profit you could end up with. Of course, as traders, we're trying to maximize this number.

When we reduce that continuous outcome to a binary - was there a profit or a loss on the trade - we lose the accuracy of that variable. You're treating a $0.01 profit the same as a $1000 profit - both of these outcomes make the exact same contribution to "win rate." Shouldn't we treat the $1000 winning trade differently than the $0.01 winning trade? Your tendency to take frequent partial profits says you're assigning the same value to a $0.01 trade versus a $1000 trade.

In fact, most strategies for taking partial profits are aiming for creating a worst case scenario of the trade ending up just barely profitable, precisely so the trade ultimately contributes (just barely!) to your ~~being right~~ win rate.

When you rely too much on partial profits, you're optimizing on the wrong variable.

When Partial Profits Make Sense

Even when you realize that you're optimizing for the wrong variable by taking partial profits, it still might make a lot of sense to take them. Here are some scenarios where it might make sense to value the comfort from partial profits more highly on the margins:

You're trading a strategy that has longer hold times - the longer the hold times the more likely you'll be in a profitable trade that eventually pulls back
You trade with size that's large enough to substantially move the market, so exiting all at once is difficult
You're currently in a drawdown and you really prefer to avoid more losing trades even if they're just barely profitable
You trade at a proprietary trading firm and you settle up each month

Any of these situations would make you value peace of mind more highly.

Reversals Will Still Happen

It's important to note that taking partial profits doesn't allow you to completely avoid the situation where a profitable trade turns into a loss. Even when you've carefully chosen your partials strategy by looking at a large number of your trades, you're guaranteed to still experience some of these.

With your partial profits strategy in place, you'll still have profitable trades that almost reach the point where you're taking partial profits only to reverse into a losing trade. It's a situation that you can't completely avoid.

How Frequently Should You Take Partial Profits?

Are you taking partials frequently or even every time a trade is profitable? If this is the case then it suggests to me that maybe your target is too far away. How would the aggregate numbers look if you moved your target closer?

If you can calibrate your target well you get the best of both worlds - trades that hit your target at full position size.

Discretionary Partial Profits

There are some very experienced traders out there that have an excellent intuitive sense of where to take partial profits in the heat of the moment. If you think you are one of these gifted traders there's a way to verify this. Go back and look at trades that you've manually intervened in and compare those in the aggregate to your system. Was there improvement from your manual discretionary exits?

This takes some effort but it's worth it. But beware: if you're like me you'll find that your shrewd trading discretion isn't quite as shrewd as you think it is.

Bottom Line

A strategy to take partial profits is likely to cost you significantly more than you might think. The peace of mind you're buying with them could very well be worth it, but it's important that you analyze why you're taking them and be honest about how valuable it is given the surprising cost in profits.

Make your Journal Compound your Trading

2020-08-17T15:00:00-04:00

As some of you know I coach high school cross country with my wife Joan. At first glance you'd think that running and trading don't have a lot in common, but as with many performance activities there are lessons to be learned from each.

Today the team did one of the tougher workouts of the year (safely socially distanced, mind you) at one of my favorite running venues, Brumley Forest Preserve. The workout is 4 intervals around a 1000m loop (or 3 for the freshman). The pace is steady, steady, fast, then back to steady for each interval. This is one of the 8-10 quintessential team workouts that serve as anchors for us to determine if we're on track to meet our season goals for the team.

We keep meticulous records for these important workouts. I record each time for each interval for each kid in a grid on a sheet of paper along with some notes. These really important workouts we only do once per season, so as the kids progress through high school it becomes more and more important to refer back to previous years' results to track their improvement. This provides a great perspective for, say, a senior who feels like they didn't have the best workout today to go back and see just how much they've improved over the years. Maybe the workout didn't go as badly as they thought it did. It's not only upperclassmen - even the freshmen get a taste by comparing their times to freshmen of previous years.

What we've realized over time that as valuable as the times for the intervals themselves are, the notes about the intangibles turn out to be perhaps even more valuable. For example, on the interval loop there is a small section of clay that you run through. We'd never really taken much notice of it but today it played an oddly important role. It had rained the previous night and the clay ended up having a perfectly sticky texture and caked on the bottom of the runners' shoes on each interval. So at the halfway point of the interval - where the loop bottoms out and gets harder for the rest of the way - the kids' shoes were probably a pound or so heavier over the next 50-100 meters as the clay came off.

It was also oppressively humid today, but not so hot. This is another detail I keep track of on the sheet. And of course each individual runner has significant things going on today that might affect their mindset. Some have just dropped an older sibling off at college for the first time and they're suddenly an only child. Another just had a zoom recruiting call with a division 1 program the evening before and was particularly fired up.

Of course there are a thousand things we COULD keep track of - but what's important?

What's true for high school cross country is also true for your trading.

What's Important Enough to Keep Track Of?

In your trading journal the most important thing is to record the profit from each trade plus the entry and exit time so you can go back to a chart and overlay your trade on the chart. This is the bare minimum and should be your starting point.

Once you start trading multiple strategies (you are or are working towards that, right?), the next essential thing to record in your journal is the strategy that the trade came from. This is really critically important.

It's really hard to over emphasize this point. It's probably the single most important data point in my trading journal. There's really no question in my mind that my trading profits would be FAR less if I didn't track the strategy. Tracking it allows me to:

Your daily P&L - that single number - hides so many details about how your trading is really going and yet that's the only number that the vast majority of traders look at when evaluating their performance if they evaluate it at all. If you have multiple strategies that you're trading with different sizing, then you overall P&L is going to be woefully inadequate for measuring your trading performance.

Beyond the Basics

What are the important intangibles you should keep track of like the weather or the sticky clay in the interval workout today? There is no one size fits all solution - it's going to depend on the strategies you trade and what's likely to have an effect on them.

It's probably not going to be immediately apparent on day one what additional parameters you should be keeping track of. What you should be doing over time is getting better and better at discovering what will be valuable to look back on in the future.

Here are some concrete examples of things I started keeping track of in my journal that turned out to be extremely valuable. These things are very likely irrelevant to the strategies you trade, but should give you some ideas.

Trade Timeframe

When I first started trading gaps, I traded off the 30 minute bars. After some success, I decided to trade the same system off the 15 minutes bars where there are more opportunities. When I started taking these additional trades, I started keeping track of the timeframe that I took the trade off of. In addition to the strategy, I added a timeframe field and used 30 minute bars or 15 minute bars depending on the timeframe I took the trade off of.

Although it's been several years now I remember distinctly how this benefited me. Right away I had a couple really big winners off the 15 minute bars. After 2-3 months though, I looked back at my journal and realized that the trades I was taking off the 15 minutes bars, in aggregate, were performing pretty poorly. This was a shock to me as those initial winner weighed heavily in my mind - I assumed that timeframe was really profitable for me. At that point I quickly took a step back and reevaluated that new timeframe entirely.

Re-entering Trades

With one particular strategy I trade, there could be a trade in a particular stock that I take that stops out pretty quickly, but then another setup materializes in the same symbol. Do you take that trade? It's a question I've thought a lot about (here's a specific example).

Re-entering trades is a really good example of something you should be keeping track of. Was this trade the first attempt of the trade or a subsequent attempt? It's easy to try to draw conclusions from a trade or two but the aggregate is all that matters. Looking back over my journal I see that taking these second or third opportunities actually play out pretty well in this particular strategy.

Is Every Trader Watching This Symbol Today?

Every trading day is different. Some days there's been nothing on my trading radar while other days there's literally been 600 stocks that, technically, fit my criteria. That context is really important. Imagine a trade that's gapping an average amount. If there's 30 stocks that day that are gapping the same amount or higher that stock is less unusual than if there are just 1 or 2 stocks gapping a similar amount.

If there are a lot of stocks to choose from then a particular trade you're making doesn't have every traders' eyeballs on it. If it's the only thing moving then you know that it probably has the focus of almost every trader. Those are very different situations and something I wanted to start keeping track of. I started labeling my trades from this strategy with "Premier" if the stock was close to one of the few symbols in the universe that day. Over time I could evaluate performance on these Premier plays separately from other trades in the same strategy. This is insight that just isn't possible without keeping track this way.

Keep Track of Changes to your Trading System

One of the most important things to record is when you make alterations to your system. For example, you increase trading size, change a rule in your system to take more or fewer trades, etc. It always seems in the moment like I'd never forget making a change like this, but it doesn't take long to forget these things. Wait - what day did I make that change to the system? That is a really important thing to keep track of and I used to overlook it.

What is NOT Worth Keeping Track Of?

There is no limit to what you can keep track of - the amount of data is endless. I often think that trading is mostly about figuring out what you can comfortably ignore. Your trading journal is only going to be valuable if you put thought into it and track things that have a good chance of being important. If it becomes a chore to track a lot of data points that end up being unimportant then you're going to be less motivated to go through the effort.

Here are some things that I purposely don't record in my journal because they didn't turn out to be valuable to me.

Any Data Point You Can Easily Recreate Later

There's really no point of keeping track of data that you'll easily have access to in the future. For example, the amount a stock is gapping, while important, isn't a data point you should devote a lot of keystrokes to recording for each trade since you can easily retrieve this value in the future from any number of data sources. It's great if you can automatically capture it, but if it takes any effort at all I skip data points like this one. Again, it's not because I think they're unimportant - they certainly are - it's that it requires so little effort later to recreate them.

Your Feelings, Mood, Sleep, What you Ate, etc

I know a lot of traders are big on these characteristics of yourself in the moment. Some traders even wear Oura Rings to systematically record sleep patterns and vital health statistics. I like the idea of automatically recording these things, but I've found that any effort to manually record this stuff just doesn't turn out to be very valuable.

The precision with which you'd need to record these feelings and such just doesn't seem possible and even if you could, in my experience, there seems to be little if any correlation with my trading performance. There's just a lot of other things that have actual tangible correlation with a trading strategy that should have priority over this.

Anything that Likely Won't Be Important Later

There are a lot of things that seem really important in the moment in a given trade, but in a month when you're looking back over several trades will not be important. Spend time thinking about what you're likely to want to look back on in the future and just don't bother with the other stuff.

What are some things that you track in your trading journal?

Trader Interview: John Burns

2020-07-08T12:50:00-04:00

The next interview in the series is with John Burns (twitter). John Burns is Senior Consultant and Performance Advisor for the ReThink Group with clients including hedge fund managers, portfolio managers, and traders, as well as Hendrick Motor Sports NASCAR #9, #88, development pit crews. Prior to this role he worked as a floor trader on the Chicago Mercantile Exchange for 17 years. John has traded futures, options on futures, equities, ETF’s on most exchanges worldwide. He has experience with mechanical, discretionary and algorithmic trading styles. Learn more about John through the ReThink Group website and follow him on Twitter @JPBJR800.

What is the most overrated trading advice?

Take the emotion out of trading. Research shows that we can’t make a decision without
emotion. As many of us have experienced the more we try to become emotionless the more
chatter and uncertainty clutter our thoughts. Emotions have energy that needs to be
recognized and vented. The most effective way to vent the energy is to simply say what you
are feeling and why. When this is done and the words accurately describe the feelings the
energy/intensity of the feelings will dissipate. As the energy of feelings dissipates so does
the manic chatter of our inner voice. When we get good at understanding what we are
feeling we are able to see the markets as they are rather than how we want them to be.

What is the most underrated trading advice?

Use emotions, especially "negative" emotions as information. Our feelings have a
productive purpose. Understanding how we feel and why can unlock the power of
unconscious pattern recognition. When we understand patterns of thoughts and feelings
and put them in the context of trading setups and exits we can really start to dive into the
art of trading. When the flow of the market is our guide rather than our demands and
expectations of what the market should do, or what we feel the markets owe us, we can
really trade the market as it is rather than seeing the markets through a lens that is distorted
with the baggage of the past experiences. As we are able to embrace and understand how
we feel and why we are able to be more present and in the moment, therefore being able to
hear and feel what the market is telling us.

What’s a non-trading related book that’s influenced you recently?

I have two for you. The first has helped me a ton on my coaching journey. The Making of a
Psychoanalyst by Claudia Luiz. The second is a great book about how we can use our
bodies to help us understand what we are feeling. Your Body is Your Brain by Amanda
Blake.

Questions for John? Hit him up on Twitter.

Do you know someone who you think would make a good interviewee? Contact me!

Day Trading or Swing Trading?

2020-06-04T11:50:00-04:00

Is it better to Day Trade or Swing Trade? This is one of those eternal questions that every trader has an opinion on. I've thought about this a lot over the years and heard a lot of traders opine about it. There are a lot of reasons to choose one or the other, but I think a lot of it boils down to your initial reaction when you see a chart like this:

Is your initial gut reaction one of hope and optimism that you could be on the right side of this overnight gap when it occurs? Or do you bristle with fear at the thought of being on the wrong end of this when you open your trading screens in the morning? (Personally, it makes me terrified and for a very good reason...)

What is Day Trading?

The definition of day trading is really very simple: when you end you're trading day your account is 100% cash. There might be a whole variety of trades that happen throughout the day for all sorts of different reasons, but you're only day trading if you're flat at the end of the day by design.

What is Swing Trading?

Swing trading is taking trades with the intent of capturing at least one overnight move. The intended hold time can be just one day or many days. What if you're intending to hold for a year? Is that a swing trade? No that's an "investment", though there is no real cutoff for when a "swing trade" held long enough becomes an "investment."

Swing Trading Pros/Cons

More time to capture the move

Since you're aiming to hold at least one overnight, you'll be in these trades for a lot more time than a day trade. Sometimes you're looking for an explosive move and you might be right about the direction of a trade but wrong about the timing. Swing trading gives your trades more of a chance to capture that move that you're anticipating.

Capture the overnight gaps - for better or worse!

Since you'll be holding overnight there's a chance you'll be riding some really profitable overnight gaps. Of course, these gaps can go against you but if you've done your homework you should be on the winning side of most of these gaps in the long run. This is the main advantage and in fact the entire point of swing trading. The overnight gaps are hard for a lot of traders to handle though.

Take advantage of the overall market long bias

One glance at a chart of the SPY for the last decade and it's not hard to recognize that there's a general long bias in the stock market. Swing trading allows you the opportunity to capture some of that natural drift upward.

Less buying power available

You'll get less buying power even at full margin when swing trading. This could be a positive but I view it as a negative since I try to efficiently use my buying power.

Day Trading Pros/Cons

(If you know me well enough you'll know that I feel pretty strongly that day trading is superior at least for my situation. I'm going to list one con and then the rest are overwhelming pros.)

Small accounts in the US are pretty much out of luck

If your account is less than $25k and you're in the US, your day trading options are very limited due to the Pattern Day Trader rule or PDT (you know, for your own good). It can be done but it's definitely a hassle. If this is the case then the scales tip strongly in favor of swing trading.

More buying power via day trading

If you're interested in optimizing your buying power, then there's no argument here: day trading wins hands down. You get twice the buying power from your broker trading intraday than you can hold positions overnight for swing trading.

Get paid on overnight interest versus paying the broker for margin

Not only do you get more buying power, but you essentially get paid to use it versus having to pay interest on margin balances held overnight. When you use margin overnight, you have to pay interest on it. Brokerages compete on that interest rate. It currently ranges from just under 2% (Interactive Brokers) to well over 9% (TD Ameritrade). Again this is the rate that you pay your broker for the privilege of holding overnight using margin.

When you are 100% cash each night (day trading) you get paid interest on your cash balance, like a checking or savings account. Now, the interest rate you get paid isn't what it used to be. When I started trading years ago with a broker called CyberTrader, I was getting paid over 5% on the balance. Today's interest rates are, of course, much less than that. If you check your statements, though, you'll see that it's not zero.

A friend of mine told me the other day: "There are two types of people in the world, those who pay interest and those who get paid interest."

As a cycling enthusiast, there's a good analogy here. Day trading is like riding with a slight tailwind while swing trading is like riding with an annoying headwind. You can ride fast with either a headwind or a tailwind, but the longer you ride the more and more the direction of the wind will add up. Over even a single ride of a few miles, this can be the difference in many minutes of time. For a visualization of how substantial this is, here's a video of a cyclist using a position that very efficiently cuts through the wind.

Your trading account is similar. The difference might not be substantial for a single day or a few days, but over the long run, this will add up to something significant. That's one reason I choose to trade with a tailwind instead of a headwind.

News comes out overnight

Most of the time the substantial news items that will drastically affect the price of stocks you're holding are released outside of the trading day. Of course, this is not always true, but when news (or a certain politically powerful person's tweets) come out during the trading day there will typically be far more liquidity available to react.

When news is usually released there will be little to no liquidity available, so if you need to get out of a trade you literally will not have that choice.

Freedom to take the day off on a whim

This is one of the huge benefits for me for day trading. Since you're 100% cash at the beginning of every day by design, you can literally just take any day off whenever something comes up. This is extremely liberating as often things in life come up that take your attention away from the market. If you're holding positions overnight you'll have far less freedom to make last-minute adjustments to your schedule.

You'll also just sleep better knowing you're in cash and not holding a large position where news has just been released and wondering if you're going to be on the right side of a big impending gap up or down.

Longer the timeframe, the less predictive a model will be

The longer your hold time, the more risk you're taking. Your money is only at risk when you're holding a position. Anything can happen. The stock can be halted, news can come out, any number of substantial (albeit unlikely) events can occur. The longer your hold time the more likely you are to experience one of these events.

When you're trading a system, this means that the longer the hold time the less predictive the model will be over a large number of trades. Trading is essentially predicting the future and it turns out that's really hard. There's enough uncertainty within the trading day, but when you hold overnight that uncertainty is multiplied many times over.

It's easier to short intraday

As I mentioned above, the market has a long bias when you zoom out to a large enough timeframe. This means that the longer your timeframe the easier it will be to trade a long strategy, but the harder it will be to use a short strategy. Selling short is scary for a lot of new traders but I know many short-term trader who make the vast majority of their profits trading short. There's an old expression: stocks take the stairs up but the elevator down. Successful traders understand this.

By limiting yourself to swing trading, you're giving yourself fewer chances to trade strategies that sell short.

Day trading is finite, swing trades can turn infinite

We all have heard this very typical scenario for beginning trades: they enter a trade for one reason, the stock goes against them, and then that reason evolves into "I'm holding this as an investment." There's a strong tendency in humans to want to be right - to sell at a profit even if the numbers say that's the least long-term profitable thing to do.

With day trading, you have a natural limit on the amount of time you can hold a trade: the end of the trading day. You can't talk yourself into turning a "trade" into an "investment" since you need to exit before the market closes. Day trading enforces this discipline in your trading.

The market will give you feedback more quickly

The shorter your timeframe the more quickly you can get valuable feedback from the market. If your trades take 5 days to play out (swing trading) versus 5 hours (day trading) then by definition you are going to get a lot of feedback much more quickly than swing trading. Over the course of just a month, this can be many, many more trades taken - all of which are learning opportunities. How fast do you want to learn?

The math is different now - commissions are zero

When I made my first trade I think I paid about $10 per side. Even at that point commissions had dropped dramatically but now they've literally dropped to zero at all the major brokerages. I remember telling people I day traded and they'd say "I bet you're broker likes you!" With commissions at zero now that math looks substantially better when compared to swing trading. Does that mean your total trading costs are zero? Not by a long shot. I still pay my normal rate at Interactive Brokers for a variety of reasons, one of which is I feel like I'm getting what I pay for.

So although commissions are free, those costs are still born by you in some way - they're just harder to see. But there's little doubt that total trading costs have also gone down in this recent industry shift. Another reason to day trade versus swing trade - the math keeps getting easier.

Which is more profitable? Has to be day trading

Your goal as a trader should be to find a profitable system (preferably more than one) and trade it as often as possible. The smaller the timeframe the more trades you'll be able to make with the buying power you have. This coupled with the fact that you'll have access to more buying power, it's easy to see that day trading has the potential to be far more profitable.

Can you think of other good reasons that should be added to the list? Contact me on Twitter.

My Favorite Trading Strategy Indicators

2020-05-28T12:32:00-04:00

Too many trading indicators on a chart is a sign of mediocrity. Your charts should be nice and clean showing you exactly what you need to see to make your pre-planned decisions and no more.

Many traders take this to heart and have simple charts that aren't littered with indicators, but too many draw the wrong conclusion at this point: that all indicators are worthless. A trader's clean chart is not a recognition that all indicators are garbage - it should represent that the trader has gone through the thorough and painstaking work of determining which indicators are most important to their trading and why. It should represent countless ideas of what indicators make their trading tick and lots of decisions about the trade-offs of including or excluding certain ones. A simple chart should represent the quantifiable tests that have gone into determining which indicators contribute to profit.

Traders spend a lot of time focusing on the event that occurs to initiate a trade (for example, a new high). In Trade-Ideas we call these Alerts. What traders quickly realize, though, is that the filters you use to determine which new highs to actually trade and which ones to ignore are the most important part of a trading strategy.

