Why Trading Strategies Are Not Working: Identifying and Avoiding Common Pitfalls

Why do trading strategies stop working? When do you stop trading? How can you avoid or minimize that trading strategies stop working? These are the most important aspects in trading because most trading strategies stop working – sooner or later. Many traders would hope a strategy lasts forever, but markets are not meant to be static. Markets are dynamic and evolve and change both gradually or suddenly. You better be prepared or at least minimize damage if (or when) it happens.

Strategies stop working mainly because of curve fitting, structural and cyclical changes, survivorship bias, behavioral mistakes, commissions, and slippage. Short-term trading is a zero-sum game and you need to accept that trading strategies at one point stop working. You better be prepared!

The better the foundation of your business plan, the fewer trading strategies stop working. The more you prepare for inevitable trading hiccups, the less they matter. Imagine yourself having one or several trading strategies that are literally handing you money on a silver plate. Then one day everything stops working and you are stranded with no strategies that seem to work! You don’t want to be in that situation.

Unfortunately, trading strategies do stop working. In this article, we look at reasons why trading strategies are not working or stop working and how you know a trading strategy stops working.

We backtest trading strategies and systems on a daily basis. If you are looking for a short term trading system, please click on the link (we have made hundreds of strategy backtests).

Table of contents:

Trading is all about backtesting and generating ideas

Markets change all the time. Good traders know this and adapt by constantly looking for ideas to put into live-action. By being prepared you minimize the damage when strategies stop working. We have personally had very profitable trading strategies closed literally from one day to the next due to new regulation and legislation. You never know what is being thrown at you.

Any quant trader should spend at least 80% of their time backtesting and brainstorm for ideas. There are plenty of ideas both for free and as subscription services on the internet. This website has hundreds of free trading systems and strategies, and around 100 paid premium strategies for our members.

What are the chances of finding a tradable trading strategy? Probably around 1 in 20 backtests show promise. Of the one in 20 that passes our backtesting criteria, very few make it past the incubation period (see below).

As you can understand, this is a time-consuming process! But in the long run, you get rewarded because you’ll have fewer strategies that stop working and your trading becomes more robust. If you don’t know how to backtest, read here for how do you perform a backtest?

Understand why strategies are not working

To better understand why a trading strategy is not working (or perhaps stops working), you need to understand why trading strategies fail:

Not long enough backtest and no out of sample test

A backtest needs to generate many trades to be of any significance. Moreover, it needs to be of significant length. A lot of traders only use a limited time frame and thus are more liable to randomness and cyclical trends in the market. Make sure you have tested your strategy over many years and in many different investment climates.

For example, the bull market from 2008/09 has been pretty long and all driven by quantitative easing from central banks. Prior to 2008/09, there was no quantitative easing. Thus, the momentum strategies that worked then will most likely face a pretty hard time when the easing stops.

Put simply, most trading strategies are not adequately backtested. Some strategies work fantastic a couple of years before they fade away. Breakouts might work in a rising market, but less so in a sideways and falling market. Be sure to test in all types of markets.

And make sure you have a proper out of sample test. Divide your dataset into two parts: one for in-sample and one for out-of-sample. Read more here:

Also, an incubation period of many months can save you a lot of money:

Incubation period: test every trading strategy live in a demo account

When you have found a promising strategy in a backtest, you should paper trade it for many months in a demo account.

We like to call this the incubation period. It’s time-consuming but this “trick” saves you money in the long run and makes it less likely your strategies stop working. And when your strategy stops working, you are prepared for it.

If you have done a live test and are pleased with the result, you can start trading it live. The majority of the trading strategies we test via incubation never make it to live trading with real money.

The strategies that pass the incubation period normally last for many years. The incubation period is an excellent way of minimizing the strategies that stop working.

Always quantify your ideas

We believe automation is superior to discretionary trading. Automation has two main advantages.

First, you can trade and execute an unlimited amount of strategies. The computer does all the trading for you.

Second, you minimize second-guessing and behavioral mistakes. The less you stare at the screen, the less likely you are to screw up by doing something not planned. The fewer screw-ups, the less likely a strategy stops working.

Why? Because many strategies stop working because you start tweaking your strategy or skipping signals. Automation rand mechanical trading strategies emoves many behavioral mistakes.

Trading strategies stop working because of curve fitting

When something is curve fitted, it is just a question about time before it ends up useless. Curve fitting happens because of too many parameters and criteria and too short a time period for the backtest.

The best trading strategies for the long term are those which have the fewest parameters. Trading needs to be simple and easy.

