I’ve already explained the best stop loss strategy for traders and investors. This post is about what traders and investors should do when they consistently lose money on their trades and investments.
The best way to deal with a string of consecutive losses depends on your strategy: are you a discretionary trader or a systematic (quantitative) trader?
Consecutive losses can mess with your trading psychology. It can lead you down the dangerous path of a gambler’s mentality. Here’s a common pattern that happens to many traders who are stuck in a losing streak.
- Lose money.
- Lose confidence in their strategy.
- Increase bet sizes. Trade more often. Copy other traders. Try to make back their losses.
- Try different strategies.
- Lose more money. It becomes a vicious cycle. Losses beget more losses.
Losing money on consecutive trades is dangerous from more than just a monetary perspective. Discretionary traders need to prevent the above negative cycle from happening. They need to break the negative self-reinforcing cycle.
- Do not lose confidence in your strategy just because you experienced a string of losses. Every strategy will go through a period of outperformance and a period of underperformance. Nothing will outperform forever. A period of consecutive losses does not mean that your strategy will no longer work in the future.
- Decrease your bet sizes when you lose money. Trade less often and only take trades with a higher probability of success. Regaining your confidence is more important than making back your losses after a string of unprofitable trades. If you can afford it, I even suggest you take a mini-vacation and take your mind off of trading for a while. Clear your head so that you can come back to trading with a fresh mind.
- Don’t copy other traders who are making money just because you are losing money. For all you know, you can be copying other traders just as their strategies go into a period of underperformance.
- Re-examine your strategy. Did you lose money because you didn’t adhere to the strategy? Is the strategy fundamentally flawed? How can you improve the strategy?
Starting from a completely new and different trading strategy is rarely a good idea. By doing so you will throw away most of the trading skills and knowledge that you learned in the past.
Systematic traders don’t face the threat of a dangerous psychological cycle whereby losses beget more losses. The quantitative strategy is emotionless. Losses should not impact the psychology of quantitative traders.
Hence, systematic traders do not need to shrink their position sizes or trade less just because they experienced a string of consecutive losses. Systematic traders should keep on following their models to the letter.
HOWEVER, a string of consecutive losses should prompt quantitative traders to re-evaluate and improve their models. The biggest improvements in my models came after a period of losses. We learn more from our failures than from our successes.
Ask yourself the following questions to improve your model(s).
*These tips are under the assumption that all models have been adequately backtested. Adequately backtesting your strategy is that first thing you should do.
- Based on your backtest, is the recent string of losses normal? E.g. let’s assume that the strategy lost money on 10 consecutive trades. Historically, the strategy has lost money on 5 consecutive trades at most. Hence, the recent string of losses is abnormal. It’s a sign that something is wrong with the model, or that the market is changing (i.e. the model won’t work as well in the future).
- Is the model missing a key component? Is there a big new indicator that the model could have used to prevent losses such as the recent ones?
- Do you need to adjust your risk management strategy? No model is perfect, so risk management is sometimes the key to improving trading/investment performance. E.g. If you were going all-in before, should you consider a scale-in strategy in the future?
*Do not try to overfit the data just to prevent recent losses from occuring again the future. Overfitting the data is always dangerous. Leave some leeway in your indicators.