A lot of traders trade stocks that reach new highs, but nobody trades ALL of them. Most of your time will be determining under which circumstances you take the trade and which ones you skip. This is the meat of your trading strategy and where you should spend the vast majority of your research time.

If you had to choose just one thing to improve in your trading process, it should be your routine for selecting filters. Improving your skills in filtering will compound over time and you'll become better and better the more you do it. Your routine will become more efficient and you'll quickly be able to get from a rough trading idea to an actual strategy that you're ready to risk money with.

The Indicators I Use in Every Strategy I Trade

I have a consistent routine for evaluating and improving trading strategies. The most important part of this routine and where I think most of my personal edge as a trader comes from is determining which indicators to use in a strategy.

If you look across every strategy I've ever traded you'll see lots of different indicators in use. You'll also see some of the same ones appearing in a lot of them - some appear in every single one. Here's the list of indicators (a.k.a. filters) most commonly appear in my strategies. When improving my models, these are the ones I look at first.

Volatility

Although some treat it as a generic term for movement, volatility has a very specific meaning at Trade-Ideas. It's the amount the stock typically moves in a 15-minute period. Does it really matter what a stock does on a NORMAL day when strategies are typically looking for ABNORMAL activity? It turns out it has a big effect. Unusual activity with a stock eventually reverts back to its normal behavior and sometimes that can happen quickly. You'll find that stocks that move more on normal days also move more on unusual days. If movement is what you're looking for you should be looking at Volatility.

Take the two charts above. At first glance, these charts seem pretty similar, but when you look at Volatility, Novavax (NVAX) simply moves significantly more than ZTO Express (ZTO).

Relative Volume

Relative Volume is perhaps the most important filter of them all. Let's say two stocks have traded a million shares so far today. If stock A normally trades 200,000 shares at this point in the day but stock B typically has traded 5,000,000 shares, stock A has a lot more interest from market participants than stock B, relative to what it normally trades. This is, of course, critically important to your trading system.

For stock A a continuation strategy probably makes perfect sense given the volume is unusually large, but for stock B the same amount of volume is unusually small. These are two completely different situations even though the shares traded are equal for the day for these two stocks. The value for Relative Volume alone could be the determining factor for choosing the direction you want to trade a stock.

Take the above two charts. They both have almost the same shares traded on the same day, but the relative volume for BNTX is 0.8 while the relative volume for SKYS is 24. The calculation for Relative Volume at Trade-Ideas is perfect because it is aware of how many shares a stock trades throughout the day. For example, if a stock has an average daily volume of 500,000 shares and by 9:45 am it's already traded 400,000 shares, the Relative Volume value recognizes that this is more significant than if the stock reaches 400,000 shares at 3:45 pm. You can read more about exactly how this indicator works here.

Gap %

A lot of traders trade gapping stocks (including me). Stocks that have the potential for movement have very often gapped up or down at the open. But not all gaps are equal. Take this gap in TSLA yesterday. It's over $18 but you hardly even notice it on the chart.

But then take a look at this gap in EVFM. It's less than $2 but very significant when you look at the Gap percent.

I've backtested gaps for a long time and the value that keeps popping up as a good one to use as a starting point is 3.5 percent. When looking for gaps up, I start with a minimum Gap Percent of 3.5, and when looking for gaps down I use -3.5.

Average True Range (ATR)

The Average True Range (ATR) of a stock has a very specific definition. Like Volatility above, it captures typical price movement. So why do I have two indicators for price movement? They are highly correlated, so surely we can just choose one and simplify things, right?

It turns out there is a subtle difference between the two measures that is quite important for trading systems. The Average True Range is measuring the daily movement of a stock, while the Volatility is measuring the average movement during a 15 minute period. These numbers are highly correlated, but you do see stocks that have higher or lower volatility numbers relative to their ATRs and vice versa.

All things equal, the Average True Range will be a better indicator when applied to a trend type strategy where you're holding a lot of the day or overnight. The Volatility indicator will be better when you're trying to capture a shorter move on an intraday timeframe. I always look at both of these indicators when designing strategies. I'd encourage you to look closely at the definitions and understand what both of them represent.

Earnings Date

There are a lot of news items that can move a stock: upgrades, downgrades, share offerings, splits, etc. None are more consistently important than earnings announcements. Both investors and technical traders are focused on earnings so it's bound to have an impact on your trading system. All things equal, stock movement due to recent earnings is more significant than movement for other reasons.

Trade-Ideas has a fantastic way to filter on Earnings Dates. I use it to determine which stocks are moving due to earnings and which ones are not. I also have scans that show me stocks that are reporting earnings after the close or the next morning.

Here's the cloud link for the Volume Leaders Reporting Soon top list I use and for the Volume Leaders Just Reported top list.

Position in Range

A stock's position in its recent range has a huge impact on its future movement. Take a look at Morgan Stanley (MS).

It gapped up above its recent range. But look at SL Green Realty Corp (SLG):

These are comparable gaps, but these stocks are in very different situations. MS gapped up well above its recent range but SLG is still very much at the bottom of its recent range. The recent trading range is very important to a stock's future price movement and I always look at the Position in Range indicator when evaluating my trading systems. The time period for the range will vary based on the timeframe for your system. For an intraday trading system you should start with the position in today's range but for longer term systems the position in yearly range might be more appropriate.

While I don't use all these filters in each strategy I trade, these are definitely the ones I examine first when researching a new strategy. What are your go-to indicators for your trading systems?

Trader Interview: Brian Lee @BrianLeeTrades

2020-05-19T14:00:00-04:00

The next interview in the series is with Brian Lee (web site, twitter, YouTube). Brian is an interesting guy - a former professional gamer who's been trading full time for 3 years now. He's a systems trader that focuses on small caps and uses risk/reward and R in his trading.

I like how Brian is an open book - he is eager to share his experiences and what he's learned. He's a great example of someone who does really well trading a system with a low win rate (about 30%).

What is the most overrated trading advice?

There are so many but I think the most overrated advice is always the kind that is unactionable. It always irks me when I see advice being given where it sounds irrefutably true, but it leaves the recipient with more questions than answers. An example might be "let winners run". So the question becomes HOW? What underlying systems are the reason you can do so? Be it an indicator, technical setup or simply removing yourself from the equation with trailing. Anything remotely specific would help a trader take action, learn from their experience and make a decision to ultimately let go or work with it.

What is the most underrated trading advice?

Again, there are so many to pick from. I would ultimately say it has to do with the simple mathematics behind a successful and profitable system. Traders often overlook what information their accumulated averages can provide in forecasting their success or failure. What if your system is ultimately unprofitable over the course of 1000 trades and you were working hard each and everyday to improve your executions fruitlessly? I think being able to translate what you've done and then make the necessary adjustments is key. Sometimes the profitable route is not the most comfortable, would you sacrifice win rate in order to succeed? I think a lot of traders want to win above all else and sacrifice their entire expectancy as a result.

What’s a non-trading related book that’s influenced you recently?

Just because it's THAT important, it would have to be Atomic Habits by James Clear despite having read that a year ago or so. Atomic habits works beautifully in tandem with The Compound Effect by Darren Hardy. Acknowledging that the little things you do each day can add up massively over the course of a lifetime is a perspective shock like none other. We all know these simple truths intellectually, but to get it drilled into your psyche is a powerful thing. Nearly all of the little efficiencies in my life were a direct result of these books and those habits continue to prove their worth each and every day.

Questions for Brian? Hit him up on Twitter.

Do you know someone who you think would make a good interviewee? Contact me!

Is Risk Management a Trading Super Power?

2020-05-07T09:33:00-04:00

Every once in a while you'll hear someone make a seductive claim. It goes something like this:

As long as you have good risk management and size your positions properly you can make money with even random trading entries.

Once you start looking you see various forms of this concept everywhere - it's even mentioned at least once in the well known Market Wizard books by Jack Schwager. For the first part of my trading career I believed this. In fact, I made this argument to several people over the years.

After more experience and trading multiple strategies, I no longer believe this to be the case. First some background.

The First Trading Lesson I Learned

My first trading light bulb moment was about risk. When you make a trade you have a certain amount of capital at work, but what I realized was that entire amount wasn't really at risk. Of course, yes, technically it is "at risk", but as you are probably aware if you're reading this, that's not the best way to think about risk when trading.

What you really have "at risk" during your trade is your maximum loss you're willing to take on the trade, not the total amount of capital at play during your trade.

Luckily I internalized this concept before I took my first trade. It's a fundamental building block of every strategy I trade.

My First Trading Strategy

I think a lot about the first strategy I ever traded. I studied very closely Maoxian's dummy trading lessons. There was a lot of valuable information in those trade reviews. (It's no longer on his site but he tells me that he has located an archive that he will be restoring when he gets to it.)

I went to Atlanta to visit my sister-in-law and while I was there I contacted Trader Mike, a well known trading blogger at the time who lives in Atlanta, to see if I could look over his shoulder while he traded one day. He agreed and I watched him trade the open and then we went to lunch and I soaked up every minute with him. He was very open and helpful and encouraging. The one idea that stuck out at me was risk management and proper position sizing.

I went back home and within a few days I started making some trades using this strategy. While I wasn't wildly successful right away, I was mostly profitable those first few months.

I have made major modifications to that core strategy over the years, but it's essentially the same theory and I've traded it continuously for almost 15 years now.

At the time I assumed that risk management was the key to that early success. It was just a matter of time before I could apply proper position sizing to another strategy and it would be successful too.

I Was Just Lucky

I started branching out into additional trading strategies. How hard is it to come up with a random trading idea? Not hard - just come up with any idea and apply proper position sizing to it and it should work - so the theory goes.

After taking this approach with a variety of strategies, I began to realize slowly over time (too slowly!) that proper position sizing wasn't a strategy in itself that could cure any trading idea no matter how bad it is.

I realized that I didn't have some sort of natural, innate ability to be a trader: I was just naively lucky when I started! That first strategy I traded just happened to be one with a solid theory that was pretty stable over time and I just happened to have come across it. What would have happened if the strategy I first traded was, like most strategies, pretty mediocre? To be honest I have no idea what I would be doing now.

It's the Strategy

This point might be obvious to most traders and indeed it does feel weird to even type it: the strategy you trade is really, really important. That first strategy I traded was way better than I thought it was at the time.

The idea that you can take ANY RANDOM entry and simply apply good money management and position sizing and have it be profitable is one of the most common trading myths I see.

Good position sizing is extremely important but it's not going to save a crappy strategy. It is certainly a fundamental requirement for good trading but it is not the strategy itself!

The Worst Market Indicator

2020-04-28T11:38:00-04:00

A trader friend of mine was attending a webinar this week and sent me this chart from one of the slides that was being presented.

The chart clearly shows that there is a wide variety of resulting performance based simply on the day of the week that the trades were initiated on. The data doesn't lie, right? Of course the data isn't outright LYING but it is certainly setting a trap that is easy to fall into.

Here's why the day of the week data trick is so tempting but ultimately meaningless.

The "Data Doesn't Lie" Stage of Trader Development

When you first start trading with a statistical perspective it really seems like a super power and in a lot of ways it is. You can predict the future in some sense. Your backtester is a powerful bullshit detector - a huge time saver when you're honing your trading strategies.

This approach gives you the ability to quickly prove to yourself whether a strategy works or not. It's a quantum leap forward in trader development and very few traders have the ability to even consider getting to this point.

However, at this stage there is a trap that most traders at this level fall into and can never get out of. I call this the Data Doesn't Lie Trap.

I was in this trap for several months many years ago. Having so much data at your fingertips is very powerful, but it's easy to become enamored of the data itself. When a backtest is telling you something, there's a strong tendency to believe it. The data doesn't lie!

Here's what is difficult about this stage: you have to become intelligently skeptical of what the data is telling you. What most traders never fully realize is that while the data doesn't lie, it presents all sorts of false positives that appear to dramatically affect your trading system but are actually completely meaningless.

The problem with the day of the week indicator is that it's very easy to come up with a story to convince yourself that it's meaningful. My system doesn't trade well on Fridays? I bet I'm looking forward to the weekend and a little bit tired compared to other days of the week. My Mondays look like they're underperforming? It's got to be because I'm tired from the weekend and a little irritable.

See how easy it is to fool yourself into thinking the day of the week is super meaningful?

Look at a Random Filter

The day of the week filter is perfectly set up to be one of these false positives. To demonstrate it, let's look at some equity curves from one of my trading systems. For this example I assigned a completely random value between 0 and 1 to each trade in the backtest. It's a random value, so there's literally no reason to expect it to have any impact on the trading system.

But what do we find?

When we look at equity curves based on 5 segments of the random value, you see that one segment seems to be dramatically better than the other segments. Values between 0.39 and 0.60 of our random filter outperform all other values of this filter.

The data doesn't lie, right?

Of course, I chose 5 different segments for a reason - there are five trading days in a week. If you compare the curves from the random value with the curves from the day of the week chart you see that they don't look that much different.

It's very likely that the day of the week filter is just as random as our arbitrarily chosen values in our random filter. But looking at either chart it's VERY TEMPTING to blindly follow the data and draw conclusions from it.

The day of the week indicator is perfectly set up to yield false positives precisely because there are exactly five trading days in a week. If you segmented almost any system into five buckets it would be surprising if you DIDN'T see random variation.

Can Day of the Week Ever Be Valid?

I can imagine some trading strategies that might be influenced by the day of the week. For example, a strategy could be affected by options expiration dates which occur on Fridays. I also suspect that earnings announcements are clustered around certain days of the week which could affect a strategy.

For most strategies, though, including the ones represented in the charts above, the relationship with day of the week will be meaningless.

Let's think about it more precisely though. The relationship might not be completely meaningless, but that's not really the question. The real question is how MUCH of an effect does it have on your trading system? Is the affect strong enough to make trading decisions based on it?

And the even MORE important question is how big is the effect relative to other filters we might want to use in our trading systems?

You can imagine a filter that shows a consistent relationship across time with your trading system, but the effect might be so tiny as to be worthless.

In the chart above, I concocted a hypothetical example to demonstrate. The blue line represents trades that have a slightly stronger edge than the red line using a fake indicator I created with values between 0 and 1. The blue line is very consistently stronger than the red line, but the edge is very slight. Despite the perfect consistency, this indicator would not be a good candidate for creating a rule for our trading system because it just doesn't provide much value since the edge is so small.

How to Make Sure You're Not Fooled by Data

The first principle is that you must not fool yourself and you are the easiest person to fool.

Richard Feynman

The above quote by Richard Feynman is one of my all time favorite trading quotes despite the fact that he was not a trader.

The point is you never really know if you're being fooled by the data! There's no test you can run to make 100% certain that you're making the correct choices in designing your trading system.

Definitely a scary thought! The way I think about it, though, is that it's actually good to have a little bit of doubt in your mind about your trading. A healthy level of humility is actually quite motivating and encourages you to continue to learn and improve your trading. This little bit of worry is the fuel for studying your systems and digging deeper than the average trader thinks is sufficient.

Most people have trouble thinking clearly about uncertainty and risk in general. Understanding and accepting this uncertainty and trading well in spite of it is what will separate you from even the good traders.

What's Your Vote for the Worst?

Do you have a market indicator that you think is totally overrated? Let me know.

The Best Way to Become a Stronger Trader

2020-04-21T11:18:00-04:00

You're trading a strategy that works. Your trading profits are becoming more and more consistent, drawdowns aren't too brutal, and you're proud of what you've created. Congratulations! You've accomplished what untold numbers of traders could not.

This should be one of the most satisfying feelings you feel as a trader. What you might not realize, though, is that this feeling of satisfaction can turn to despair in an instant. The market can change quickly and it doesn't care how much work you've put in to developing your strategy or how long it's been profitable.

If you're trading a single strategy, your trading is vulnerable - no matter how good the strategy is. In order to be successful in the long run you're going to need to trade multiple strategies.

A couple weeks ago I noticed one of my main trading strategies was performing really poorly. It's a short strategy and I would have thought it would be killing it in March 2020 but surprisingly it didn't. After researching for two solid days and trying to figure out a way to adjust it, I ended up abandoning it (at least temporarily).

This was my very first profitable trading strategy that I created all on my own. I've traded some form of this strategy for 13 years! This strategy has put my daughters through college and sent us on family vacations over the years. It allowed us to move houses and has given us freedom.

I hate to see it go, but what would have been devastating is if this was still my ONLY strategy. If this would have happened in 2015 or 2016 when it was by far my main strategy and I had not yet gotten other strategies off the ground it would have been soul crushing.

Here's why.

Don't Fall in Love with your Strategy

When you create your first profitable trading strategy it is strong source of pride. You've literally invented something that creates money! This is fantastic.

The problem is that immense pride in your strategy will eventually make you cling to this strategy longer than you should. There will come a time when your strategy will require major work to continue to be profitable. It might even become completely worthless. It could be happening right now and you don't even realize it.

When it happens, there won't be anyone telling you "it's time! this strategy needs a major overhaul" or "you should scale back your size on this strategy now." It likely won't happen quickly and obviously - it will happen slowly and subtly over time. The change will sneak up on you and the warning signs will be small and easy to explain away.

That pride you have in your creation will be a serious vulnerability. It will be difficult to abandon your strategy or admit that it has become flawed because it has become part of your trading identity. To abandon it will mean on some level that you're giving up on yourself as a trader.

Going from One to Two Strategies is Huge

I think the biggest step a trader can make is to go from one successful trading strategy to two. Because of the psychological issues mentioned above, this step is even harder than creating your very first strategy! As you solidify that first strategy it becomes part of who you are. You start thinking "I'm the kind of trader that trades X."

Once you do that it becomes harder to create a strategy that trades Y.

But the benefits from having now TWO truly distinct strategies are immense. All at once your trading becomes much more resilient to drawdowns since most of them will be more shallow. See these lines in the chart below. You can see the combined equity curve of both strategies together is a dramatic improvement from either of the two strategies alone.

The more subtle benefit, though, is that you'll become less married to your strategies. Instead of having a lot of emotional investment tied up in them, you become a little bit removed.

You become a much more objective observer of your strategies - they need to constantly prove their worth to YOU instead of the other way around. You've got options now!

This step took me 7-8 years to truly achieve.

Your Trading Intuition Improves

Once you are able to get a second trading strategy online, your trading intuition will be far better. There are a lot of trading strategies out there - you can't trade all of them. At this point you'll be much better at evaluating them and figuring out which ideas to pursue with your finite amount of time.

You'll recognize some of the subtleties of what happens when you start trading a strategy live versus a backtest or paper trading. You'll be much more prepared to come up with your third, fourth, or fifth strategy. You'll waste less time on trading ideas that don't pan out because you'll have developed the experience to recognize bad ideas and good ones.

You'll become more like a general manager of a baseball team, having a broader picture about what's best for the long term health of your trading team, identifying strengths and weaknesses and addressing them.

Your trading will be far more robust.

Backtesting the Closing Range Trading System

2020-04-07T11:38:00-04:00

Last week I posted a description of Ken Calhoun's Closing Range trading system. Now I'll go through the process of backtesting the system itself and comparing my theories about what data points would affect its profitability.

A brief overview of the system itself. It looks for a breakout in the first 15 minutes above the closing 30-minute range from the prior day and uses a stop at the bottom of the closing range. Pretty simple:

As I suspected, the system puts out a LOT of trades. Including all these trades produces some pretty poor results, so the question becomes under what circumstances should you take trades. That is, which trades from the system should you actually take and which ones should you ignore?

Is it even possible to find a profitable subset of trades from this system with an equity curve that looks that bad? You might be surprised. Let's take a look.

Which Filters to Use?

I suggested in my last post that the filters that would make the most difference in this system would be:

The height of the closing range
Volatility
The opening gap/immediate trading action

So let's look at each of these.

Height of Closing Range

When you look at the height of the closing range you see that it has increasing profitability the larger the value is. Here's a chart of the equity curves for each range of values.

The purple line represents the trades with the highest closing range height values in the trade set. The smaller the values, the worse the trades.

Volatility

One filter I look at in almost every system I examine is volatility. How much does this stock move normally, outside of the day in question? Stocks that typically move more, in general, are more profitable to trade. But wait - we're trading this event that's already unusual by definition - does it really matter what it does on a normal day? Why?

Because stocks tend to revert back to their normal character, so even on unusual days this tendency will still exist. Given the fact that this trading strategy has relatively few requirements for "unusualness" anyway, it will likely revert to normal even more so. Here I use Average True Range (ATR) for my measure of volatility.

Notice that the highest levels of values for the Average True Range are the most profitable (the purple line). All lower values tend to be grouped together. Also, note that all these lines each represent the same number of trades.

Opening Gap%

I thought that the opening gap would be important for this trading system. Imagine a large, meaningful gap down. Just how important can the closing range from yesterday really be in that situation? The more meaningful the gap, the less meaningful the closing range.