Simplicity reduces strategies stop working

Many traders spend months tweaking one “super strategy”. We believe this is wrong for two reasons:

First, you risk curve fitting or going round in circles. You should be very careful in changing parameters, at least only after rigid backtesting and incubation.

Second, you risk ending up with more parameters than necessary (and thus curve fitting). The best trading strategies are always those which have the fewest parameters.

Third, you want many strategies, not just one good one. Several “not so good strategies” are highly likely much better than a “super strategy”.

Structural change makes trading strategies obsolete and they stop working

We believe the best trading strategies are based on some structural edges.

By structural trading edges, we mean an edge that is built on how an exchange operates, for example. The specialist system on the NYSE was another example of what we consider a structural edge.

We had great success for some years trading the opening imbalances at the open on NYSE, a strategy called opening price trading strategy. But all good things come to an end, and the change to electronic trading made the specialist system almost obsolete. Thus, our best strategies simply stopped working.

How the stock exchanges operate tremendously impacts how strategies work (or do not work).

Another example of a structural market edge is the turn of the month effect (this one could be labeled cyclical as well). We suspect this effect happens because investors and savers allocate more money to stocks at the end and the beginning of each month.

We believe it’s easier to diagnose any problems with structural effects than many other edges and they are less likely to stop working.

Cyclical change makes trading strategies difficult to trade and follow

Some strategies work well in certain types of markets and not so well in others.

For example, trend following has always had many years of underperformance before they start working again. This makes them very hard to follow and trade, and that’s perhaps the reason why they seem to work in the long term.

The Dogs of the Dow strategy was once a very good but less so the last ten years. Is this a cyclical or a structural change? Permanent or temporary? We don’t know, but the markets have evolved and changed since the strategy became very popular.

For example, Ben Bernanke started quantitative easing, which has greatly impacted asset prices and behavior. Is this permanent or temporary? We don’t know, but it sure changed the market!

Being dependent on one type of strategy makes you vulnerable

Some only trade mean reversion, and others only trade trend following. Likewise, some are day traders, and some are swing traders.

We believe this is a mistake for many aspiring traders. You should be agnostic and trade anything that works. You need to diversify as much as possible to smooth earnings – you need a portfolio of trading strategies .

One dollar made in crude oil is the same as one dollar earned in day trading Microsoft. One dollar made day trading is the same as one dollar made in a weekly time frame. We believe the most rational approach is to diversify to different time frames. Why? Because not all time frames stop working at the same time.

Strategies are not working because of survivorship bias

This is something all traders ignore (or forget). They tend “forget” because survivorship bias in trading should be just a minor problem – a detail?

No, unfortunately, survivorship bias can have a huge impact. We have covered this in a separate article which we strongly recommend reading:

Behavioral mistakes make you not follow the signals of the strategy – thus you have no strategy

The first requirement to a trading strategy is that you should trade all signals the strategy tells you to do. But trading biases always put a spanner in the works. It’s easy to skip a trade after four losses in a row or if you are in a drawdown!

But this means, in reality, that you don’t have any strategy in the first place if you skip trades. It’s almost impossible to know before you trade a signal if it’s going to be a winner or loser. The markets are unpredictable and usually not intuitive. You have not backtested omitted trades, and thus you have no strategy. Many quants become discretionary traders by skipping trades.

Commissions and slippage are underestimated

Because of structural changes, like described above, slippage might increase or decrease depending on certain factors. For day traders this might be the difference between a lot and nothing.

However, if you stick to very liquid assets, slippage should not be a problem. We measured slippage in live trading.

Inefficiencies get arbed away

Eventually, all inefficiencies in the markets get arbed away. A strategy can become too well known, for example, when a book is written about the strategy.

Short-term trading is a zero-sum game

Always keep in the back of your head that short-term trading is a zero-sum game. If you invest for the long term, you get a tailwind from the gradual increase in prices (inflation) and earnings growth. This takes time to get reflected in increased share prices, but traders don’t have this luxury. You might want to consider what is best – trading or investing.

The options and futures markets are a 100% zero-sum market – even negative considering the costs. What you make, someone else must lose.

Because trading is a zero-sum game, you can’t expect trading strategies to work forever. They sooner or later stop working:

Almost all trading strategies stop working – sooner or later

If you find a good trading strategy you need to accept that sooner or later it will stop working – preferably later, of course.

This is the sad fact of trading. If you’re a long-time buy and hold investor, you don’t need to worry about this. But if you’re a trader, you need to understand that trading is a constant battle of having an arsenal of trading strategies.

When to stop trading a deteriorating trading strategy?