Sure enough, you see another strong correlation here. Literally the bigger the gap the worse the trades perform. The smaller gaps represented by the red line are actually starting to look like a system you could trade!

What to Look at Next?

There are other filters I'd want to look at next, but I believe the improvement gains from additional filters would be smaller and less obvious.

What other filters do you think would be worth examining? Let me know in the comments and I'll try to test them and post an update.

Ken Calhoun's Closing Range Breakout System

2020-03-23T11:47:00-04:00

In the April 2020 issue of Technical Analysis of Stocks and Commodities magazine, Ken Calhoun outlines his Closing Range Breakout trading system. Ken is on Twitter and tweeted this interestingly prescient market call on January 24:

Not bad actually.

In this post I'll outline the Closing Range Breakout strategy, provide some commentary, and offer some thoughts on how I would modify it if I was forced to trade it.

The System Details

This intraday system is based on two days of trading - it's a combination of the range of the last 30 minutes of trading yesterday, plus a modest gap down today below that range. If that occurs, then you're looking for a breakout above the top of the range from the last 30 minutes yesterday and you're placing a stop at the low of that range. Here's a chart that is included in the article that makes it easy to see.

For this example, the closing range yesterday (2/7/2020) for AMD was $49.65 - $49.98. The next day (2/10/2020) it gapped down slightly opening at $49.47. It quickly went above the high of yesterday's closing range ($49.98) so here is where you'd go long. You'd put a stop underneath the low of the closing range at $49.64 or so.

There's no mention of a target or a hold time in the article, but it seems reasonable to assume you'd be holding until at least the close.

Ken mentions that high-frequency algorithms typically use daily open/high/low/close values so this technique allows you to gain some "price improvement" by getting in before it hits the daily high. He also mentions that he often uses an additional strategy to scale into this trade later. (If you know me you know how skeptical I am when people mention how gracefully they scale into trades.)

Is This Strategy Worth Pursuing?

Most of the strategies I read about I'm highly suspicious of. I actually think this one might be worth further study. There are a lot of details missing (hold time?) and he does include some apparent rules with no detailed explanation. For example, he actually uses $50.20 for the entry above and provides the arbitrary explanation that "$50.00 + $0.20 = $50.20". He also mentions that it is "best" if it takes less than 15 minutes for the range breakout to occur, but no mention of what he considers "too late" to take the trade.

Ken also mentions that this is a relative strength play, but the volume on the entry day is not particular strong compared to the previous day. Here's a daily chart of AMD with arrows pointing to the entry day.

Although a perfect description isn't included, there are enough details to warrant researching this idea further.

Next Steps for this Strategy

It's important to know your trading style and what is in the realm of possibility for you to trade. The very first question I ask myself is how many trades per day does the system generate. Without doing any backtesting my guess is that this system likely generates a lot of trades since the rules that were outlined are fairly loose, especially given the apparent lack of minimum volume requirements.

I'm looking for trading systems that, prior to any filtering, produce a lot of trades. There are a variety of reasons for this, but it boils down to the fact that with many trades to start off with, I know I'll be able to selectively filter the trades down to the most profitable ones and still have it trade frequently.

The good news is that this strategy should be pretty easy to generate a backtest for. The rules are clear enough and not very complicated.

After generating the backtest I'd want to look at two different things right away:

The Height of the Closing Range

Because the closing range constitutes the entire setup of the trade, it will likely have a dramatic effect on the system. Also, we're not talking about the opening range which is typically wide - sometimes these closing ranges can be really tight. If that range is tight then any setup you enter the following morning is going to have a stop that's really tight too. There will be plenty where that distance is prohibitively tight.

There will also be stocks where that range is really wide - too wide to make a profitable trade since the risk/reward ratio will not be suitable.

The Opening Gap and Immediate Trading Range

The second aspect that will likely be very important to the profitability of the system is the opening gap and the first few minutes of trading prior to the trade signal.

Recency is really important to think about when evaluating trading systems. What do I mean by that? In general, the more recent action is typically the most important. For example, which is more relevant to your system: yesterday's opening range or today's opening range? Of course today's opening range because yesterday's opening range is old news at this point. This is true for a lot of indicators too. Which is more important: the 50 day moving average or the 200 day moving average? A lot of traders look at both but if I have to choose I'm going to concentrate on the 50 day since it describes more recent action.

The most recent action prior to the signal will give you the most clues about profitability. The gap distance will be very important. The gap would definitely need to be modest. Defining what "modest" means for this system would be top priority. A large gap down followed by a breakout would mean price has covered a lot of distance in a short amount of time and I'd worry that the "move had been made" already. Notice even in this well chosen example the trade comes close to stopping out after just a few minutes:

Ponder the System's "Theory"

A big mistake that a lot of traders make is they don't think deeply about the trading system "theory". When I first started backtesting I would often make this mistake. It's tempting to simply follow what the data tells you. The data doesn't lie, right?

What you realize with more experience is that while it's true the data doesn't outright lie, it frequently misleads. Fast forward to the point where you're trading this system and an inevitable drawdown comes. You need to be able to believe thoroughly in the underlying theory of your system to trade through that drawdown. If you don't you'll likely give up.

My biggest worry now about this particular trading system is the closing range itself. What's the theory behind why that range is so important? The system is really putting a lot of importance on it - after all the breakout and the stop is 100% defined by that closing range. I know from experience that price does a lot of aimless drifting during the last half hour of trading. You can always optimistically concoct a story about why that range is important enough to create a trading system around it. Right now I'm not convinced that there's a compelling story. I would spend a lot of my research time pondering this question with a very skeptical stance.

Is it Tradeable?

I'm not sure but it seems worth looking into. Even if you don't end up with a tradeable system, this type of research can be very valuable. You'll pick up some tendencies and notice some behavior trends that you can use to apply to other systems.

What other factors would you look at with this system? Are there modifications you'd make to make it more profitable?

3 Things You Can Do to Trade Profitably During CoronaVirus

2020-03-16T14:08:00-04:00

The volatility we're currently seeing in this market is enormous and marks a huge change from what feels like a very short time ago. Just look at this chart of SPY and it's easy to see how things have so dramatically changed.

I've done tons of research into understanding how my trading systems work and knowing what factors affect them. When the market has changed so dramatically though, how valid can all that research really be? How much weight do you place on the recent market action versus the market history up to that point? Of course the market has changed - does that mean my trading systems have changed too? By how much?

These are somewhat philosophical questions that every trader will handle differently. Some trading systems are highly sensitive to the overall market while others are more resistant to it. Here are some things I do after hours or on the weekends to prepare answer some of these questions.

1. Update your Backtests with Recent Data

Remember back when March Madness still existed? Imagine filling out your bracket and trying to make the best predictions you can while only looking at the first half of the season. The most recent games are OF COURSE the most important! Ignoring them would be insane. That is what it's like when you make trading decisions based on older data.

Now is the time to update your backtests so they contain the most up to date information including recent trades and various data points from the overall market that you think might be important to your systems. I spent the weekend updating all the backtests for the systems that I trade. This gives me as complete a picture as I can reasonably create.

2. Compare Performance to Similar Historical Markets

This is something I do routinely, but the change has been SO drastic that it's hard to find ANY similar historical market. If you look hard enough, though, you realize that literally every trading day is different. Look at the candles identified by the blue arrow in the chart below. Generally speaking the candles are similar - pretty small and mostly green. Even during this period of what seems like consistency you'll find lots of variation from one day to the next and one week to the next. This should worry you during "normal" times but during times like this with high volatility it makes me worry a little less.

Here's what I do to compare to similar markets of the past even when no similar ones REALLY have occurred.

Data Points that Describe the Current Market

It's tempting to look at a data point like Average True Range (ATR) - a popular indicator to determine volatility. Here's a ten period ATR for SPY with the values for each day plotted according to the year it occurred. You come away with the impression that this market is roughly twice as volatile as even the 2008 market. No other market can even compare - yikes!

The true picture is more complicated though. The SPY, of course, is much higher now than it was in 2008 so a 2 point swing in the market in 2020 is nothing but in 2005 there were hardly any days with that much range. When you look by ATR as a percent the data looks much different:

The market from 2008 and 2020 have now flipped! 2008 looks way more dramatic than the current market. You'll also notice that although there weren't as many volatile days since 2008, there are still some useful periods in recent years to compare to.

I've spent a good bit of time looking at my trades during the periods in 2015, 2016, 2018, and 2019 where the SPY ATR percent was greater than 2. Some of my trading systems did well during these periods, others poorly, and for others the performance was about average. Going through this process gives me a much better perspective on the current market. I can make decisions with more confidence. For example, I know which of my trading systems I should be trading with bigger size now and which I trade smaller or not at all.

In addition to ATR percent, I'd suggest taking a look at the market's position in its recent range and look for times where ATR percent was relatively high AND the market is very low in its recent range.

3. Do as Much Prep as you can After Hours

When you're looking for unusual situations to trade - like stocks gapping up or down - what do you do when EVERYTHING is gapping up? These recent days have put me in exactly this situation and it's something I thought I was prepared for. Last Wednesday I tweeted this:

Tomorrow there are going to be even MORE candidates for one of my trading systems. How am I preparing for this so I'm not overwhelmed like the other day? After all, if there are a lot of candidates on some days for your system, those are the days with a chance of being very, very profitable. Plan for them since they don't come very often!

Here's what I do. I know that there are certain factors that correlate highly with the profit of my systems. Relative volume is a good example for one of my systems but for others that value is not as important.

Normally I'll take all the trades that my system spits out, but on the rare days where there are more trades that I'll be able to take I'll only take trades that rank highly on the most important factors for that particular system. For each of my strategies I have an alert window in Trade-Ideas. Those are alert windows for "normal" days. I also have prepared alternate windows for each of the strategies for "busy" days. These busy day windows have more restrictive filters, so if I have to choose between trades I can quickly execute my pre-planned strategy for making that decision rather than having to make a decision I'm not prepared for.

In addition, I already know that tomorrow there will be a VERY LARGE number of candidates in one system. Normally I look at the premarket action to determine what to trade which on regular days I have plenty of time to do. There will not be nearly the amount of time necessary to do that when there's 12 times the number of candidate though!

There are some factors I can look at NOW (on the weekend) to plan ahead though. What I normally do just before the market open I'll do this weekend - whittling the list down to a manageable number of candidates before the time comes. This is a really valuable exercise not only because I won't have to skip trading like I did on Wednesday. It also forces me to learn more about this particular trading system. For example, perhaps there are some trades in the system that I should exclude entirely even on "normal" days. Or conversely, maybe there are trades I should be trading with bigger size. Maybe I'll find some trades that don't quite meet the system's criteria but with a small adjustment I could include them, adding more profit to the system overall.

5 Simple Questions for Your EOD Trading Review

2020-03-11T10:49:00-04:00

You can prevent trading surprises by asking yourself 5 questions at the end of every trading day. But first some motivation for why.

It was pretty obvious just listening to it that we needed a new refrigerator. It sounded more like a clothes dryer than a fridge. As if the loud boisterousness wasn't enough, every few months I would find a puddle of water in front of the freezer. I would roll my eyes knowing I had to clear the line from the freezer to the drain pan because it was clogged - again.

You would think that these subtle clues would have been enough to inspire us to replace it with a new one. When we'd settle on one I'd look at the reviews - not exactly confidence inspiring. Literally every refrigerator on the market, no matter how good the average ranking is, has some absolute horror stories among the one star ratings. We did, finally, take the plunge and got a new fridge a few days ago. I didn't realize it when I placed the order, but it turns out that was the best decision I made in a long time for a reason I was completely unaware of.

I showed the delivery guys in and pointed to the existing fridge although I could have just told them to use their ears and follow what sounds like an airplane taking off. They pulled the fridge back from the wall to get it in position to remove and I heard one guy say "uh-oh - you've got a problem."

Our fridge had been leaking from the water line for some time. Yikes! The boards in our hardwood floor were starting to buckle and I worried that I would have to replace these like I did in our bathroom about a year ago. How unlucky! As I looked closer and inspected the damage I realized that we weren't unlucky at all but the decision to replace the fridge now was so much better than I initially thought for a reason I had no way of knowing at the time. Buying a new fridge now had allowed me to see this hidden issue before it became bad enough to require a major repair.

The Fridge Teaches us a Trading Lesson

What can we learn about trading from this lucky refrigerator incident? All of my trading strategies have various levels of automation. I haven't manually entered a trade in my brokerage platform in many years. They're all entered automatically with the correct size and all predefined stop orders and target orders eliminating my all-to-often human error.

The ease of trading this way gives you more capacity as a trader. Since you're not calculating position size in your head and then fumbling around in a clumsy interface to enter orders, you free your valuable time to trade more profitable strategies. The math is simple: if you can manually initiate a trade every 30 seconds but since you can automatically (or semi-automatically) enter them every 5 seconds (or even 0 seconds) then you have more time to enter more trades in a small amount of time.

I highly recommend this approach and have spent the better part of a decade automating all my strategies to the fullest extent possible.

Remove discretion, eliminate mistakes, increase your trading capacity - what can go wrong? Sounds like nothing but positive outcomes can occur, right? While this is mostly true, there is a hidden downside that you need to be aware of: increased risk of neglect.

It's easy to set up the automation and forget about it and that's what many traders imagine automated trading to be. But that's not the case at all. Trading strategies are not static because the market is always changing. For example, here's a chart of SPY from fall 2019 to the current time - a great example of a stark change in the overall market. Do you think your trading strategy behaves the same way in these two distinct market types? Doubtful!

You should understand how your strategy performs in different market types and look for clues along the way to challenge and support your theories. The continually changing overall market is just one of the many things that can cause your strategy to change over time. This most recent market change was obvious to everyone but a lot of changes can happen very slowly over time and, like my refrigerator leak, are barely noticeable at all.

Find your Trading Leaks Before they Become a Problem

Automated trading is not automatic. It's not like adding auto-pay to your monthly water bill and forgetting about it. It's more like adding auto-pay to the family cell phone bill with 7 teenagers without an unlimited data plan - it requires diligent monitoring.

I resist the urge to watch my profit and loss numbers throughout the day, but I religiously do a trading recap every day after the market close. Here are a few of the items on my checklist:

How did I trade today? (Note: a very different question than "How much money did I make today?")
Did my strategies perform as expected? Better? Worse?
How does the backtest compare to the actual trades in my live account? Were there significant differences? Why?
Did I miss any trades that I should have taken? If so, can I make an adjustment to take those missed trades in the future?
Were there profitable trades that almost met my criteria but didn't? If so, can the strategy be adjusted to capture them in the future?

Having a checklist of questions to go through at the end of every trading day will force you to keep tabs on your strategies and identify refrigerator leaks before they become a major problem. We have a tendency to look only at the top line P&L for the day but this hides a LOT of important details. As a bonus, this daily review is also fertile ground for generating new trading ideas for research and continual trading improvement.

Is Running out of Buying Power - A Good Thing?

2020-03-05T15:12:00-05:00

Just a few weeks ago my phone rang and I had a conversation that, unbeknownst to the caller, took me back 23 years ago to when I graduated from The University of North Carolina at Chapel Hill. The caller was my daughter's good friend who had just graduated from college last spring. He had recently started a job in New York City and seeing as I'm the "finance guy" in our family, called to pepper me with some investing questions. He wanted to get started off right.

These questions were eerily familiar. I was happy to talk to him and impart what knowledge I could to a millennial who was not accustomed to using phones for actual conversations. He was particularly interested in which brokerage I thought he should use and didn't really like my first answer ("it doesn't matter.") He insisted on pinning me down, so I recommended Schwab for his purposes.

After we hung up I had the bizarre feeling that I had been through this before - but on the opposite side. In the spring of 1997, I was the one asking these "important" questions, getting advice from various people in my life to invest the tiny amount of money I'd somehow managed to cobble together.

Most of the memories of the investing "wisdom" I received is now very foggy and vague - 23 years of time will do that to memories (or even a much, much shorter amount of time if you ask my wife). I do, however, vividly remember one piece of advice that was insistently repeated by multiple people I looked up to: avoid at all costs, no matter what, the dreaded margin call.

Getting a margin call meant something had gone horribly wrong and you had been completely irresponsible to have let it happen. A margin call was literally a scolding phone call from your broker and it meant that you were using margin and had run out of buying power in your account; it was time to either add more money or inconveniently sell some existing holdings. Shame on you!

It took me several years of trading to come to the realization that this is exactly the wrong way to think about buying power. Here's why.

Efficient Use of your Capital

First, let's take a look at an extreme case. Let's say you have $250,000 in your brokerage account but you only bought 1 share of AAPL and held it for a year. Apple is trading at $313 right now, so you have $313 at work in your account. That leaves $249,687 of cash in your account ready to be somehow invested. You're using 0.12% of your capital in this account. If you add margin to the mix it's even less than that!

We can all agree that this scenario is a very inefficient use of your capital. You're wasting most of the money in your account when you could be doing something else with it.

Use as Much Buying Power as you Can

You want to allocate your capital efficiently. Everyone likes efficiency, but what does that really mean for trading? Efficient use would be using 100% of the buying power in your account at all times, including margin. It turns out that "maximum efficiency" is also an extreme case - the exact opposite of our example above. In practice you won't be able to know what trades are coming your way so you won't be able to allocate the precise amount required to trade them. You'll need to come up with a decent approximation ahead of time.

Estimate the Capital Required

You should have some idea of the types of trades you'll be making. This is the hard part for the vast majority of traders - coming up with the trading system you'll trade. Let's assume though that you have a loosely defined trading system in mind. In theory you could come up with a simple estimate by using this formula:

max shares * max stock price * max trades per day = max buying power required

In reality, though, this calculation will overestimate the amount ACTUALLY required. Why? Because it's highly unlikely that you'll ever run into the situation of using the max share size for all the trades on a day where you reach the max number of trades for the highest priced stocks that you'll trade. This is so rare that it's not worth planning for anyway. Think of the value for this calculation as the upper limit.

I hesitate to recommend winging it, but in this case a reasonable approach is just to make a guess and use that amount.

How Do I Know if I've Run Out of Buying Power?

I remember the first time I ran out of buying power when trading. I was using the old Scottrade Elite for my trading platform at the time. (Anyone here old enough to remember that platform? Let me know in the comments!) The status messages for orders were neatly tucked away making it very difficult to find out why an order didn't execute. I didn't even notice until minutes later when I glanced at my P&L and I was still breakeven when I should have a tidy profit from the trade I had assumed I entered. My first thought was there was an error with the platform but after calling support they told me I had run out of buying power. I instantly remembered the financial advice from my college days and hung my head in shame. How could it come to this! By the time I realized this the profitable trade had already passed me by - even more frustrating!

It's good practice to try to visualize this scenario before it happens and come up with a plan for when it occurs. You'll need to make some split second decisions about what to do. Here's what happens in Trade-Ideas Brokerage+ when you run out of buying power. Your order will be rejected and will have purple lettering. Look for the Error Reason column - it will say "Not enough buying power." In the example below I put in an order to buy 100,000 shares of AMZN and, of course, it was rejected due to insufficient buying power. Note that this is another extreme example - luckily none of my trading strategies will ever call for buying this many shares of such a high priced stock!

Consider when you're likely to run into this. It's not when you're just casually monitoring your positions - this will happen exactly at the point where you're eager to get into what could be a profitable trade. Don't take it personally! If you're not prepared, it can easily create a situation where you'll make a costly trading mistake - or even a few in a row.

OK You've Run Out of Buying Power - Now What?

When you actually do run out of buying power as you try to open a new position, you'll have three options of what to do about it, each of which are perfectly valid choices.

Doing nothing is probably the underrated choice here. You'll likely be pretty frustrated and ripe for making a costly error here. Stop entering new trades for the day and just let your existing trades play out - a safe choice.

The next option is pretty simple - just reduce the size of the order you're trying to enter. For example, instead of buying 1000 shares use 500. This has the advantage of taking your intended trade as planned. It's possible that doing this will allow you to slide just under your buying power limit.

The third option is the most time consuming and requires some quick decision making: exit or reduce size of an existing position. It sounds simple but in the heat of the moment it's really easy to make a mistake so it's worth going through the motions and coming up with a plan outside market hours.

You'll need to quickly determine which of your positions are contributing the most to your buying power consumption. If you exit a position that isn't consuming that much buying power it may not help at all. I've had this happen before: I just started exiting my positions one by one until I got under the limit but I ended up exiting ones that contributed a negligible amount, so I ended up getting out too early from several profitable positions.

In my experience, there's usually just one or two positions that contribute the overwhelming majority of the buying power. Being able to quickly identify these positions can be the difference between getting into the profitable trade you're trying to enter and missing out. The trading platform I use (Trade-Ideas Brokerage+) includes a column called "Exposure" so I can sort my positions by how much buying power they're consuming. This feature allows me to quickly identify those positions and reduce size or exit them quickly.

Read more about Trade-Ideas Brokerage+ and why I use it to enter all my trades.

Monitoring your Buying Power

The above graph shows my buying power available as a percent of total buying power over the course of 10 months of my trading. Notice the red line doesn't ever go to zero. That doesn't mean I've never run out of buying power. The red line only needs to fall to the point where your next trade would consume more than what's currently available. So many of those downward spikes in the graph represent points where I was essentially "out of buying power" even though technically there was some level of buying power remaining in my account.

Note also that there will be plenty of points where you were "out of buying power" but you wouldn't know it because there happened to not be another trade you were attempting to make that would have put you over the limit. This graph gives me a long term picture of my buying power whether I had rejected orders that made it obvious to me at the time or not.

I WANT to run out of buying power occasionally - not every day of course but somewhat regularly. It's not something to dread - it's a sign that you're efficiently using your capital but also a gentle nudge suggesting there might be ways to slightly modify your strategies to use less capital.

What if you NEVER Run out of Buying Power?

If you're never run out of buying power, then that's great! Or is it? Remember our extreme example above of buying 1 share of AAPL in a $250k account? It's not just sub-optimal but it's actually quite risky. The most basic unit of risk in trading is your account. You can theoretically lose all the money in your account but not more than that.

If you're not running out of buying power even occasionally then you should consider that your account might be too large. (A great problem to have, by the way!) Think about it: if you're not running out of buying power then by definition some percentage of your account is not required to execute your trades. That excess money is only earning interest - but otherwise is not working on your behalf. Is there something else you could do with that money that would be of better use to you? I suspect there is.

I keep close tabs on my buying power consumption over time and if I DON'T run out of buying power routinely then I see that as a problem that needs to be addressed. Here are three options you should consider if you're in this situation:

There is no right answer here - these are all personal decisions that are highly dependent on your current trading situation.

But - when you do run out of buying power, consider it a pat on the back rather than a scolding.

Trader Interview: High Patterns Chart Group @HCPG

2020-03-02T14:59:00-05:00

The next interview in the series is with the High Patterns Chart Group (web site, twitter). These guys have been around forever. Their service has a unique blend of important daily points that coincide with intraday setups. They will stalk particular setups in stocks for many weeks, patiently waiting for them to materialize. They are unusually focused on trade execution.

I appreciate the no frills quality of their web site. This post on not catching every trade provides a good window into their trading philosophy.

What is the most overrated trading advice?

Any vague advice like "You’ll never go broke taking profits".

Yes, that’s true, but you’ll also never make any real money until you learn to sit on profitable swings and only sell when they fail the trend parameters from the original plan. If you look closely at trading aphorisms you will notice that they actually start to contradict each other at different points of the trading time-frame. Some advice is fantastic for short-term trading but terrible for position trading. Advice without specifics of time-frame has little value.

What is the most underrated trading advice?

Risk management is the most important trading advice we can think of but it’s not underrated - it gets a lot of love from every professional trader we have ever met. For most underrated trading advice we would say "Become a master of a few solid strategies and really get to know well a dozen liquid stocks." We often see new traders skip from one strategy to another becoming a jack of all trades and master of none. Trading is a ruthless business and to be a jack of all trades will not cut it in this profession. You need to have an edge; for us the edge is to stalk often the same set-ups for weeks and when they trigger use a handful of strategies we know very well and have used now for two decades.

What’s a non-trading related book that’s influenced you recently?

I usually read non-fiction but was given a novel as a present a while back that I thought was exceptional: Station Eleven by Emily St. John Mandel. Story is set in a post-apocalyptic world in which a virus (the Georgian Flu) has wiped out most of humanity. It’s ultimately a text on human resilience and adaptability and how lives are intertwined across catastrophes. Well-written, poignant, and a joy to read.

Questions for HCGP? Ask them on Twitter.

Do you know someone who you think would make a good interviewee? Contact me!

Trader Interview: Sunrise Trader @SunriseTrader

2020-02-20T14:59:00-05:00

The next interview in the series is with Sunrise Trader. He's one of the best traders to follow on Twitter and I highly recommend you check him out. He summed up his Twitter purpose quite nicely just the other day:

Scroll through his feed and you'll find a lot about his trading plan along with nicely marked up charts but also daily inspiration and quotes that make him a joy to follow. I'm really pleased that he agreed to do an interview because I knew he'd give some excellent answers. I love his detailed and concise explanation about money management, an absolutely critical skill for any trader.

What is the most overrated trading advice?

"Complexity/logic and the belief a trader needs to know it all."

The market is not based on logic and complexity. It is based on human emotion and the current market participants' thoughts and actions. A trader must keep in mind that it is not the news or earnings release that is important. It is the reaction to the news or earnings release. Reactions are often different than what logic might think.

Many want to know all things trading. It is next to impossible. What a trader should do is hone their skills to one or two types of setups and have the patience to wait for those setups to materialize.

Traders need to keep things simple. Keep their trading plan, charts and methods simple. Don’t overthink. Traders need to trust in their process. Once a trader finds a system that works for them, they need to wash, rinse, repeat over and over again.

I often say: Plan it, set an alert, see it, trade it. See it first. Use your eyes.

What is the most underrated trading advice?

"Risk management"

Many come to the trading business thinking about all the money they want to make, when what they should learn right out of the gate is how much money can be lost and a formula for how many shares can be purchased.

As traders our #1 job is risk management/money management. If you take the time to learn money management, you will be ahead of 90+% of new traders in my opinion.

You need to ask yourself and plan with these primary questions in your mind each time you place a trade:

Now for some math, you start with an account of $10,000 and you want to buy a stock that is trading at $50 per share. How many shares can you buy? Hint: it is not 200 shares. First, you need to decide how much per share you are willing to risk. Let’s say you settle on $10, really? $10 x 200 shares = a loss of $2k or 20% of your account. Do this just a few times and you will see an account balance of ZERO.

To find out how many shares you can buy, you must calculate using a % of your total account. Traders who are successful will often risk up to 2% of their total account on each trade. 2% of 10K = $200 dollars. You now decide, based on your stop, what the risk per share will be. For this example, your stop is $2 below the purchase price. You are willing to risk a total of $200 (2% of your total capital)/a stop of $2 means you can buy 100 shares. If your stop was $5 you could buy 40 shares. You may find that your risk tolerance is greater than 2%, maybe for you it is 5%. I implore you to do the math based on your personal risk tolerance.

I can tell you that trading takes time to learn, there is no holy grail and no perfect system. If you can spend time on learning a system, gaining an edge and perfecting money management/risk management you will be miles ahead in your trading career.

What’s a non-trading related book that’s influenced you recently?

10% Happier by Dan Harris. He makes a case for mindfulness and meditation. It is a mix of true-life stories with research and wisdom. You learn through practice to quiet the voices in your head and appreciate living in the moment.

Questions for Sunrise?

Ask him in the comments below or ask him on Twitter. Thanks Sunrise!

Do you know someone who you think would make a good interviewee? Contact me!

Sever Your Market Tether on Vacation

2020-02-19T14:59:00-05:00

When I first started trading it was very hard to go on vacation and spend time away while the markets were open. I would reflexively check what stocks were gapping and try to imagine how my trading day would be going if I were trading. Honestly I just couldn't enjoy vacation - I constantly felt like I was missing out on profitable market action but more importantly I worried I was losing time to improve as a trader. What most traders don't realize is that purposeful time away from the markets is one of the most valuable long term investments you can make for your trading. This post explains how to use vacation to improve your trading.

Realization that Vacation is Long Term Profitable

As a new trader years ago I would dread time off. Sometime over the course of the last 15 years of trading, though, I've become way more comfortable spending time away from the market. Rather than being something to dread, I came to relish days off. I can't pinpoint a particular moment in time when my thought process changed - it was a gradual change that occurred over time although I do remember a specific incident that accelerated it...

My Worst Day was a Day I Shouldn't Have Even Been Trading

Many years ago my wife and I had planned to travel across the country to spend time with friends for the weekend. We had purchased plane tickets, hotel, and the rental car. We had been travelling a good amount prior to this trip so as the travel day approached we were not exactly looking forward to getting on another plane.

The day came and on our way to the airport very early that Friday morning, we both looked at each other and realized we really didn't want to go on the trip. We just couldn't get back on a plane and fly all the way across the country. We decided to turn the car around and go home - one of those crazy decisions that we never make. "Ah!", I thought as we drove home, "I'll be able to trade today." Was having to skip a trading day one of the reasons we turned around that morning? Not consciously but looking back subconsciously it had to have been.

I traded that day as I normally would having skipped a vacation that we'd already paid for. You can guess what happened - that ended up being my worst trading day up until that point. I didn't make any big mistakes - it was just dumb luck that this happened to be the day that my strategies performed REALLY, REALLY BADLY. I've never forgotten that day - a very costly one at least partly due to the fact that I was uncomfortable being away from the market.

I've recently thought a lot about my increasing comfort with time away from the trading desk and after seeing the results of this poll from Brian Shannon from Alphatrends where most traders said they wanted the markets opened more I realized that most traders aren't getting the most out of their time way from the market.

Eliminate the Distracting "Market Tether"

As traders we feel the need to be "in tune" with the market. When we go on vacation there's an underlying fear that we'll lose that synchronicity - we'll become out of touch with the market and when we return to trading it will take time to burrow back into the market's current flow.

What I've come to realize is that this market tether is exactly what you need to cut on vacation to become a better trader over time. Doing this right will allow you to truly enjoy your time away from the markets AND improve your trading each time. Here's how.

The Market Tether: Short Term Satisfaction but Long Term Closed Mindedness

The vacation "market tether" is bad for traders for a couple of obvious reasons and a very important one that's not apparent:

The first two are obvious - if you're distracted for any reason you're not able to fully enjoy your current vacation activity. You're simply not getting the most out of vacation. Not only does this make the vacation less enjoyable than it should be, but you'll ultimately be missing out on one of the most important long term benefits of time away.

This "market tether" can be conscious or subconscious. Either way it's satisfying a short term need at the expense of long term trading improvement. The short term need is the desire to stay in tune with the market. Less experienced traders might even be missing the thrill of market action like the feeling of a gambler who steps away from the slot machines.

When you're trading each day you should be following your trading systems closely. By definition you are burrowed down into your trading zone - ignoring all other distractions. This includes even other clues for other ideas that could turn into profitable trading strategies. Regularly letting yourself to come completely out of your "trading zone" - that is, severing your market tether however psychologically difficult - will ultimately allow you have a fresh perspective on the market itself and your own trading. What I've found over the years is that this fresh perspective isn't possible if you're continuously burrowed into the trading zone you've created for yourself day in and day out. You need to get completely out of your trading zone to be able to expand it and improve it.

Without occasionally severing your market tether you'll always be the trader that trades the myopic zone that you've created for yourself. Many of my best trading ideas have come right after time away from the markets.

Take Vacation with Intention

When you have this perspective it's much, much easier to spend time away from your trading desk. In fact, you should look forward to it and plan ahead to ensure that you're getting ENOUGH time away from the markets to get better.

When planning vacation I always check my earnings season tool to choose times that are likely not to see significant market action. I know how my strategies are affected by earnings so I can plan to spend time away when my strategies are likely to not trade frequently anyway. Because I day trade exclusively, I also have the flexibility to take an unplanned vacation day on a whim since I have no overnight positions that I'm obligated to manage - one of the most underrated reasons to day trade.

When you're on vacation, it's much easier to enjoy when you realize that you're literally becoming a better trader by not trading. Ignore the markets while you're away and you'll be refreshed and in a position to see the markets in a different light when you come back.

Do you have strategies for taking market vacations? I'd like to hear about them in the comments.

Earnings Season: How to use it in your Trading

2020-02-11T14:09:00-05:00

Most traders and investors are familiar with the concept of earnings season: the period of time where most public companies release their earnings and various other fundamental financial metrics (price/earnings, cash flow, debt, etc) as required by the SEC. These company announcements very often trigger large moves in the stock price as the market responds and processes the the information about the company and establishes a new equilibrium. The volatility around this response is often quite strong and is the focus for many trading strategies. As I often say, I don't attempt to trade the news but I trade the market's reaction to the news.

Most traders think about earnings season in an inaccurate way. This post explains why that is and suggests a much better way to think about earnings seasons.

Why “season” makes no sense

The word season implies that there’s a definite start and end date. Consider deer hunting season. You have a definite start date where it is legal to shoot deer up until the end date of the season at which point it is illegal again. Everyone knows the well defined dates of the season and almost everyone adheres to these rules. This is not at all the case with earnings releases. You can literally find companies reporting earnings on every trading day of the year.

There is also general disagreement about when earnings season starts and ends. Traditionally it was thought that earnings season officially kicks off with the earnings release from one company: Alcoa (AA). Over the years as technology companies have become increasingly important this tradition seems to be fading somewhat.

I've noticed that traders often speak as if they are intimately familiar with earnings season but if you ask them to put the earnings season start and end dates on their calendar and you'll end up with a variety of different dates chosen.

Does this make the entire concept of earnings season invalid? Of course not, but there is a much more useful way to think about the concept. Different trading strategies perform differently depending on how many companies are reporting. Some strategies depend entirely on earnings announcements and others AVOID earnings announcements specifically. It's important to think about how your trading strategy is affected by earnings announcements and earnings season - for example, when you're planning time away from the market you probably want to schedule the time outside of earnings season.

A better way to think about earnings

Here's how I've come to think about earnings season over the course of over a decade of trading.

First, when you look at the distribution of when companies report earnings, you definitely see a clustering around certain times of the year. However you’ll also notice a lot of companies reporting outside those clusters. See the chart below.

The second thing that stands out from the chart: there are four earnings seasons throughout the year but the length of each of them varies widely. The first earnings season of the year is much more spread out than the rest of the earnings seasons. Why? Most companies' fiscal years align with the calendar year so these companies are reporting earnings for an entire year starting in mid January. It takes longer to report annual earnings than quarterly earnings since you're producing fancy, glossy reports and fulfilling additional requirements.

So what date makes sense to use as the start of a particular earnings season given the fact that companies report every trading day? Enough traders still respect the Alcoa earnings report as the start of the season to follow along. When you plot those dates on the chart it does seem to mostly align pretty well with what most would consider the start of the earnings seasons. Until some other method comes into vogue this seems logical.

What about the end date for each season? You can't simply add a certain amount of days to each start date since the season length varies so much. A better way to think about it is for a given day calculate a percent of the way through that particular earnings season. In other words, of the total number of companies reporting that season, what percent have reported as of a particular date?

Dynamically Updating Chart Showing Earnings Big Picture

The above chart is dynamically generated and shows the current day (or next trading day) and what percent through the current earnings season we are. As of this writing it shows February 11th and that we're 33.1% through the current earnings season. Use this chart to determine when it's best to take time away from the market. Because the earnings seasons have different lengths, this visualization is a much better way to think about earnings.

Earnings Season is the Forest, now let's look at the Trees

Now that we've used an intelligent way to determine where we are within earnings season, let's look at the best way to scan for individual companies that have reported recently or in the near future. There are a few different tools you can use for this purpose but we'll look at two: Yahoo! Finance Earnings Calendar and the Trade-Ideas Top List.

Yahoo! Finance Earnings Calendar

The Yahoo! Earnings Calendar is very popular and does a decent job of allowing you to see which companies are reporting on a given day. By default it shows all companies that are reporting today and you can click on adjacent dates in the header and see earnings announcements for these different days.

Because it shows all companies reporting earnings, the first thing you're going to want to do is filter this list down. On the date I've chosen here you can see there are 122 companies displayed. That is going to be far too many to be able to process in a reasonable amount of time. Most of these companies don't have enough volume to trade anyway. There are some filters you can apply to the list by clicking on the Event Filters link and at first glance the list seems substantial. However when you look closer and try to apply a simple filter for Average Volume you quickly realize that it doesn't contain this very elementary filter.

This alone makes the list unusable but on top of that there are only a couple fields available to display for each stock. As a trader you need to be able to view the appropriate fields right alongside the symbol in the list. Looking them up for each symbol is time consuming and requires a ton of mouse clicks. This could be the difference between catching the trade and being simply too late to catch the move.

The other major drawback of this calendar is the fact that all companies that are scheduled to report earnings today are in the list. This includes companies that are reporting before the close as well as companies reporting after the market close. Why is important to make this distinction? Imagine you're looking at the list in the middle of the trading day. A sizable number of companies in the list will have already reported prior to the market open but most of the rest will be reporting after the close.

These two categories of companies are dramatically different! Companies reporting prior to the open will likely be quite volatile while the ones reporting after the close will still have relatively calm price action prior to their earnings release. Similarly when you look at yesterday's earnings reports the one that reported before the close have already had a full day of trading to process the report while the ones that reported after hours have not.

Most companies report their earnings after the close but a significant number report before the open. Here's the breakdown:

Why is this important? It's good to understand what the majority of companies do, but there's another important difference. When companies report after the close there's the post market trading session, the overnight, plus the pre market session before the next normal trading session occurs. There's significantly more trading time plus clock time before the next trading day as compared to companies that report before the market open. I definitely have strategies where this dynamic has a strong effect. By the time the regular session rolls around, companies that reported yesterday after the close can be somewhat superseded by the companies that reported in the pre market.

Nasdaq has a similar earnings page but it suffers from the same limitations as the Yahoo! earnings page. These earnings views could be fine for a lot of investors but if you're trading the markets you are definitely going to need more flexibility in your scan which ultimately saves time and effort and will allow you to take more profitable trades.

A Much Better Earnings Scanner: Trade-Ideas

Trade-Ideas is a scanner and artificial intelligence product that is the best way I know of to display recent and upcoming earnings announcements. It doesn't have the filtering limitations that the Yahoo calendar has and you can display whatever fields you want for each symbol. You can also quickly sort the list by any field and even paper trade any symbol using the Trade-Ideas simulated trading account that comes with every subscription.

Here's a view of my Recent Earnings Announcements top list window in Trade-Ideas. This list allows me to view only companies that have reported earnings this morning before the open OR yesterday after the close. That is, only companies where the current trading day is the first trading session after the company's earnings announcement. I also have applied some basic filters to reduce the list of companies reporting earnings to just the ones that I'm likely to trade. For example, I have a minimum value for daily average volume and a minimum price of $1 and a maximum price of $500. I know that I won't trade symbols outside of those thresholds so my list excludes them from the beginning.

This view is just not possible in other platforms. Here's the cloud link for this window so you can bring up this exact top list in your Trade-Ideas.

The second top list I frequently use in Trade-Ideas for earnings is my Upcoming Earnings Announcements window. I have it configured to show me all companies that are reporting earnings after the close today or at anytime over the following week. This view has all my favorite columns to sort by including the Earnings Date field. That allows me to quickly sort the list by when the company is releasing earnings relative to the current point in time.

So symbols will appear first on my Upcoming Earnings Announcements window and when the first trading session after their announcement comes around they'll fall off that top list and appear on the Recent Earnings Announcements list that I use during the trading day. Here is the cloud link for my Upcoming Earnings Announcements window so you can bring up this exact top list in your Trade-Ideas .

You can easily modify the Earnings Date filter for your own use and, for example, only show companies reporting earnings before the next session or fewer days. To view only the companies reporting earnings in the next two days, change the value of 5.5 to 2.5:

These earnings scans are just one of many features that Trade-Ideas offers. Click on the link below to learn more about Trade-Ideas. Sign up and you can immediately start using the two windows I use to view Earnings Announcements that I mentioned above.

Click Here to learn more about Trade-Ideas and use code DMABE15 to get a 15% discount

Can Traders Learn Anything from Poker?

2020-02-03T15:25:00-05:00

Several years ago I started playing poker as an intellectual pursuit with the intent of learning some lessons from the poker world that I could apply to my trading. I thought as a trader that I had a healthy view of money that would give me an initial boost in poker. Bankroll management? That's the basic skill of a trader and applying that to poker was second nature. There are a lot of parallels with poker and trading and I thought that my trading experience would ultimately translate well into poker.

I have mostly abandoned "serious" poker at this point for a variety of reasons and this post will explain why. I feel like I've gotten all I can get out of poker and while I'm mostly disappointed that I wasn't able to apply more to my trading I did learn one very valuable lesson.

My Initial Goals for Poker

I set out with a handful of goals for my poker endeavor:

My Poker Process

Live Poker in a Casino

The nearest casino to where I live when I started playing was Harrah's in Cherokee, NC which is about a four hour drive. A good friend of mine has played poker somewhat seriously since college so we have organized a couple trips a year to either Cherokee, Las Vegas, the Hard Rock Casino in Tampa, and more recently the MGM at National Harbor after it opened a few years ago.

Live poker in a casino is a blast - if you haven't played in a casino I'd highly encourage you to do so. I thought it was going to be a seedy place with a bunch of low lifes but nothing could be further from the truth. Although of course there are the occasional jerks, I have been consistently amazed at the friendliness and camaraderie at a poker table at a casino. You see all sorts of people from all walks of life coming together to play an awesome game with a perfect blend of skill and luck. I've played a lot of hours in casinos and I'd say that the average poker player is far more fun and friendly than the average person.