You have hopefully found a few leads in this article.

But the best advice is to set up a list of potential red flags BEFORE you start trading a strategy live. How much of a drawdown are you going to tolerate? When is the logic behind the strategy flawed?

You are much better prepared if you write down some arguments in your trading journal (every trader should have one).

How do you know a strategy stops working? Strategy deterioration

If you know that all trading strategies sooner or later stop working, you are somewhat prepared. If you do the following, we believe you are better prepared and minimizes the risk of strategies stop working:

Look for abnormalities

Abnormalities normally revert to the mean, but of course, not always. Trading is a numbers game.

Stock prices are not normally distributed, sometimes we get a black swan, but we believe mean reversion is the lowest hanging fruit in trading. Jim Simons also agrees that mean reversion is low hanging fruit.

Correct position sizing

Setting together a portfolio of trading strategies is not easy. The thing that complicates the most is the position sizing.

For example, if you trade 5 different strategies in stock indices, do you just trade one signal at a time (not taking a signal when you already have a position), or do you still trade the signal to increase your overall exposure?

Are you tempted to increase size after a period with good results? There are many temptations to adjust the position size along the way, and often it will be the wrong thing to do.

Wrong position sizing makes you believe a trading strategy has stopped working, but in reality, many times it all boils down to the correct size of your positions.

Our best advice on position size is to trade smaller than you like:

Prepare for inevitable drawdowns by trading small

Always trade smaller than you like. If you have a good strategy or a good period, it’s very tempting to increase size in the belief that you’ll make more money. Many want to get rich in a hurry! We believe it’s better to get rich slowly by being patient and let your capital compound.

But it’s not that easy. If you get in over your head, you make inevitable mistakes, especially behavioral mistakes. Many increase size after a good period, only to lose more when the inevitable drawdown happens. During the drawdown, you reduce size….. This is a vicious cycle you want to avoid.

The best medicine for avoiding behavioral mistakes is to always trade a little smaller than you would like. If you want to get rich in a hurry, you increase the risk for a substantial setback sooner or later when strategies stop working.

Make sure you use the Holy Grail of trading – diversify

The Holy Grail of trading is having many different trading strategies that are uncorrelated to each other. That is, of course, difficult, but it should be your goal.

When you can trade unlimited strategies, only your imagination and idea generation stop you from trading plenty of strategies. It would be best if you diversified on markets, time frames, and types of trading strategies.

The point with diversification is to have strategies offset each other but still make a positive return.

Thus, when your strategy stops working, you are prepared. It’s not likely that all your strategies fail you at the same time if you are properly diversified.

Why trading strategies stop working and how to avoid it

The truth is, perhaps sadly, that the future is unknown. On the other hand, this is what makes life worth living. If all were plain sailing, it would be rather dull and boring (?). You can’t eliminate the risk that your trading strategies stop working, but you can prepare for it and minimize the risk.

What do you do to prepare for the time when your trading strategies stop working? Do you panic and turn off the strategy? Or do you just keep on plugging as if nothing happened?

The main problem in trading is that there is no way for sure you can tell if a strategy is finished or just in the middle of a normal and expected drawdown.

However, if you have a clear idea of why the strategy is working in the first place, or at least why it should work, you can better tell if you should continue or stop trading the strategy.

Moreover, you avoid or minimize trading strategies stop working by making proper backtests with many months of incubation testing in a demo account, you diversify into strategies by trading different assets and time frames, and you look for trading edges where you can have a sustainable edge.

The markets are non-stationary and adaptive, and thus most trading strategies stop working (sooner or later).

12 Reasons Why Trading Strategies Stop Working

Why trading strategies stop working will be the last words of this article. Trading strategies perform poorly in live trading mainly because of behavioral mistakes, curve fitting, survivorship bias, and improper trading size changes. It’s hard to replicate an unbiased backtest to live trading.

If you have spent considerable time developing a strategy, it’s frustrating if it performs poorly in live trading. What is happening? Why does it perform so poorly when it worked so well in backtests?

As a rule of thumb, you should always expect your strategies to perform worse than on paper. All backtesting, no matter how cautious you are, involves an element of curve fitting.

Why do trading strategies stop working?

It happens to every trader sooner or later: the strategies stop working or they experience a deep drawdown.

What do you do? Continue trading and hope for the best? Should you change strategy or give up?

Below we give some examples of the most obvious reasons why trading strategies don’t work in live trading and why they stop working (eventually):

Backtests compress time and thus you ignore drawdowns while backtesting

You can test a strategy over many decades in just one second, thus compressing time. In live trading, you spend years doing the daily grind of buying and selling, while a backtest is done in seconds or minutes.