Home Games

My friend also hosts a home game 5-6 times a year so I got his advice for hosting my own game. His game is always a tournament and I knew I wanted to play cash games, so I started hosting my own monthly home game. These are extremely low stakes games that are mostly just fun. Even the good players aren't taking the game that seriously and the "cheap thrill" of poker at these stakes ends up being a very inexpensive form of entertainment.

Playing Online

I also played a bit online although it's quite difficult to play now in the US and the competition even at the lowest stakes is very strong these days. I like being able to use a tool like Poker Tracker to track performance over time. I don't play online anymore just because playing live is so much more fun. Playing online does allow you to play a LOT of hands pretty quickly so in that regard it's good to play online to advance past the basics. After that I found it too tedious and just craved playing live.

How are Poker and Trading Similar?

How are Poker and Trading Different?

In trading I have a few pre-defined trading strategies that I use. I've researched them deeply and there's no question how I should approach things during the trading day. I know the odds that trades from different strategies will be profitable so during the day there's really not a whole lot of discretion for me.

This was ultimately a very difficult thing for me to transfer to the poker table. You can't have planned for every situation at a poker table - there's just too many factors to consider at any moment. There's a LOT of discretion and judgement calls to make that you just can't plan for ahead of time. You have to be able to study some general situations and then be able to apply a lot of different concepts in real time at a poker table when everyone at the table is anxious for you to play to keep the game going. This takes a tremendous amount of experience and study away from the table to get good at. It's also one of the things that makes poker so great - talking about hands after the fact with other players. In some situations you'll might talk to 5 different players and get 5 completely different opinions about the best action to take in a certain spot. This is one of the best things about poker that there's not really an exact equivalent to in trading. Sure you can talk about trades after you make them but there's nowhere near the same level of analysis that you can do after a poker hand.

I realized pretty early on that it was not going to be possible for me to be able to play enough poker to get enough consistent and intentional practice to get very good. You can spend a lot of time studying away from the table but you have to also play a lot of live hands to implement what you've studied.

So What Did I Learn about Trading from Poker?

Beyond the basics of risk management and putting in time away from the table/markets is there ANYTHING that traders can learn from playing poker? To be honest it was a good bit less than I was originally hoping for. My main takeaway from poker, though, is I think a very important one.

The best poker players can intuitively know when a situation arises where they have a strong edge and are able to exploit it as frequently and efficiently as possible. For example, recognizing when you're very likely to have the best hand or when your opponent is likely to fold to a raise. The ability to know when these situations arise is vitally important in poker and the actual cards in your hand become less important - it's more about determining what your opponent has.

In this case there is a definite parallel to trading: when you have a trading edge you should be able to recognize it and put on larger size. I've spent the better part of a decade thinking about this and I think I've made some headway. That's my main goal for 2020 - trading with bigger size when I have an edge. More about this in another post.

My Poker Future

So am I abandoning poker? Not at all. It's such an awesome and underrated game. I'll continue my friendly home game and will continue making the occasional trip to a casino to play live when it's convenient. Hopefully more casinos get built within driving distance one day and I can play more frequently live in the future. If you have never played poker I highly recommend you give it a shot!

Trader Interview: Brian Shannon @alphatrends

2020-01-31T15:45:00-05:00

The next interview in the series is with Brian Shannon. Brian has been trading for a LONG time and has developed the reputation as one of the best guys in the business. His market commentary videos are well known for having a concise, no-nonsense approach. His book Technical Analysis Using Multiple Timeframes is excellent and widely reviewed and recommended. Find out more about Brian at his Alphatrends website and be sure and follow him on Twitter @alphatrends.

What is the most overrated trading advice?

"Winners take care of themselves."
Once you have your money in the market, you can never let your guard down, complacency is the silent equity thief. Winners are clearly less stress, but accumulated profits are your money. Profits are not "house money" that you can be careless with. Things can change quickly in the markets, without a plan to protect profits and manage your winners you will give back large gains and worse, allow them to turn into losers!

What is the most underrated trading advice?

People will mention they are "bullish or bearish" on a stock or the market, without any reference to a timeframe. In order to add value, there needs to be some point of reference from a time perspective. I might be bullish on a long term uptrend in the market when I look back a year or two, but there will be periods during that bullish trend where the best trades are on the short side. Also, being "bullish" might be from the reference of a purchase made two years ago, that doesn't make it a good buy today.

What’s a non-trading related book that’s influenced you recently?

The Impossible Climb - The story of Alex Honnold and his accomplishment of being the first person to free solo the 3,000 foot El Capitan, the largest cliff in Yosemite National Park. The book chronicles the laser focus it takes to tackle a goal that was widely considered impossible, if not a suicide mission.

Questions for Brian?

Ask him in the comments below or ask him on Twitter. Thanks Brian!

Do you know someone who you think would make a good interviewee? Contact me!

Trader Interview: Fred, Lone Stock Trader @lonestocktrader

2020-01-22T13:19:00-05:00

The next interview in the series is with Fred, the Lone Stock Trader. Fred trades for a living and posts about it on his web site. He's written several excellent articles on his system and trading in general that are worth reading. His 2019 review is particularly good as well as his post about how he transitioned from failed business to profitable trader. I love the no-nonsense style of his writing and his openness about his trading. I'm really happy to post his responses here.

What is the most overrated trading advice?

The most overrated trading advice is "get out when you're wrong". But don't get me wrong (pun intended). The advice is sound.

I consider it overrated, because it reinforces the perspective that losing money on a trade means you were wrong, which is a wrong association in my opinion. If you're following a trading strategy, losses are just part of the normal distribution of the strategy. The result of one trade is random. The result of one hundred trades is less random. Thinking that a loss (or ending the day/week/month in the red) automatically means you've done something wrong shows that you haven't accepted the probabilistic nature of trading, and that you're on the dead-end path of trying to win ("be right") all the time, which often is at the root cause of why so many traders end up blowing their account.

What is the most underrated trading advice?

"Review your past trades".
It's something most traders know they should be doing. Yet I'm pretty sure very few actually do it. That's the single exercise that turned my trading around years ago. I discovered my strengths, my weaknesses, and that if I had followed my strategy perfectly, I would have made money instead of losing consistently. The whole game then shifted from me trying to make money on every trade, to me focusing on following/executing my strategy perfectly. That's when I started making money. That's when I genuinely accepted that trading was probability game.

What’s a non-trading related book that’s influenced you recently?

It might sound cliche, but "Atomic Habits" by James Clear had a huge impact on my life. Motivation and discipline only lasts so long. Be it saving money, losing weight, being a successful trader, running a marathon or nurturing a healthy relationship, it's not your discipline/motivation that will allow you to reach these goals. It's your habits. This book explains and gives examples of how to form good habits and get rid of the bad ones.

Questions for Fred?

Ask him in the comments below or ask him on Twitter. Thanks Fred!

Do you know someone who you think would make a good interviewee? Contact me!

My 2019 Trading Annual Review

2020-01-21T13:55:00-05:00

Last year I made some big changes in how I trade my main 3 strategies. Each year I go back and review all the trades I took and see where I could improve. Are there any adjustments I can make to get better? Did any strategy perform poorly relative to what I expected? This is a good time to reflect on the changes I made and see how they played out.

First of all, above you'll find an equity curve (in R multiples) for the entire decade. The total R for the decade was 2011.9. This includes probably 10 strategies or so I've traded during that period. Pretty good. When you look at an equity curve zoomed out like this it looks smooth but when you zoom in you notice some drawdowns. One of the great benefits of using R multiples to measure performance is that it normalizes performance no matter the risk amount you're using for a particular strategy. At any given point in time I may be at full risk in one strategy but a small fraction of that in another. Here's a post where I go into detail about my process for sizing up.

My Gappers Strategy for 2019

Although this curve looks ok by the end of the year, in March it looked terrible! That is the time where I took a step back and reevaluated what I was doing with this strategy. Keep in mind that the basic strategy is one that I've traded for over a decade now. I've made some pretty drastic changes to the strategy over the years but the fundamental strategy is exactly the same. So what did I do in March?

I started looking at my backtest in a completely different way. I removed the stops! (I know, I know - bear with me.) My workflow from the backtest went as follows:

The Filter Phase is the hardest part and the one that takes the most energy and experience to do well. The set of trades that I end up actually trading turns out to be a pretty small percentage of the total backtest. I realized that I was doing my filtering after the stop had been applied to the trade. This has the affect of ignoring some valuable information for each trade. Here's my new workflow that I'm using now:

Notice that the stops and targets are applied at the end instead of the very beginning. Why does this matter? The difference is subtle but turns out to be very important.

Let's take two types of trades from the backtest. They both end up stopping out but the first type stops out but just barely and then continues in the desired direction. Here's a theoretical example of the first type: LVGO from 1/14. It barely hit the stop price of 28.99 only to continue on.

The second type stops out and then continues its plunge finishing the day well below (assuming a long trade) the stop. A good example of this is STT from 1/17. It hit the stop of 83.32 and continued south for the remainder of the day.

In my original workflow, these two types of trades were considered equivalent and my filter phase would not notice any difference among them. In fact they are very, very different! My updated workflow accounts for this difference - I consider it like adding another full dimension to my backtesting routine.

I'm hoping to continue sizing up this strategy in 2020.

Strategy B

My other main strategy I've been trading largely unchanged since 2015 or so. Here's the equity curve for 2019 for strategy B.

This doesn't look great but when I zoom out and look at the chart from 2015 to present it looks fine having gained 400 R. This strategy is actually quite flexible. It's designed to use variable position sizing based on the quality of the setup. I haven't implemented that yet (I use same size for each trade in the strategy) but I hope to do this in 2020 which I'll write about in a future post.

I hope you traded well in 2019 and you trade even better in 2020! If you have any questions feel free to contact me.

Trader Interview: Anne-Marie Baiynd @AnneMarieTrades

2020-01-16T16:52:00-05:00

The next interview in the series is with Anne-Marie Baiynd, a long time trader, coach, and author of The Trading Book (Amazon link). I haven't yet met Anne-Marie in person but we've interacted on social media quite a bit and I think her Twitter presence is great. I know several folks in the trading industry that have met her in person and have nothing but good things to say about her.

Her bio tells me she's had a wide range of experiences before planting her trading roots: neuroscience, mathematics, econometrics, and recruiting - plus she's started several companies along the way.

Here are her responses:

What is the most overrated trading advice?

"You've got to take the emotion out of trading"

Though people are becoming more sensible about this, I remember when I started almost two decades ago, this was all the rage. The fact is that trading should be disciplined but humans cannot operate without emotion, so people end up trying to stifle their emotions only to see them explode in other aspects of their lives or their trading accounts. Emotion has to be managed - but it cannot be squelched in the trading environment.

What is the most underrated trading advice?

"Learn to paper trade strategies properly before you trade in the live environment"

Everyone wants to be in on the action before they actually know what to do. Myself included. Granted there are things you learn in the live trading space that can only be assessed there, but jumping in with real money before you establish proper risk protocol and strategy execution is like putting on slalom skis for the first time and getting dropped off atop an Olympic ski jump....with almost as disastrous results. Learn to trade before you actually trade.

What’s a non-trading related book that’s influenced you recently?

"Thinking Fast and Slow" by Daniel Kahneman

An excellent study of the decision systems we have and how we war with them in the realms of our personal biases. It helped so much in the understanding of the thought process that goes into the decision-making business of trading.

Questions for Anne-Marie?

Ask her in the comments below or ask her on Twitter. Thanks Anne-Marie!

Do you know someone who you think would make a good interviewee? Contact me!

Trader Interview: Sean McLaughlin @chicagosean

2020-01-10T19:13:00-05:00

I'm starting a trader interview series. The series will not be a long form, exhaustive list of questions about how and why the interviewee got into trading or how their upbringing did or did not contribute to their success. There will be just three simple questions designed to reveal how the trader separates themselves from the trading herd.

There's a lot of trading advice floating around out there. Some of it's great, some of it's terrible, and a lot of it is so ingrained in the collective trader psyche that it becomes meaningless or cliche. Some of it applies only to a certain type of trader ("sell in May and go away") and some of it is so common that no one would dare question it ("add to your winners, cut your losers short").

The first two questions apply to the collective trading advice that is present all around us. What is the most overrated trading advice? What is the most underrated trading advice? I expect I'll get some pretty contrarian takes on these questions even for the already contrarian bunch that traders are.

The last question is designed to bring out a learning suggestion - a book recommendation. Not the same tired question ("what's the best trading book to buy?" - it's One Good Trade by the way) but a different and much more interesting question. What's a non trading book you've read recently that INDIRECTLY helped your trading? In other words, a non trading book that you were surprised to find lessons that you could apply to your trading or just improved your life or understanding of the world in some way.

Who is Sean McLaughlin?

I appreciate my friend Sean McLaughlin (@chicagosean) for agreeing to participate and being the inaugural interviewee. I don't remember the first time I actually met Sean but it feels like I've known him a long time. He's brutally honest about his trading and that comes out in his blog and his tweets. Sean has a great voice and hosts at least two podcasts that are worth checking out. He hosts a Denver traders' meet up which I understand is awesome - I wish there was something like that in my area. Sean came to Trade-Ideas via StockTwits and he's been an awesome addition. Here are Sean's answers to the questions...

What is the most overrated trading advice?

Journaling. Yeah. I said it.

Look, I journal. But I don't do it every day. And I certainly don't do it for every trade. I do it when I'm called to do it. I don't set a timer, and I don't force myself to eat spinach whenever I don't journal. Deep introspection is important for traders. But the means in which we all get there varies widely. For some, its meditation. For others its exercise. I might like to hike. Or maybe inspiration hits you best when you're in the shower or on long drives? Whatever works for you, do more of it. At the end of the day, we all need time to think and strategize and re-energize away from the screens. Whatever that means to you and however that works for you -- rock on with your Spirit Animal self.

What is the most underrated trading advice?

The X's and O's of trading are important, no question. But no matter how efficient you are at learning how to be a better trader, and no matter how quickly your assent to trading mastery, none of it will matter -- NONE OF IT -- if you don't get your personal financial house in order and establish systems and best practices to systematically save money, minimize tax impacts, aggressively pay down and ultimately avoid debt, and live within your means with a sensible budget. No amount of income you might derive from the markets will matter if you don't take care of this stuff first and make it a priority throughout your journey. Take it from me. I've lived the nightmare.

What's a non-trading related book that's influenced you recently?

I TEACH YOU TO BE RICH, Ramit Sethi. Terrible title, but life-changing approach to personal finances for me. The introduction to YNAB within this book alone was worth the $10 cost. This one book has opened my mind to so many new things to be aware of and be systematic about and can be directly linked to an ever-increasing positive slope to my personal net worth, self-esteem, productivity, health, family relationships around money, and ultimately my success as a trader. All these things are linked. The sooner we accept this, the sooner we thrive in all facets of our careers and life.

Questions for Sean?

Ask them in the comments or hit him up on Twitter. Thanks Sean!

Do you know someone who you think would make a good interviewee? Contact me!

What Frequency of Trades is Best for a System?

2020-01-09T12:27:00-05:00

When evaluating trading systems, how do you decide what frequency of trades is best? It seems like an easy question but there are several factors to consider and many of these decisions can be the difference between a successful trading system and one that's not worth your time. Here's my framework for determining the right number of trades for a model.

As Often As Possible? Maybe!

On one hand if your trading system has a significant edge then theoretically you should trade it as often as possible - no filtering at all, right? In practice though there is typically some filtering that needs to take place.

Consider the chart above. You have your trading idea, say, new highs on high relative volume. Most trading systems should start out with a basic trading edge - a strong theory that is supported by looking at a large number of trades in a backtest.

When done properly, the more filtering you do to your trading system the higher the profit per trade but the lower the total profit from the system. This is because proper filtering will filter out the worst trades at each point along the x-axis. (I estimate that 90% of my edge comes from my ability to choose filters that make sense - I'll write about this soon.)

Imagine you can determine with decent accuracy which trades will be profitable and which will not. If you were really concerned about the win rate (unhealthily so!) then you could reduce the system to just a single trade that was highly likely to be profitable. But at what cost? Total profit of course. So you can see there's a tension between total profit and profit per trade when you are able to meaningfully filter your trading system.

What's the Right Balance Between Total Profit and Profit Per Trade?

This is the ultimate question and where most of your work occurs. There is an art to coming up with the right balance and a lot of what you choose will come from experience. Depending on your situation the more conservative approach would be to apply more filtering at first - that is, choose a point nearer to the right side of the chart. The more aggressive approach would be to choose a point nearer to the left side.

There are good arguments to be made for either direction. If you have more trading experience then the more aggressive approach can be quite valuable. The more quickly you gather live feedback from the market the more quickly you'll be able to iterate and understand more about how your trading system acts in the actual market and how that differs from your theoretical backtest. Of course there are costs associated with this and as I've written before there's always the real temptation to scale a trading system up too quickly (something I've done many times) since you're typically overly optimistic at this point in the system development cycle.

If you choose a point towards the right of the chart you'll have less risk but that comes with the cost of having to wait potentially a long time before the feedback comes (i.e. trade signals appear). Of course there is no "right" answer - you'll have to gauge for yourself what makes sense given the nature of the strategy and your personal preferences.

Other Important Factors to Consider

How will this affect the systems you're already trading?

If you already have a trading system that you're trading how will these new trades affect it? Will the trade times overlap? Will this new system be a distraction? Is the trade frequency of the new system dramatically different than your current one? If so trading the new system might be a serious distraction from the trading you're already doing. If you're mentally burrowed down trading in the zone in one system and then a signal from another comes along you might underestimate just how much of a distraction that can be.

How fast is too fast?

Like the video clip from I Love Lucy above implies, there's a point where you'll be overwhelmed by the number of trades. There's a wide variety of capacities among traders - some can easily handle more trades and others find it difficult. This can be alleviated by automating your entries, your exits, or both - something I highly recommend. Also note that you should err on the side of fewer strategies if given the choice. For example, would you prefer to take 10 trades from a single strategy or one trade from 10 different strategies? It should be obvious that 10 trades from a single strategy is preferable.

How slow is too slow?

Another factor to consider is what's your threshold for the lowest frequency? I think about this in terms of trades per day. I try to keep my trading systems above 0.5 trades per day if possible. Why? I find that anything less than that and it's not frequent enough to keep my attention. I need to be focused on the strategies I trade - understanding fully why they should be successful. There's something about the repetition of trades in a system that keeps this focus in the forefront of your mind. As the frequency of trades drops it's harder and harder to recall that focus quickly.

What about buying power?

A non-obvious factor when you add a trading system is the buying power that is required. The more trades in the system the more buying power needed. Combine this with systems you're already trading and this could become a problem quicker than you realize.

It's quite frustrating to run out of buying power just before some winning trade signals materialize! One thing I do is keep a log of buying power over time. This updates in real time as I'm trading. I can go back and see when I had the least amount of buying power available over a period of time and I can plan accordingly.

Which day had the most trades?

Trades per day is a good benchmark, but that number hides a very important piece of information - what was the day with the highest number of trades? This can vary dramatically between systems even with the same trades per day. It's really important to plan ahead and visualize what those days would have felt like. Would you have been able to keep up with all the trades? Would you have run out of buying power?

It's up to you!

It's clear that once you take all these factors into consideration the choice for trade frequency for a trading strategy is a very personal one and there will not be a one size fits all answer for every trader.

Do you approach things differently? Let me know in the comments.

Exiting Trades Too Early or Late? Here's Why...

2019-12-27T16:38:00-05:00

I came across this question on the DayTrading subreddit the other day.

In this case the trader thinks he's exiting early because he's worried about a big loss. Big losses, of course, are uncomfortable. You have to be able to tolerate them to catch the profitable trades. The problem is not the occasional big loss - the most difficult part of trading is that you can't predict when there will be a large concentration of losing trades (a drawdown).

If you find yourself deviating from your plan and exiting your positions too early or too late it could be one of two things that's occurring:

If the trader is mostly comfortable taking losses and is still worried about big losses then he should reduce his trading size to something where he can think more clearly about each trade.

Just as common a situation though is that the trader hasn't put in the work and research required to understand their exit strategy. If you find yourself second guessing your plan and overriding your pre-planned exit then the best course of action is to test different exit scenarios and see which exit strategy works best over a large number of your trades.

If you don't know which exit strategies work best for your strategy then you should drop what you're doing and do the research required to come up with that answer.

Here's an example from one of my trading strategies. This strategy enters early in the day and holds the trades until the end of the trading day if a stop loss or target isn't hit. The result is a lot of waiting for positions to play out. Any one trade looks erratic and obvious in hindsight but I know that if I exit earlier than the end of the day I will be leaving money on the table across a large number of trades. There is no guesswork on my part - the numbers don't lie.