You lose a lot of information when just crunching numbers. Moreover, what looks easy on paper, is not as easy in live trading. You can ignore drawdowns in a backtest, but not when you are risking real money.

Strategies do poorly in live trading because you do behavioral mistakes

A trading backtest never replicates live trading, even though we would argue that backtesting works pretty well. The problem is that we constantly fool ourselves by our cognitive errors and behavioral mistakes. If your strategy has shown a 20% drawdown, how do you deal with it in live trading? In a backtest, you know the strategy performed well after the drawdown. But in actual trading, where the future is uncertain, you don’t know that. Do you keep on trading, do you start tweaking or adding variables, or do you stop trading?

Our biases make it very difficult to do what the strategy tells us to do. Markets have an uncanny habit for shaking out the faint at heart – at the exact wrong time.

How do you deal with behavioral mistakes?

Victor Niederhoffer says that a bad system is better than no system at all. Stick to your systems until you either abandon them or put them back to paper trading.

Trading strategies stop working because you quit in the middle of a drawdown

The biggest drawdowns are yet to come. One of the reasons you chose a particular trading strategy is most likely because it has small drawdowns. This is kind of curve-fitting. Thus, you can expect any strategy to have a bigger drawdown than in your backtest.

Trading strategies stop working because you curve fit

What is curve fitting?

Curve fitting is when you use variables and parameters that fit the past but is unlikely to predict future prices. The future is never like the past. Despite this, we change variables and parameters until we get the results we want.

To elaborate, when we curve fit, we don´t fit our models to market behavior. We fit them to market data. That is a huge difference since market data consists of market behavior and random market noise. For that model to be profitable in the future, historical data’s random patterns must repeat themselves. However, the one primary trait of random patterns is that they do not hold any predictive value, since they are random.

Too many variables make your trading strategies stop working

The more you put into your strategy, the more likely you are to curve-fit your strategy. The simpler you make it, the better. A system might be so complex that it has no predictive value. A slight market change might turn the strategy into a loser. Moreover, be on the lookout for trades that might explain a significant part of the profitability. Such trades could be due to chance and noise and are unlikely to repeat.

The world changes and thus, your trading strategies stop working

Such an obvious fact is easy to forget. No strategy lasts forever.

The markets are mostly random

Because markets are mostly random, many of your strategies and edges are the result of noise. It’s genuinely not an edge, but just something that happened to be profitable.

Correlation is not the same as causation

Because markets are predominantly random and evolving, most correlations in trading are spurious. Most relationships are indirect, not direct. Whatever you do and conclude, the result might come from chance and is not proof of causation. Any strategy that seems statistically significant might be so due to noise or hidden factors.

There are many false positives in the markets.

Your trading strategies don’t work in live trading because you ignore survivorship bias

Survivorship bias is more prevalent and important than you think. For example, in March 2021, Seeking Alpha published a strategy that outperforms the S&P 500 by holding 40 stocks based on holdings of the best hedge funds (the article is behind a paywall).

How did the author conclude this?

He started in 2021 by picking 40 large hedge funds that outperformed the S&P 500 from 2008 until 2021. He then used the quarterly holdings of these funds going back to 2008.

Needless to say, the result is fantastic, obviously because he has picked the winners during this period. This is, of course, unlikely to be repeated. The problem is that if you used the same criteria back in 2010 to pick the 2010 stocks, the strategy would have chosen other hedge funds and holdings. Among the 23 comments about the results, just one mentioned the flaw of survivorship bias.

Almost all traders neglect survivorship bias.

Trading costs make your trading strategies unprofitable

Backtests require realistic entry and knowing when to exit a trade. However, these are often based on “after the fact”. Thus, a strategy that enters on the close needs to buy seconds before the close (or in after-hours). This, of course, might change the results significantly. Here’s how you can trade at the close.

Trading strategies perform poorly in live trading because you read news

The world is bombarding you with news from all angles. It’s challenging to ignore the news. An abundance of information and free commissions make a recipe for poor trading results. We suggest you keep both news channels and social media at a distance.

Improper size and money management make trading strategies stop working

Make a rational plan before you start on how to allocate your capital – you have to find the optimal capital allocation. It’s how you deal with losses that are paramount for your survival as a trader. How do your strategies perform together as a portfolio? How much capital should be allocated to each trading style?

The pendulum between pessimism and optimism makes you change the size. After a good run, you increase the size, and after a bad run, you decrease the size – only to find out the market turned around. Then you return to your original size. It doesn’t matter how good your strategy is if you can’t execute it properly.