Creating a SPY Trading System

2019-12-03T00:37:00-05:00

How Do You Fix “Trading on Tilt”?

2019-11-07T17:04:00-05:00

Mike Bellafiore asked this question on Twitter yesterday. It’s a great question that almost every trader deals with at some point.

https://medium.com/media/264060af57a285bd5c6c798bb7566ec5/href

There are a lot of thoughtful replies in that thread with some good advice: step away from your trading desk, trade with half your normal position size, stop and go exercise, etc. Of course these are all things you should do if you find yourself in this situation. All of these “solutions,” though, are temporary band-aids for a more permanent problem. If you don’t address the deeper problem you’re likely to continue to find yourself in these difficult trading situations.

The Deeper Problem and How to Fix It

What is the root cause of trading on tilt? It’s really a symptom of a much deeper problem that you should try to solve: you don’t understand your trading system well enough.

If you’re trading on tilt then it likely means that the market has put you in a situation that you didn’t realize could happen ahead of time. “I had no idea this many trades could go against me in one day!” or “Who knew that I could lose so much money in a single trade!” Having these thoughts in the middle of a trading day is a major flaw in your system that must be addressed immediately. How?

The fundamental problem is that you haven’t done enough work outside of the trading day to fully understand your trading system and why it works. What are the best and worst days that your system is going to have? Under what types of markets does your system work well? When does it perform most poorly? You can’t predict the future but you can look in the past and get a really good idea about the range of performance you can reasonably expect from your system. If something surprises you during the trading day, it’s likely that you’ve skipped this arduous but critically important step in preparation.

Peer into the Past

Historical market data is really easy to get access to now. Go back and backtest your system for as long as you can go back. Look at the equity curves — are they smooth or do they have spikes? (And be careful, if you look over a large enough timeframe all curves look smooth!)

Here’s an important step that most traders skip — look at the performance by day of your trading system. What were the best days? The worst days? What days did it trade the most? How many days are there with no trades? Look at the trades it took on those days and truly visualize what trading that day would have felt like with size. Could you have kept up on the days where it traded a ton? What would you have done on the days with the biggest intraday drawdowns?

This is the hard work required to be prepared for any given trading day.

Easy for you to Say, Dave — You’re an Automated Trader — I’m a Discretionary Trader!

What about traders that trade with their instincts? “You can’t backtest my super-duper trading discretion. I trade with my extraordinary feel for the markets.”

I know plenty of traders like this and while it seems like these are fundamentally different styles, they’re really very similar: You get a signal where you’re confident you have a trading edge and you take the trade. Sounds pretty simple and in a lot of ways it is.

How you attain that confidence in your edge varies from trader to trader. Confidence for a discretionary trader comes from experience and trading results over time. This is more valuable than any backtest but it takes time to develop that experience.

If you get into situations where you end up trading on tilt, then you’re probably trading with too much size and you should reduce your size until you gain more experience with your system.

Of course there are no easy answers but if it were easy everyone would do it!

(Like this post? Follow me on Twitter)

Why Trade-Ideas Paper Trading Is Such a Big Deal

2019-11-01T17:58:00-04:00

American Presidents, the Stock Market, and Political Bias

2019-08-15T00:44:00-04:00

Should you re-enter trades that have stopped out?

2019-07-15T17:57:00-04:00

Here’s a difficult trading situation that often confounds new traders or even experienced ones that are experiencing a drawdown: a trade setup occurs, you take the trade according to plan and it quickly hits your stop — but then it immediately sets up again for the same type of trade.

Do you take that second setup? On one hand a setup is a setup and not taking the trade would be a mistake. Though on the other hand the market has already told you you were wrong once — being told you’re wrong twice or three times just seems stupid.

Here are a couple methods you can use to increase your confidence level in this common situation. A large fraction of your trading confidence will come from your research outside of market hours and this situation is no different.

Keep Track of These Situations To Evaluate the Big Picture

As opportunities for re-entering trades occur it’s important to keep track of them to understand what happens over a large number of occurrences. Any individual trade is unimportant — it’s the aggregate that matters.

If you’re having difficulty with this situation you probably are taking some of these re-entry trades and skipping others. That’s understandable but to really gain confidence in these you’ll need to keep track of every one of them. If you’re only trading some then your sample is incomplete and your mind will play tricks on you by easily recalling the big winners or losers but forgetting the bulk of the instances. This is common and why keeping track of all your trades is so important. Your psyche will lie to you but the numbers won’t.

I suggest trading these subsequent setups but with really small size. This allows you to risk a small amount of money so the trade is real rather than theoretical which gives you skin in the game so you’re more likely to pay attention over time. As you trade these re-entries, it’s important to track them separately from the “normal” setup. Tagging your trades in a trading journal is a perfect way to handle these. The re-entries are a subset of the main strategy that these trades come from. For example, use a tag like “Strategy X” for all trades from this strategy whether they’re re-entries or not. For the re-entry trades, use an additional tag “ReEntry”. This allows you to track trades across the entire strategy but also filter on only the re-entry trades to measure their performance separately.

After I accumulated several trades using this method, I realized that the re-entry trades were actually performing better than the system overall. It absolutely made sense to trade these second chance setups — perhaps even with larger size.

Backtest to Get the Longer Term Picture

It takes time to wait to accumulate a lot of real-time trades to keep track of. You should absolutely do that but in the meantime you can do a backtest to understand what happened in similar situations before you started keeping track.

One approach to capture this situation is to have your backtest skip the first N opportunities in your strategy and trade the N+1th one. Of course, there will be fewer trades in the trade set since a lot of times there’s only a single setup, but you should be able to gather a lot of past instances of these re-entry trades to examine closely in a chart. You can start with N=1 and then run another with N=2, etc.

Every strategy is different but these two steps should give you a deeper understanding of your trading strategy overall but also give you confidence to trade the re-entries (or not!) knowing you have data to back you up.

If you liked this post, you'll love my free newsletter where I teach how to come up with your own profitable trading strategies. Sign up here ->

Takeaways from Mike Bellafiore’s Discussion on Stopped Out Trades

2019-03-01T22:25:00-05:00

My Approach to Trading with Bigger Size

2019-02-27T18:35:00-05:00

Trade-Ideas SCoRe (Stock Composite Rating)

2019-02-15T21:51:00-05:00

Here’s a good write up of Trade-Ideas SCoRe or Stock Composite Rating. It blends our technical, fundamental, and non-structured data into a nice metric that can be used to assess a stock’s overall strength. Here’s the full description from Andy Lindloff who spearheaded the effort to create the metric.

The Trade Ideas’ SCoRe (Stock Composite Rating) is a proprietary formula that measures a stock’s strength along technical, fundamental, and non-structured dimensions. We employ over 17 such metrics to measure each SCoRe. A stock can have a SCoRe of 30 to 100, with 100 being the best score. Unlike the other rating systems, the SCoRe is dynamic, and will change in real-time during live market hours. This allows our clients to act swiftly to quickly changing price action. ScoRe incorporates both Technical and Fundamental metrics, with an emphasis on moving averages and the position in range on multiple time frames.

The Top-List above only looks for stocks with a SCoRe greater than 90. It has identified a stock that may be on the verge of breaking out to an all-time high. iRobot Corp. (IRBT) has a SCore of 98. They recently had earnings and the stock exploded to within cents of it’s all-time high set back in August of last year.

With a huge short float (42%), a new all-time high above $118.75 could really get this thing going as many shorts will be scrambling to cover. The stock price has made a big move since earnings, so a pullback would not be a surprise and some may wish to use that weakness to enter a position at or near the rising 10 day SMA, should it get there.

You can view all the documentation for all our filters on the Alert and Filter Help page. You’ll need a subscription to Trade-Ideas to use the SCoRe.

You Missed a Trade - Now What?

2019-02-07T17:56:00-05:00

One of the most frustrating things that can occur as a trader is when you miss a profitable trade. You’ve gone through countless hours of diligent work and research to create and refine a trading strategy, you’ve paper traded it, you’ve double checked that you crossed your Ts and dotted your Is, and maybe even weathered a drawdown. Finally another trade setup comes along and — dang! — you miss it by either being a moment too late or, even worse, you have your entry order in place and you don’t get filled and the price blows by.

The price is now well into what would have been profitable territory had you gotten in the trade, but now you’re left sitting on the sidelines wondering what might have been.

Like getting barely stopped out of a profitable trade, this can be very frustrating for a trader. This can also lead to another situation that most traders don’t put a lot of thought into.

Price Pulls Back to your Original Entry

So you missed the original trade, but now the price has pulled back offering you another shot. Do you take it? Here’s a hypothetical but very realistic example in SYY from 2/4/2019.

There are two conflicting ideas in this scenario.

You are being offered a second chance to take the trade at the original or perhaps even a better price.
However, if you take this trade you are guaranteed to take 100% of the trades that end up hitting your stop as this is exactly the behavior of trades that stop out.

These two ways of thinking about this scenario are of course in stark contrast to each other. What is the best way to think about this scenario so that you have a plan when this all too common situation arises? I see two answers to this question, one very simple and one more complicated but complete answer.

The Simple and Perfectly Valid Answer

Your default answer should be this: if you hadn’t missed the original entry, is there any reason you wouldn’t still be in this trade? If not, then you should take the second entry — after all, this is literally a second chance to execute your original plan for this trade.

This is a perfectly valid answer that gives you a stress-free way to respond to the situation. But…

The Difficult but More Rewarding Answer

The real crux of the situation is this: even if you establish that you would still be in the trade if you took the original entry, you now have more information than you had prior. Has the stock exhibited any behavior that makes it more likely to end up a profitable or losing trade? If so, that should play heavily into your decision about whether to take this second entry.

This leads us to a discussion of my favorite and commonly neglected trading topic: post-entry trade analysis. Every trader spends a lot of time thinking about pre-entry analysis, but very few spend the time required for the more rewarding topic: what happens after you enter your trades.

Post Trade Analysis — Where to Begin

To start making a plan for our situation in SYY, we need to figure out where to focus. The first thing to do is review the charts for the trades you’ve taken. Focus on the trades that went in your direction initially like SYY. Separate these charts into profitable trades and losing trades. Is there some behavior that some of the winning trades exhibited that some of the losing trades didn’t? If so, try to formulate a rule and keep score using a spreadsheet for as many previous trades as you can. As with any sort of analysis, it's the aggregate that counts — any one particular trade in and of itself is meaningless.

This can be especially difficult since these are trades that you’ve taken and probably have some memory of (hindsight bias). Try to leave this emotional baggage at the door. As much as possible take on the role of a skeptical, neutral observer.

If you find a characteristic that shows promise it can have a dramatic effect on your results. We’re only discussing this missed trade scenario, but think about what this implies. If you can determine a statistically sound rule to use for this scenario, you can also apply it to different ones. For example, if you’re already in a trade that exhibits profitable behavior and then pulls back as SYY did, you can use this information to scale in and add to your position. Conversely, if it shows negative behavior you could exit your existing position at breakeven and avoid a loss entirely. This is hugely powerful information that can substantially raise your system’s profitability — and not by adding more trades, but by simply altering the trades you’re already making! As I alluded to in my post on scaling into trades, this is very difficult by has the potential to be highly rewarding.

Most Underrated Trading Platform Feature: Time Stops

2019-02-04T20:06:00-05:00

SPY and Rising/Falling 200 Day Moving Average

2018-12-17T01:19:00-05:00

After Brian Shannon’s tweet the other day about new lows in markets below the 200-day moving average, I thought I’d start doing some research on the subject of moving averages in the overall market.

Streaks of Rising vs. Falling 200 DMA

First off, here’s a list of the longest streaks with a rising 200-day moving average in SPY. Notice how the second-longest streak just ended towards the end of October.

08/15/2015: 665 days
10/23/2018: 607 days
10/14/2014: 367 days
11/19/2017: 351 days
08/08/2011: 231 days

Here’s a list of the longest streaks with a falling 200-day moving average:

07/27/2009: 392 days
04/29/2003: 315 days
01/07/2002: 230 days
04/14/2016: 75 days
01/27/2012: 60 days

Notice the length of these two sets of streaks. The streaks with a falling MA are just so short compared to the streaks with a rising MA. Of course, there is a strong positive bias in the market, so this is exactly what you’d expect to see. It’s still striking to look at the numbers this way. The 75-day streak that ended on 04/14/2016 is fourth on the list! Most traders just don’t have much experience in a bear market.

Here’s another visualization that puts this in perspective:

The above chart shows every trading day since 2005. Green days indicate a rising 200-day moving average, and red days indicate a falling 200-day moving average. The darker the shading, the longer the current streak. There’s a lot of green there! Nothing of real significance in almost a decade. What percentage of current traders do you think have been trading longer than 9 years? It has to be low.

The Edge with Rising/Falling 200 Day MA

Is it really true that we’re more likely to make new lows when the price is below a falling 200 DMA as Brian says? Is it one of those market truisms that everybody says but doesn’t really stand up to scrutiny?

It turns out that it IS true — but how much? How strong is the effect?

When the price is below a falling 200 DMA, on average the next day’s low will be 0.029% lower. When the opposite is true — that is, the price is above a rising 200 DMA, on average the next day’s high will be 0.049% higher.

What About the 50-Day MA?

The 50-day moving average is shorter, so it “catches up” quicker to the most recent price, so we’d expect the streaks of rising and falling MAs to be shorter. This is exactly what we see.

Longest streaks of rising 50-day MA in SPY:

01/22/2010: 189 days
03/16/2011: 134 days
02/27/2007: 133 days
03/11/2004: 133 days
05/11/2017: 119 days

Longest streaks of falling 50-day MA in SPY:

01/05/2009: 143 days
10/01/2002: 105 days
04/01/2008: 96 days
01/26/2001: 90 days
11/15/2001: 89 days

It’s easy to see how bad 2008 was in this chart — the two longest streaks of falling 50 DMA with most of the days in the same year.

What about the edge versus the 200 DMA? When the price is below a falling 50-day MA, the low on the next day is on average 0.045% lower than the previous day. When the price is above a rising 50-day MA, the high on the next day is on average 0.068% higher. The effect is even stronger with the 50 than with the 200. I’ll take a look at shorter moving averages in a future post.

(If you like this post, you’ll probably like my Twitter feed where I post different SPY-related charts each day depending on the market situation in the #SpyWhatsNext hashtag.)

How to Think about Trading Halts

2018-12-13T01:27:00-05:00

The other day I noticed that one of the symbols on my daily watchlist had halted in the middle of the day. It was TNXP on 12/7/18 and it was unavailable for trading from 10:20am until about 45 minutes…

Now available here: http://www.davemabe.com/the-best-defense-against-trading-halts/

The Best Defense Against Trading Halts

2018-12-12T16:33:00-05:00

Years ago I worried a lot about halts. I had just read Fooled by Randomness by Nassim Taleb which had just recently been released and recommended to me by Trader Mike. (My Amazon account tells me I bought it in May 2006 which would have been less than a year after I started day trading.) That book has had a major impact on the world — the term “black swan” is now very common and people at least believe they understand the concept.

At that point in my trading career I was still a beginner. I had assumed all my life that day trading was risky and was still coming to grips with the fact that the vast majority of the risk was in holding overnight — which day trading specifically avoided. Being a risk averse person I still harbored the assumption that day trading was risky because everybody said it was. After reading Fooled by Randomness, I thought that trading halts were the black swans that I had ignored so I put a good bit of thought into them.

Research

Whenever I feel like I don’t understand something as well as I should, I do research on the topic until I’m comfortable with it. I wanted to at least get a sense of how big a problem trading halts might be. I downloaded all the trading halt history I could find on Nasdaq’s trading halt page and put them in a spreadsheet. The first thing I thought when looking at the data was that there are a lot more halts than you realize — there were 21 trading halts just on the one day that TNXP halted!

That seems scary but when you drill down you realize that most of them are thinly traded or just strange halts that aren’t likely to occur in most common trading situations.

What about the halts that do happen during common trading occurrences?

You Will Experience Them

If you trade for long enough, it is inevitable that you will experience a trading halt in one of your trades, and I assure you, it will be scary.

I’m pretty sure I’ve experienced 4 trading halts over the years, the longest of which went from Friday to the following Monday. That was not a very fun weekend!

One thing to remember, though, is that once trading resumes after a halt sometimes price is in your favor. That is, some trading halts will hurt you but some will benefit you. As long as you have a healthy mix of long and short strategies, in the long run there’s a good chance that the halts you experience are going to be a wash. Here’s a chart of the first halt I experienced — HAR on 9/21/2007. This one ended up going in my favor for an over 8R win.

The Best Defense Against Trading Halts

Even though in the long run it should be a wash, you still need to do what you can to avoid being wiped out by a particular halt. The best way to minimize the damage is through proper position sizing. It boils down to a simple concept — do you need the money you have at risk? If it was tied up for a day, a week, or even many months — how much pain would that cause you? Make sure you size your positions such that you’re putting on healthy size but not so much that a halt would wreck you. This sizing is a personal choice without a “correct” answer, but it’s important to go through this thought process knowing that there’s a small chance that the money you risk on a trade could be tied up for A LOT longer than you imagine. Plan for the worst case scenario you can think of.

The other main defense against trading halts is, perhaps counter intuitively, trading a lot. The more statistically profitable trades you put on, the less impact a trading halt will have when you step back and take a long term view on your trading. Even a large loss from a trading halt should be just a blip on your long term equity curve.

Is the Market Really More Likely to Continue as Gap is Bigger?

2018-12-05T01:30:00-05:00

If you don’t follow Steve Burns on Twitter, you should. He tweets all sorts of interesting market-related stuff. This one, though, made me do a double take:

This is one of those market “truisms” that everybody nods their heads to knowingly but very few people bother to verify.

Well, I like to verify things and not in a way to prove people wrong. Rest assured my motives are entirely selfish — if this statement is true then there’s an edge to be traded profitably. More often, though, by verifying things you end up learning something. Even if you can’t directly apply it to a trading strategy now, over years of research you’ll be able to pull from your growing library of market knowledge.

The reason I perked up at this particular tweet is because it runs counter to a lot of my research over the years on the behavior of the overall market. That is, there’s a LOT of mean reversion in SPY.

For the tweet to be true, we’d need to see the price close higher than the open after large opening gaps up and close lower than the open on days where there are large openings gaps down. Does that happen? Let’s take a look.

The Backtest

I ran a very simple backtest for the SPY:

When the opening gap is greater than 0, go long at the open and exit at the close.
When the opening gap is less than 0, go short at the open and exit at the close.
When the gap is exactly zero, do nothing.

I also capture the Gap % for each day which will let us determine the correlation. The first thing I notice is that this is not a profitable trading strategy which is not surprising. A profit factor of 0.96, win rate of 49%, and an average profit of -$1.84 per 100 shares traded. But that’s taking every trade — let’s look at the size of the gap.

A quick glance at the chart and you’ll see that the bars on either edge are the most extreme gaps — the red one of the left represents the largest down gaps and the green one on the right represents the largest up gaps. If our original statement is true, we’d see bars going in the opposite direction on the ends of this chart — that is, they would extend above the zero line. We see literally the opposite of what the statement suggests we’d see.

OK, but What About Correlation?

When you work with enough backtests and statistical data, you quickly realize that you can be easily fooled by data. In fact, even in the chart above that the opening gap percent might be positively correlated with average profit per trade even though it appears as if it can’t possibly be. How?

We simplified our trade set by creating buckets for each level (range) of gap percent. When we do this we necessarily lose the full story. Correlations are strongly affected by extreme cases — exactly the cases that were collapsed into the bars on the left and right edges of the chart.

To determine correlation you need to look at the entire trade set — not just the buckets summarized in the chart. When you do, though, you see that the size of the opening gap is, in fact, negatively correlated with average profit:

Correlation for gaps down: -0.033
Correlation for gaps up: -0.016

What if we limit ourselves to only the more extreme gaps? In that case it gets even worse:

Correlation for bigger gaps down: -0.084
Correlation for bigger gaps up: -0.095

Again, we’d see positive numbers for these correlations if the original statement was really true — but we see the opposite.

So What Did We Learn?

By doing this, we learn a couple things. It reinforces the best advice I can possibly give any trader: don’t believe things at face value — do the work required to convince yourself it’s true.

The other takeaway is that while the correlations here aren’t strong enough to amount to a tradeable edge, they’re getting closer to that point. With some more work, this data suggests you could create a system that actually fades these strong opening gaps.

My Take on Improving the Equity Curve

2018-11-29T01:35:00-05:00

We’re making excellent progress on Brokerage+ and I wanted to highlight a particular feature that I came up with several months ago. I’m calling it the “Profit Tracker” although I’m sure there’s a much better name someone can come up with for it. Here’s what I was hoping to accomplish with it.

The Humble Equity Curve

Every trader is familiar with an equity curve — basically a line or area chart of your profit (or loss) over some period of time. Here’s a screenshot of one that I just took from our Holly strategies window.

There’s a lot of information conveyed in an equity curve — this one shows the aggregate profit and loss from all positions throughout the day.

What the Equity Curve Lacks

Here are some questions that an equity curve DOES NOT answer:

How many positions are contributing to the profit and loss?
How many of those positions are currently profitable?
What portion of the total profit is each position contributing?
Is all the profit coming from a single out sized winner?
How many of the positions are short versus long?

The equity curve is great because it’s easily understandable and it’s a simple and pleasing visualization (more pleasing when it’s more green no doubt!)

Trying to answer any of these questions makes the equity curve a lot more complex. You could add points to show when positions were initiated or make it a stacked area chart with each layer in the stack correspond to a position but by doing so you lose the simplicity and familiarity of the equity curve. I’m tempted to try a stacked area chart, but it would definitely have to be bigger to be able to zoom into the details — a simple equity curve can be very small and still convey the necessary information.

A Different Way to Visualize Profit and Loss

When I set out to try something different, I wanted to convey more information in less space by adding the ability to answer some of the questions that the equity curve does not. It should also be interesting to look at — for example looking at a chart is a lot more interesting than looking at a column of numbers in a spreadsheet.

Enter the Profit Tracker. It’s a profit and loss continuum with each position plotted on it, but also the total profit marked with the larger black triangle. Here’s another image highlighting some of the details conveyed.

It updates automatically each second so the symbols jump around a bit with each update as it reflects the current status. You can see a live example of the Profit Tracker in Dan’s video from earlier today. Notice the Profit Tracker in the top left of the video.

Also note that there are some positions on the top of the continuum while others are on the bottom. Why? By default the Profit Tracker places them on the bottom, but if it realizes there are symbols that need to be placed close together it puts them on the top to minimize the overlap and try to make all symbols visible.

It’s Missing the Time Element from the Equity Curve — Or Is It?

By adding position data to the visualization, we essentially remove an important part of the equity curve — the time element. You can quickly see what the profit and loss was throughout the day in the equity curve where the Profit Tracker operates more like a current snapshot.

While there is no x-axis with time on the Profit Tracker, an indirect subtle indication of time is still there. The scale of the continuum is automatically adjusted based on the maximum and minimum points of total profit throughout the day. Here’s an example from earlier today zoomed into the right hand side:

With only a quick glance you can see that our current profit is off the highs for the day. While this doesn’t convey the exact time of day it does give us some sense that we’re off the highs and by how much. You can in some sense think of this as conveying the same information that the vertical axis does in an equity curve.

Where to Go From Here?

While I think this is a pretty useful and unique view of a portfolio, I think it can be improved.

Use a gradient color for the symbol font based on some property such as profit level
Vary the size of the font based on some aspect — recent profit movement for example
Add a vertical mode that you decrease the overlap when displaying a lot of positions
Display a tooltip with some information when you hovered over each position in the continuum

What do you think? Would you find it useful? Suggestions for improvement? Let me know in the comments and be sure and follow me on Twitter if you don’t already.

(Also, Brokerage+ is coming out of beta really soon, but there are a limited number of licenses available. Click here to see how to secure your reservation.)

Why I Ignore the Overall Market when I Trade

2018-11-26T21:58:00-05:00

Although I have a chart of the SPY open in my trading platform during the day, I am only mildly curious about what it’s doing. Even that might be overstating it. When the market gaps up strongly I don’t have a directional bias in my daily gap trades and neither when the market gaps down.

I realize that it sounds crazy to some traders to completely ignore the overall market, especially when you consider the fact that the movement of most stocks are correlated with it. Given the fact that so many traders watch the overall market and use it to determine how they trade individual stocks, why in the world would I choose to ignore it?

Benefits to Ignoring Overall Market

I imagine most systems traders consider how to include the overall market as an input to their trading systems. I thought a lot about it as I designed the systems that I trade.

Here’s a list of reasons why I concluded that I should have no overall market inputs into my systems:

Is the Overall Market Really Highly Correlated with your System?
Although most stocks are correlated with the overall market on a given day, is your trading system highly correlated with it? It may seem appealing if it’s true, but in my opinion this should be a strike against the quality of your trading system. Why? What does it say about your trading system if it is so dependent on behavior in the overall market? To me it means your system really isn’t all that unique or statistically significant. A robust trading system SHOULDN’T be strongly correlated with the overall market.

A Market Input Reduces the Number of Trades in your System
If you find an overall market input that is correlated enough to make a difference in your trading system’s performance, then including it will necessarily reduce the number of trades in your system. In fact, there might be entire days or even weeks where your trading system won’t take trades specifically because of your market filter. I’m trying to take as many profitable trades as I can so anything that reduces the number of trades I need to look at with a very critical eye to decide if it’s really worth the trade off.

The Overall Market is Finicky
I’ve taken stabs over the years at developing systems to trade the overall market using the e-minis. What I quickly found is that when even with 20 years of 1 minute bars, the relatively profitable situations that repeat over time is fairly small. When you do find reliably repeatable opportunities they are relatively infrequent. If you loosen your standards a bit to find more frequent opportunities, the uniqueness of the situation is reduced. Another way to think about this is that each market day is unique — including such a finicky filter in a separate trading system seems risky and somewhat arbitrary to me.

It Feels Like a Shortcut
I’ve looked very closely at how the overall market affects some of my strategies. When determining filters to use, the ones that relate to the overall market usually correlate somewhat strongly. It’s always felt like a shortcut to use them though. I’ve always concluded that my systems should be able to stand on their own. If I can’t find other ways to improve a system I’m designing then I take that as a strong sign I should go back to the drawing board and think harder about what I’m trying to accomplish with the trading system.

It’s a LOT Less Stressful
Rather than including a lot of indicators and filters into your system, it’s always preferable to exclude as many as you can. There’s ALWAYS more data points you could be looking at — the trick is having the confidence to ignore the data that’s unimportant. That takes time and work to research how indicators may or may not affect your system. If you don’t do that research, you’ll always have some doubt in the back of your mind that you cluelessly ignoring something important. This is especially true for the overall market which everyone on Twitter has an opinion about. It feels great to be able to confidently ignore that chatter. This reminds me of one of my favorite quotes from Albert Einstein:

“Everything should be made as simple as possible, but not simpler.” — Albert Einstein

Going Forward

Even with all the reasons I’ve listed above, I haven’t given up on incorporating overall market filters. This is another benefit of having my systems ignore them — I can always introduce them in the future in a more intelligent way.

For example, to counteract the effect of reducing the number of trades, you could increase your position size since in aggregate each trade should be more profitable and you should be more comfortable scaling up size, all things being equal. I’m also working on a method that instead of a binary yes/no for if the overall market filter is satisfied or not I could use a confidence score from 0 to 100 based on the value of the current market filters. More on this general idea in a future post.

Is Getting Stopped Out of Profitable Trades - A Good Thing?

2018-11-19T22:45:00-05:00

I came across the tweet from Mike Bellafiore the other day describing a typically very frustrating trading experience that I’m sure will resonate with a lot of traders.

So you make a trade with all your risk parameters set and you get stopped out, only to see the stock move strongly in your direction. When the dust settles, you stare at a beautiful chart — a quintessential move that is right up your alley — and you found a way to take a loss on the trade. This situation is not that uncommon if you’ve been trading for any length of time and, man it can be frustrating. Here’s a good example from Friday in KBH:

The article describes the situation as if the trader was fundamentally unprepared for this particular trading situation and how he should have done a little more homework to handle the trade differently once he was stopped out. I agree you should absolutely do as much as you can to prepare for the trading day well before the opening bell rings.

Being Unprepared Isn’t The Reason

The important thing to remember though is that you can do all the preparation in the world and this situation is guaranteed to still happen. It would be statistically surprising if this DIDN’T happen pretty routinely.

The proper takeaway I’ve learned over the years is that a well-functioning trading plan will necessarily have these trades occur with regularity. In fact, it’s actually a positive thing that they occur — your general thesis is sound and your stop was placed almost perfectly.

Any Single Trade Is Irrelevant

Remember: any single trade is unimportant to the success of your trading system. If one trade can cause this type of meltdown, then you either need to trade with smaller size or redesign your trading system.

Don’t let this situation frustrate you. Handle it like a pro — recognize it and make a mental note. If it happens a lot, go back and backtest using a looser stop and see if there’s an improvement. Only make changes if you can prove to yourself that an alteration will be more optimal over a large number of trades.

How to Scale In To Trades (with Examples)

2018-11-12T21:40:00-05:00

I’ve been gap trading for over a decade. One thing I learned a long time ago was it’s human nature to obsess over getting into trades, but the real opportunity for improvement is what you do after you’re in the trade. Once you wrap your head around the basics — sound position sizing, use stops properly, etc — you should come to realize that where you make and lose money is how you handle your big winning trades.

What Is Scaling In?

Scaling in to trades is the process of adding more shares to an existing position to achieve higher profits, presumably after seeing a confirmation signal after your original starter position was taken.

Trading is Simple — Just Add Size to Your Winning Trades!

One thing that you’ll hear a lot of traders talking about scaling into your winning trades — that is, adding size when a trade is going in your direction. To hear them talk about how gracefully they do it makes it seem seductively easy:

and

I’ve looked at scaling into trades a few times very closely with my own trading systems.

My conclusion: scaling into positions is too hard and most traders should not do it and focus on other easier areas to improve. (I do have some caveats at the end of this post.)

For Scaling In to Work, This Must Be True

In order for scaling into positions to make any sense, you have to be able to recognize some profitable conditions AFTER you’re in a trade that you COULD NOT recognize at the time of your original entry. This seems subtle but obvious at the same time — if you could recognize the situation prior to the initial entry just put on more size to begin with! (See caveat at end.)

So let’s say you’ve found a post trade entry situation where you believe you have an even greater edge than you did prior to your entry. It has to be a very unique situation because if your trade is already significantly profitable, then adding to the trade is going to raise your average price to an unacceptable level (let’s focus on long trades only.)

On the other hand, if the price is still close enough to your entry price that scaling in will change it only by an acceptable amount, then you’re more likely to be adding size to trades that will end up as losing trades (this is, of course, very bad.) See this example from a trade that Trade-Ideas Holly AI took in RRR on 11/8/18:

What Happens To Your Original Stop Loss Order?

Let’s say you’ve determined the price point where you think it’s profitable to add size to a trade when the price has gone in your direction. What do you do with your original stop order? Do you move it closer to your new average entry price? If you do, then you’ll be adding size to positions that some of which end up stopping out. If you leave it where your original stop was then you’ve simply increased your risk for this trade and made your average entry price worse.

Perhaps you look for another “setup” in the trade with its own entry price and stop price that is different from the stop price in the original entry. For example, this trade in URBN from 11/8/2018.

If you’re “scaling into” a trade but you’re using a completely different entry price and stop price you’re not really scaling in at all — this is really a trade from a distinct “system” that happens to coincide with a symbol you’re already in. If that’s the case you should treat this as two distinct trading systems and test, trade, and track performance completely independently from one another.

Have a Plan For Managing Your Exit Orders

In any of the scaling in situations I’ve described above, managing the orders in your trading platform is difficult and more prone to costly errors than normal. Imagine the URBN scenario where you’re managing two sets of exit orders from two different entry points. Now — which set corresponds to the first entry and which to the second? What size should the positions be? The additional orders alone add complexity to our position management.

Not only are there more orders to manage, but any mistake we make is magnified since we’re adding size! No room for errors!

There Are Much Easier Things To Do Than Scaling In

Even with the extra complexity that scaling into positions introduces, I’m open to the possibility that it can be done profitably — it’s just nowhere near as easy as some would have you believe.

There’s a whole range of things traders could do to improve their trading that are easier than scaling in — for example, are you giving your winners enough room to trend? Should you use a target order? Should your stop be looser? Tighter?

A better approach to variable sizing would be to try to determine when a system’s edge is the strongest and use a larger trading size when that situation occurs and a smaller trading size when the edge is weaker. You could do this by assigning a score (0–10) to your trades prior to entry time based on some criteria that you’ve researched. This could serve as a “confidence score” and you could use a larger initial size for trades with a higher score.

Conclusion and Caveats

I feel that most traders are better served not scaling into trades. But, there are some important caveats that I want to mention.

You may have to trade with a large enough size that you simply can’t enter your entire position in one order — in this case look at IB’s Accumulate/Distribute algorithmic order type.
Longer term overnight trading can give you more time and flexibility to scale in more profitably.

Do you scale into day trade positions systematically? I’d love for you to change my mind on this.

How to Visualize Your Stock Watchlist

2018-11-05T01:57:00-05:00

I’ve been posting my watchlist to my Twitter for some time now. In the olden days of Trade-Ideas, the only window type available was an alert window — a great tool for tracking specific events in real-time across the entire market. For example, you can have an alert window notify you when stocks reach a new 30 day high.

But what if you were looking for stocks that were gapping but weren’t near 30 day highs or lows? It’s nice to be able to rank the entire market by certain criteria even if stocks hadn’t broken new highs or lows yet. That’s why several years ago we added Top Lists to Trade-Ideas. It took a while for users to realize how powerful the top lists are, so uptake was initially slow. As I predicted, though, they’re closing in on being the most popular window in Trade-Ideas now. Even with the increasing usage over time, I say they’re still undervalued.

Thinking of an Alternate View

I spent a good bit of the last couple of weeks brainstorming ideas around the top list. The standard grid view is awesome, but when we look at a column of numbers it’s hard to get a real sense of the distribution of values contained in each row. Sure you can sort and even apply custom colors to a column to make it pop, but it’s still confined to the grid view which makes it hard to visualize the range of numbers.

Take a look at this screenshot from my watchlist from yesterday:

The color coding helps but it’s hard to quickly recognize that the relative volume for GSKY was twice as high as any other value in the list and the top 4 values (GSKY, TWOU, AAC, VCEL) were vastly higher than any other value.

My Initial Prototype

I wanted to create a view that lets you see the magnitude of the differences and gauge the order of the values without having to sort the column. Here was my first stab at a different top list view.

This is a scatter plot across two dimensions. In this case, the dimensions are Gap Bars and Relative Volume, two important values that I use in determining which stocks to trade and how to trade them. This view lets you visually see the four highest values in relative volume at a glance but also how extreme they are in terms of the gap.

I chose Gap and Relative Volume for the X and Y axes, but you could choose any two columns from the top list. Here’s one with Price on the X axis and Volume on the Y axis:

But We Can Do Better

So far so good, but I think we can improve on this. We can add more dimensions to the view.

Here I’ve added a gradient color as the background of the labels based on the Float of the stock. The darker blue the label, the smaller the float. The lighter the label, the higher the float. You can quickly see that GOGO has the highest float in the list and OUT, MYL, SPLK, MAR, ABC, and UNVR have low floats relative to the list. The point shares the same background color as the label.

Final Prototype: A Four-Dimensional View

There’s one more dimension we can add: the size of the label. Here I’ve added the Position in Range as a parameter in the view. The closer the stock is to its high of the day, the larger the label is. For example, OUT is closer to its lows relative to VCEL which is closer to its highs.

What we end up with is a visually appealing view of our top list across four different and distinct dimensions — completely customizable by using any combination of columns in the top list.

So what do you think? Any changes you would make? I’d love to hear from you.

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All Gaps Are Not Created Equally

2018-10-30T01:03:00-04:00

To trade intraday, you need to find stocks with the potential for movement. Gaps are one of the best ways to identify stocks that have that potential. On any given day there are typically plenty of gapping stocks to choose from — sometimes there can be an overwhelming number of them. We all have a finite amount of capital and time — how do you decide which gapping stocks are important?

You can use a filter for the dollar amount of the gap, say $2. This might work well for lower-priced stocks, but high-priced stocks like AMZN routinely gap $30 or more.

How about using a percentage of the previous close price? This is definitely a better approach and a common one that most traders make. (Gap % is one of Trade-Ideas’ most popular filters used in just over 10% of strategies.)

An Undervalued Approach to Gaps

While most traders stop at using Gap %, this approach leaves out valuable information that can help you determine just how unusual the gap is in a particular stock.

Some stocks are what I call “gappy” — that is, they routinely show up on my gappers scan when I use percentage as a threshold. In other words, an opening gap for some stocks just isn’t all that special. When it’s not unusual, it doesn’t attract other traders' attention which is required for a stock’s price to move.

The next level for scanning for gaps is to use what is called Gap Bars. This looks at the gap not in dollars or percentage terms, but in terms of the particular stock’s normal volatility — how much it normally moves on a routine day. At first glance, you’ll notice that Gap % and Gap Bars are highly correlated, but there are subtle and valuable differences.

Here’s a great example from last Friday from my daily gappers list.

The first thing you notice is that these gaps look pretty similar. LSCC and SNAP were roughly the same price ($6.16 and $6.28) and the Gap % was in the same ballpark (-15.1% and -12.7%).

But when you look at Gap Bars they’re very, very different (-31.7 and -11.7).

Look at the Charts

A quick glance at the charts and you’ll notice the subtle difference. The chart in SNAP shows that the gap is more routine in the context of the market action over the most recent several days.

Compare this to the LSCC chart and it’s easy to see that the gap in LSCC is just far more significant. So even though the gaps are practically the same in terms of dollars and percent, when you include volatility the gap in LSCC stands out as far more unusual which is exactly what we’re looking for.

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How To Trade When The Entire Market is Moving

2018-10-26T10:04:00-04:00

I’ve been trading gaps since 2005 with a statistical, data driven approach. I’ve put in a lot of quality time outside of trading hours backtesting, looking at charts, and developing software to carry out my trading plan. When you take trading seriously and instill a positive, improvement-focused attitude in yourself, once the market opens you should be executing a plan that you’re totally prepared for. You should essentially be following a script.

My Trading Script

I trade several strategies every day. My main set of strategies, though, follows this routine:

Ha! I’m joking about #5 — once my trades are in I literally don’t watch them for the rest of the day — no kidding.

The vast majority of market days this works well. But what happens when every stock in the market looks “tradeable?”

On Big Market Days, Everything is Moving

On < 5% of market days, most every stock looks unusual!

These are the hardest types of days to deal with — there’s a lot of opportunity but you can’t realistically take every trade that looks unusual. It’s easy to get overwhelmed and become paralyzed on days like this. The problem is there is a lot of money to be made on these days so it’s good to prepare for them ahead of time. Here’s what I do.

Today there were 64 stocks on my top list for this strategy when there’s normally ~10–15. The first thing I do is look at this top list that looks at a single stock: SPY. (Here’s the cloud link.)

I see that the SPY which represents the S&P 500 is trading at 13.8 relative volume. If SPY was trading “normally” it would have a relative volume of 1.0, so this means the SPY is doing 13.8 times it’s normal volume at this time of day — that’s a lot! Here’s what my unfiltered watch list looked like at the time (notice the vertical scroll bar!)

This top list also includes the relative volume column. If stocks have unusual activity but on lower relative volume than the overall market, then they’re not really that unusual even it a stock is doing 4 times its normal volume.

Here’s what the top list looks like after I’ve applied some custom coloring to the Relative Volume column:

The column comes alive showing you what is really unusual today compared to the overall market. Solid red shows me that it’s well below the threshold I’ve set. Darker blue tells me that the relative volume is unusual even on this market day. Lighter blue to white means it’s above the threshold but not by a ton.

This let’s me quickly see what is REALLY unusual given what the overall market is doing. I can very quickly and confidently narrow my list using data that I can rely on.

Try Trade-Ideas Now to Take Your Trading to the Next Level

If you liked this post, follow me on Twitter @davemabe to see my daily watchlist and links to future posts.

How I Trade Gaps

2018-10-24T21:52:00-04:00

I’ve been trading gaps for over a decade. Over the years I’ve refined my trading routine using statistics and machine learning to figure out what works for me and what doesn’t, determining which gapping stocks I should trade and which ones I should ignore, how to best trade up gaps and down gaps, and automating as much of my trading process as possible.

Not all Gaps are Equal

Gaps up, gaps down, large gaps, small gaps, gaps with high volume, gaps with low volume — there are all sorts of different types of gapping stocks each day. How do you decide:

Of course these are not easy questions and it can take years of experience to get closer to the answers. What you’re primarily trading to answer is: will the stock have movement after the opening gap? If it is likely to move, then it’s tradeable.

My Daily Trading List

Each day I post my curated list of stocks that are on my gap trading radar for the day. This list mostly comes from my Trade-Ideas scan which I’ve honed over years of trading to efficiently generate a list of gaps which are worthy of possibly trading that day. My Trade-Ideas top list looks like this:

How I Use My Trade-Ideas Watchlist

This one view of my watchlist in Trade-Ideas gives me a succinct view into the data points I need to make trading decisions. It’s sorted by the Gap% column so I can visually determine which stocks are gapping up or down and by how much. Green background means gapping up, reddish background means gapping down. The darker the green or red means the bigger the gap.

Other Important Columns Color Coded

Other data points that I’ve statistically determined are important for trading gaps are color coded. With just a quick glance I can see some stocks are more tradeable than others and some should be considered a priority gapper today.