The best advice we can give is always to trade smaller than you like.

All in all – there is no perfect strategy

Many are looking for the perfect strategy with minimal drawdowns. It doesn’t exist. The price you pay for making money in the markets is pain from drawdown and temporary setbacks. You can’t expect to make money without risk. As we have written numerous times: It’s better to have many “imperfect” strategies and let diversification take care of the drawdowns.

How to reduce the risk of poor live trading

Below we briefly mention some methods to minimize disappointment when you go live with your strategies:

Number stability

By changing your variables’ values, you get to measure how the results change from even small modifications. For example, if one of the variables is ADX(5)>40 try changing it to ADX(5)>45 and so on. Does it improve because of just a few winners?

Out of sample

Out-of-sample testing involves testing your strategy on data not included in the backtest. This can be done by splitting your data in two: one part for developing your strategy, for example, from the year 2000 until 2017, and then testing out of sample from 2018 until today.

Incubation period

An even better method than out of sample is to use an incubation period.

How do you do an incubation period?

You open a demo account with live or delayed quotes and run your strategies as if it was live. This is the best out-of-sample test you can get. You get to see how it performs and get to see the drawdowns live.
We suggest you do an incubation period for several months, preferably at least six months.

Monte Carlo simulation

Monte Carlo simulations are used to model different outcomes of the variables and the parameters in your strategy. It makes random sequences to evaluate your trading system’s robustness to find how the element of risk and randomness might influence the forecasting abilities.

It works by reshuffling the order of the trades in a backtest and can expose weaknesses that otherwise had would be hidden in the backtest. The simulation then gives you a list of potential outcomes – CAGR, drawdowns, risk of ruin, etc with probabilities.

The best medicine for avoiding trading strategies that stop working: Trade smaller than you like

Most traders are too optimistic about how much pain they tolerate. Everything looks easy in a backtest, but when real money is at stake, we tend to make many behavioral mistakes. Greed makes you count the chips before they are won and makes you trade sizes that are too big for your bankroll.

But success is about building up small and frequent profits over time. Prepare for a daily grind. To manage that, you need to trade a smaller size than you would like. This is the only way to detach you from money.

We recommend keeping a journal where you record all your trades (and just as important the trades you skip). Trading is a continuous feedback loop! We have provided a trading journal example for your convenience.

Conclusion: why trading strategies don’t work in live trading

Trading strategies don’t work in live trading, or they stop working completely, for a number of reasons: you curve-fit data, ignore data, or you might do behavioral mistakes and not follow your system at all!

To minimize this risk always do an incubation period of your strategies and trade a smaller size than you’d like.


Why do trading strategies stop working?

Trading strategies stop working or become less effective due to various factors such as curve fitting, structural and cyclical market changes, survivorship bias, behavioral mistakes, commissions, and slippage. Markets are dynamic, and strategies need to adapt to evolving conditions.

When should I stop trading a strategy?

You should consider stopping a trading strategy if it consistently underperforms, deviates from the expected results, or if there are structural changes in the market affecting its effectiveness. Regularly review and reassess your strategies to ensure they align with current market conditions.

How can I minimize the risk of trading strategies stopping to work?

You minimize the risk by conducting thorough backtesting with a sufficient historical dataset, including an out-of-sample test. Implement an incubation period by paper trading the strategy for months in a demo account before going live. Diversify your portfolio with uncorrelated strategies and trade smaller sizes to manage drawdowns effectively.

What is curve fitting in the context of trading strategies, and how does it impact their performance?

Curve fitting is when when variables and parameters are tailored to fit past data, potentially leading to poor predictions in future market conditions. It is a common reason why trading strategies may not work as expected in live trading.

Why is it essential to trade smaller sizes than desired when implementing trading strategies?

It’s essential to trade smaller sizes than desired when implementing trading strategies in live trading due to factors such as behavioral mistakes, curve fitting, survivorship bias, and discrepancies in time. Trading smaller sizes is crucial to managing the psychological aspects of trading, such as greed and optimism. It allows traders to build profits gradually and detach themselves emotionally from the monetary aspect of trades.

How can Monte Carlo simulation be utilized to enhance the robustness of trading strategies?

Monte Carlo simulation can be utilized to enhance robustness of trading strategies by reshuffling the order of trades in a backtest to expose weaknesses in a trading system. It provides a probabilistic analysis of potential outcomes, including CAGR, drawdowns, and risk of ruin, contributing to a more robust strategy evaluation.

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