Stocks that Will Likely Move After the Opening Gap

The list that I post each day has been curated by me to include only the stocks that have high likelihood to move after the opening gap. I don’t determine the direction for the purposes of this list, but potential for movement = tradeable.

Only once I determine that the stock has a good chance of movement after the open will it make my daily tweet:

How do I Trade These Gaps?

I use 4 different strategies to trade these gaps: 2 long and 2 short. Over the years I’ve made the actual order execution as quick and painless as possible. When I started trading over a decade ago, I entered the trades manually. I quickly realized that there were two main ways this was hurting me:

I eliminated both of these problems using software. I started developing my own software to enter the trades. A combination of man and machine helped me take more profitable trades and eliminate all my order entry mistakes. I quickly learned that entering trades this way opened up lots of new opportunities to trade profitably.

I’ve gone through several iterations of the trading software over the years: fine-tuning certain aspects and adding new features that over time I discovered that I needed. That process has culminated in the Trade Client.

SPY since 2000 - Overnight vs. Intraday

2018-07-28T19:17:00-04:00

In a recent post about the Last-Hour Trading Technique, I mentioned one of my assumptions about the overall market. I think I read somewhere that most of the gains in the SPY are from overnight gaps rather than intraday movement. If true, of course, this implies that there is a lot of money in the overnight gaps and suggests that some swing trading strategies should have a strong position in your trading arsenal.

But I was curious and being someone that likes to verify things rather than blindly follow what the crowd says I thought I’d test this theory to make sure.

What I found surprised me — it’s a little more complicated than a binary yes or no answer.

So I tweeted a poll to see what people thought:

Buy at the open, sell at the close (“intraday”) versus buy at the close, sell at the following open (“overnight”). The responses were pretty soundly in the overnight camp, but not overwhelmingly so.

When I ran some tests I initially thought they confirmed the overnight theory — the final overnight number was solid while the intraday number was basically unchanged. But I decided to look at the equity curves and I see a more complex picture. The difference between the two are negligible since 2009 and, in fact, the intraday system outperformed the overnight system slightly.

Why would this be? I’m not sure, but my main theory is general efficiency argument — over time the markets are getting more efficient.

I’d love to hear other theories in the comments.

Another important takeaway for traders from this exercise: A picture shows so much more than a final number — Always look at the equity curve!

Last-Hour Trading Strategy by Ashwani Gujral

2018-07-23T18:04:00-04:00

This is the sixth in a series of articles summarizing the monthly trading strategy article in the Technical Analysis of Stocks and Commodities monthly magazine.

System Type: Overnight holding

Author of article: Ashwani Gujral, author of How to Make Money in Intraday Trading and on Twitter @gujralashwani.

The Last-Hour Trading Strategy

Gujral outlines his process for his last-hour trading strategy. He takes a position in the last hour of the day, holds it overnight, and exits in the first hour of the following trading day. He seems to have a lot of rules for this strategy that he doesn’t go into a lot of detail about. The overall idea seems appealing — the first and the last hours of the trading day typically have the most action. Add to that the overnight where you can have serious gaps and you’re really only participating in the most volatile activity of the trading day. Here are some of the guidelines he mentions in the article:

There’s always a setup — it sounds like he’s always taking at least one trade
By the end of the day “it’s clear” which direction the overall market has a bias towards, which are the strongest and weakest groups of stocks, and which stocks are breaking out of daily ranges
Look for breakouts on high volume in the last hour of at least 3% up or down from the previous close — a perfect use for Trade-Ideas
Claims this system has an 80% win rate
Since it fails 20% of the time “get out fast when you realize something is not working.”

Here’s a well-chosen example of a trade with this system:

My Thoughts on This System

The article lacks a lot of detail about the actual rules of the system, but I don’t think his point was to provide a blueprint. He describes a valid system that’s worth thinking about. The most appealing part is that you’re literally only holding a position during the parts of the day where statistically there’s typically the most movement.

There’s a lot of money in those overnight gaps. I remember reading an article some time ago that mentioned that if you took out all the overnight gaps in the SPY it’s close to unchanged for some long period of time. I haven’t tested that but the point is valid — most of the news comes out after hours. When you day trade you specifically avoid these gaps.

Of course, this strength is also a serious weakness. When you hold overnight it’s only a matter of time before a stock you’re holding gaps against you hard. For this reason, I’m always skeptical that I could get a system like this to work well in the long term.

Ironically, one of the main reasons I day trade is so I can sleep well at night. If I need to be away from my trading desk one morning on a whim — no problem, I’m all cash. This is counterintuitive to most people who believe day trading is all stress.

One way to incorporate overnight gaps is to extend your holding period for a day trade into the following day for a system where you’re normally exiting prior to the market close. This is where I’ve spent the bulk of my research on overnight gaps over the years, although it has been a couple of years since I’ve looked closely.

My problem with this approach is how do you decide which trades to hold overnight and which to exit normally prior to the market close? If you can determine that, why should it matter that you happen to be holding the position? That is, if this is a statistically profitable segment of time to be holding certain positions, then it makes sense to have a separate system for this segment. Extending the holding period of a system to the following day feels like a form of the sunk cost fallacy. I’m holding this position so I might as well gamble and hold it overnight and see what happens.

TODOs

Take a fresh look at this type of system — taking a position late and exiting early in the following session.
Do an analysis of the overnight gaps in the SPY and quantify how much of the overall movement is overnight versus market hours.

Question

Do you extend some trades overnight until the next day’s session sometimes? How do you decide when to do that?

TASC #5 — Most Traders Expect Too Much or Too Little From Candle Patterns

2018-05-17T01:10:00-04:00

This is the fourth in a series of articles summarizing the monthly trading strategy article in the Technical Analysis of Stocks and Commodities monthly magazine.

System Type: Candle stick patterns

Author of article: Sylvain Vervoort, author of Capturing Profit with Technical Analysis

The Four Bar Candle Pattern That’s Supposed to Indicate Reversals

Sylvain makes an argument for a particular candle pattern that shows up in four different ways. There are two sets of patterns — one for uptrends that are reversing (the “downstep”) and one for downtrends that are reversing (the “upstep”).

As in almost all articles of this kind there are some well chosen charts that show how perfect the candle pattern can be.

Usually Two Responses, Both Wrong

At this point there are usually two responses to these types of candle patterns. Some traders will look at the well chosen example chart and, despite a little skepticism, will do some further study looking for the particular pattern and build a trading strategy around it. Another group of traders with a little more experience will look at this pattern and dismiss the idea entirely. They used to be the first type of trader but feel like they’ve been around the block and that candle patterns and simply voodoo and will quickly dismiss them.

Both of these responses are the wrong way to think about candle patterns. They both are approaching the candle pattern as if the pattern itself is the trigger to build a trading system around.

A candle pattern alone is (almost?) never enough to use as a trading system. It has to be combined with several other filters and only when they are satisfied might the candle pattern have a statistical significance within a trading system. To use them as the primary trigger in a system is not likely to work out, but don’t dismiss them so soon.

A Better Approach

They way I like to think about candle patterns is to see if they appear in some of my already existing trading systems. Trading systems are usually either trend following or reversal systems. Because all systems are based on price action and candlesticks are just one way to reflect that price action, the trigger in your trading systems will necessarily be preceded by some candle patterns. It’s likely you can examine those preceding bars and put them into a finite set of categories of patterns.

You’ll probably find that some of those categories perform better than others. This often leads to more interesting questions:

Can I increase trading size when a certain pattern appears in my system?
Can I completely eliminate some losing trades by skipping some categories of trades within my system?
Can I fundamentally alter my system in such a way to capture more trades within a certain profitable category?

These are all good, thought provoking questions that traders should always be asking. Remember — the bar is pretty low — lower than many people think. If you can find something that’s statistically significant within the random noise of the market that consistently improves your trades just slightly — that can be very valuable.

TODOS

There are two ways I could see exploring this particular step up/down pattern. One would be categorizing the previous patterns in a couple of my systems on an intraday level. Another might be to take a broader look at the daily charts on my intraday systems. That is, what daily patterns precede the day where a trigger occurs? Both of these are useful exercises for further exploration.

TASC #4 — Should You “Trade” Your Equity Curve?

2018-05-08T01:17:00-04:00

This is the fourth in a series of articles summarizing the monthly trading strategy article in the Technical Analysis of Stocks and Commodities monthly magazine.

System Type: Equity Curve

Author of article: Oscar Cagigas, no Twitter but here’s his web site (Spanish): http://onda4.com

Deactivate/Activate you System Based on the Equity Curve

Oscar suggests a rule based way to toggle trading on and off based on the current equity curve of a trading system. He compares several different methods for doing this. The simplest is based on a moving average of the equity curve. If the equity curve falls below the moving average, simply ignore new trading signals until the equity curve rises back above the moving average. Sounds simple, right?

It’s more complicated than it seems. Of course, if you waited for your ACTUAL equity curve to rise when you’re not trading it you’ll be waiting forever. Because of this you have to keep track of the SIMULATED equity curve as if you didn’t pause your trading. This chart shows the process but it took me a few minutes to understand exactly what the lines meant.

I think the chart is overly complicated because it is overlayed on the Silver price chart which, although it’s the market for the system he’s trading, it’s secondary to our main purpose. The black line is the SIMULATED equity curve that we’re using as a reference. The blue line is the ACTUAL equity curve representing the subset of trades from the system that we actually take. By the end of 2011 you can see that the blue line ends up much higher than the black line.

He goes through 6 different methods to activate/deactivate your system based on certain aspects of the equity curve — the slope, different moving averages, a Donchian channel, etc. There’s a thoughtful discussion about this entire exercise just being an opportunity to overfit which he is careful to try to avoid. He also tests his methods using out of sample data which reduces the chance that he’s curve fitting. All the methods he tested showed varying degrees of improvement over the original reference equity curve.

My Take on Trading your Equity Curve

When I read this article my first thought was that making trading decisions based on your equity curve would overly complicate things. The underlying trades within your system don’t care what your equity curve looks like. If there was some correlation between the performance of trades and some aspect of the equity curve then you could pretty easily test it. If you detect any correlation my guess is it would be very small.

Keeping up with the reference equity curve, while not an impossible task, is definitely not a negligible chore. The process would be to run a backtest probably each night and chart it and see whether to activate or deactivate for the following day. Multiply this by the number of systems you have and it quickly becomes a lot of work and attention.

But Wait — We All “Trade Our Equity Curves” Whether We Realize it or Not

The more I thought about it the more I realized that we all “trade” our equity curves to some extent. If your account heads to zero you’ll be forced to reduce size since your buying power will be shrinking the whole way down and eventually, the deactivate switch will be set for you. Most of us would reduce position sizing long before that hard limit. That pain point is different for everyone and while a lot of traders would take action to avoid a big drawdown, I suspect many might not be able to articulate a well-thought-out plan ahead of time. Without a plan, we’re susceptible to fear and greed and our own human nature to make mistakes in the heat of the moment just like we are during the lifetime of each trade we make.

So is this “trading your equity curve” or a “well-designed money management plan”? A little of both.

My TODOs

Like my last post, I have a to-do item that’s tangentially related to the article. Put some thought into some better-defined rules for scaling down size during drawdowns. Periods of drawdown are inevitable and it’s well worth having a plan to react to them.

TASC #3 — Camarilla Points by Slawomir Bobrowski

2018-04-27T01:21:00-04:00

This is the third in a series of articles summarizing the monthly trading strategy article in the Technical Analysis of Stocks and Commodities monthly magazine.

System Type: Range trading

Author of article: Slawomir Bobrowski, no Twitter or online presence that I could find other than this strange article about a trading system based on a passage in the book of Deuteronomy.

Like Pivot Points, but Different

Pivot points are a fairly common method traders use to define significant support and resistance levels based on the previous day’s trading session. They are several levels that are typically used: S1, S2, S3, etc for support levels (below the price) and R1, R2, R3, etc for resistance levels (above the price). S1 and R1 are the closest to the price and the larger the numerical value in the pivot point the further away that point is.

Camarilla Points are based on the same concept but:

Use different formulas for the price levels
Can be applied to a range of prior days rather than just the previous day

Here are the formulas for the camarilla points:

R5 = (High / low) * Close
R4 = Close + Range * (1.1)/2
R3 = Close + Range * (1.1)/4
R2 = Close + Range * (1.1)/6
R1 = Close + Range * (1.1)/12
S1 = Close - Range * (1.1)/12
S2 = Close - Range * (1.1)/6
S3 = Close - Range * (1.1)/4
S4 = Close - Range * (1.1)/2
S5 = (Close -(R5-Close))

Strategy for Trading the Camarilla Points

Here’s a chart that shows the points on a chart of the Dow from 2012. The idea of the system outlined in the article is that you wait for the price to reach R3 or S3 and trade that move until it reaches the opposing point. S4 and R4 are used as breakout triggers — that is, you trade with the move (in the image above, short at [3], buy at [4]).

The R3 and S3 levels typically seem to be fading a move like in this example. Buy at [1], sell at [2].

My Takeaways

I’ve always pretty much ignored pivot points. I know a lot of traders pay a good bit of attention to them and some of them are quite successful using them. Here’s why I’ve ignored them up until this point.

The pivot points are derived from the actual price levels from the previous day. Why focus on data points that are one layer of abstraction away from the actual source of the pivot points? At least start with the actual previous day’s prices (open, high, low, close) directly and see if those affect system performance. This is why I focus on the previous day’s close, high/low, and open in that order. The more recent price level is more important, so the previous close is significantly more important than the previous open.

However, as more and more traders look at a derived data point, the more you should be willing to pay attention to it simply because of the decisions traders are making based on it. For example, common moving averages (50, 200) are typically more important than a more obscure indicator that nobody has heard of.

As far as I can tell, pivot points don’t meet that attention threshold for me. Where does that leave the camarilla points? Given the fact that I’m guessing not a single person that reads this article will have heard of them, then the attention traders give it is minuscule or non-existent. Also, the arbitrary nature of the formulas and timeframe you apply it to make it seem weak — for example you could take any chart and come up with a timeframe for the camarilla points that works well.

My TODOs

So I’ve dismissed the camarilla points. Does that mean this was a worthless exercise? I don’t think so. It does spurn me to take a closer look at the standard pivot points and see if they have any affect on my trading systems. The nice thing about backtesting is that you can come up with a prediction about some aspect of the markets and test it. My intuition tells me that the previous days price points matter more than the pivot points. I’ll do some testing and report back my results.

Smiles and Frowns by Thomas Bulkowski — TASC 10/2013

2018-04-26T01:24:00-04:00

This is the second in a series of articles summarizing the monthly trading strategy article in the Technical Analysis of Stocks and Commodities monthly magazine.

System Type: Trend following

Author of article: Thomas Bulkowski http://thepatternsite.com/ and he has several trading books on Amazon.

Trading with Personality

Thomas Bulkowski introduces a pretty simple concept which he calls smiles and frowns. These are basically new trend highs and new trend lows as seen in this graphic from the article.

He identifies 6 points on this oversimplified chart and concludes that C is the best entry point and D is the best exit point. Why not A and F? Those are the exact same prices as C and D, so why not use those?

Because using C provides confirmation and at least a chance that the price isn’t going to continue to fall. D instead of F because it’s better to get out too early than too late.

This is the definition of trend trading. Although this concept as outlined in the article is nowhere near an actual trading system, it does provide a basic framework for trend trading. A question you should always ask yourself when designing a trading system is what is the move I’m trying to capture? Is your system reverting to the mean or riding a trend that you expect will continue?

Important points about smiles and frowns:

Buying at point A is bad because you have no idea where the bottom of the move will be
Point B provides the perfect entry point but only in hindsight
Point E is the perfect exit point but in real time it’s never obvious where that is
Point D is better than point F because prices fall faster than they rise so it’s better to get out too early than too late
Also, in general, shorter hold times reduce overall market exposure and frees up capital for additional trading opportunities
He suggests using a moving average shifted to the left (making it slower) on a line chart to better identify smiles and frowns

My Takeaways

A “system” is too strong a word to describe this article. It’s a good basic framework for trend following and serves as a good reminder of the characteristics of all such systems.

His suggestion that “selling too early” is good and his trades confirm this make me want to double-check that the hold times in my systems are optimal. For example, for some of my intraday trend-following systems I normally hold until the close — perhaps testing some way to exit earlier in the day would make sense. If most (but not all) of the profit comes early then it might even be logical to exit earlier even if there’s a little bit of profit that comes later in the day.

Fusion Trading by Josh DiPietro — TASC 8/2015

2018-04-25T01:27:00-04:00

This is the first in a series of articles summarizing the monthly trading strategy article in the Technical Analysis of Stocks and Commodities monthly magazine.

System Type: Mean reversion intraday trades that can turn into swing trades

Author of article: Josh DiPietro from https://www.daytraderjosh.com/ and no activity on his Twitter https://twitter.com/Day_Trader_Josh

Josh gives a rough outline of a system he calls “Fusion Trading”. It uses a combination of important price levels on the daily chart with similar levels on the intraday chart. When these levels line up and the price reaches these levels, the setup is in play. Rather than take trades exactly as these levels are hit, he waits until the price continues beyond the level by 25 cents, 50 cents and 1 dollar. The further beyond the price level, the more reliable the trade is. These important daily price levels must have held for 10+ days, so when the price hits them it will have been a quick move to get there. The “fusion” trade is trying to capture a small pullback from that move as it bounces near these important price levels.

Here are some important points about this system:

Important prices are determined before the market open
These prices come from four levels: Premarket highs/lows, previous day highs/lows, daily chart highs/lows, newly formed intraday highs/lows
The price levels are “close” to each other and used to ladder in to a position
Important to know points for initial entry and then secondary entry points (for example, $0.50, $1.00, and $2.00 below the important price level)
Has maximum of three tiers for laddering into a position
Must have a longer term swing price level within $3 of the initial entry point, otherwise not valid
For intraday trades, he uses different price levels prior to 9:45am than after that time
Trades only higher priced stocks since they move a lot and are large enough that big institutions are trading them
As with all “catching a falling knife” trading strategies, you have to be willing to tolerate being in the red a good bit of the time
He alludes to having previously used $0.15 increments for entry point ladder and profit taking ladder, but switched to $0.50 increments — doesn’t fully explain why
He has some rules for turning an intraday trade into a swing trade and goes through an example but I didn’t really follow the logic
Says he has “literally 100 more rules and procedures for capturing the correct entry levels”

My Takeaways

The alignment of daily and intraday levels might be worth pursuing. I could see developing a way to automatically identify these levels and incorporating them into my own systems. It would be interesting to identify these areas and see if performance is correlated to the distance from important daily points. Using them as a filter would, I suspect, drastically reduce the number of trades in the systems I have in mind — especially if combining a swing and intraday price level.

Treating VERY high-priced stocks as a different universe all to their own I think makes sense. It’s probably worth looking at my systems only on high-priced stocks.

Turning intraday trades into swing trades has always made a lot of sense to me but I’ve never found a system that I’ve backtested where the data has shown me a clear path to doing it. Holding a position overnight simply because it hasn’t hit a stop or target that you thought would hit intraday seems like a volatility crap shoot.

Trading Ideas from Old Technical Analysis of Stocks and Commodities (TASC) Magazines

2018-04-24T01:29:00-04:00

I had a subscription to Technical Analysis of Stocks and Commodities way back several years ago. I wrote a few articles for them that ended up being published. As the owner of a web trading software company that occasionally advertised in the magazine, they’ve sent me the magazine for several years now.

I have to admit — I rarely read it. I typically glance at the cover to see who this month’s interview is with to see if it’s someone I know. I also glance at the trading strategy article to see if it’s worth reading.

I have, however, for reasons I can’t fully describe, saved almost every magazine I’ve received. I thought that one day I would troll through the archives looking for trading strategy ideas. My archive has swollen to over a foot of shelf space. I considered simply tossing them.

I thought a better idea would be to blog a summary of the trading idea from each magazine. Finding a fully formed trading strategy in the magazine is almost certainly a pipe dream — I realize that most people that write articles for TASC are indirectly marketing some product and/or raising their public profile. What other incentive would you have to give away a working trading system in such a public way?

The point of reviewing these old trading ideas is not to find something to trade as-is — it’s to stretch your trading brain and get out of your trading rut. We all have to work hard to think of unique trading ideas. It’s arrogant to think that we have all the trading answers instilled at birth or even learned through the years of experience of one person. It’s also silly to expect to read a few articles and come away with a profitable trading strategy. The best that we can hope for is something in the middle — see how other people think differently about the markets and see if there are some nuggets that we can incorporate some aspect of their ideas into our own to create something unique.

I’ll be taking each of the magazines in my archive and writing a summary of the trading strategy article before it goes to the recycle bin. The goal is to add some ideas to my trading strategy vault. My goal is to post a new summary regularly. We’ll see how it goes.