What are some best practices and tips for backtesting and forward testing mean reversion systems?

1 Define your hypothesis

Before you start backtesting and forward testing your mean reversion system, you need to have a clear and testable hypothesis about the market behavior and the signals you want to use. For example, you might hypothesize that a certain asset is mean reverting when its price deviates from its moving average by more than two standard deviations, and that this is a good entry point for a long or short position. You also need to define your exit criteria, risk management rules, and performance metrics.

2 Choose your data and tools

The quality and quantity of your data and tools are crucial for the reliability and validity of your backtesting and forward testing results. You need to choose a data source that provides accurate, consistent, and complete historical and live data for your asset class and time frame. You also need to choose a backtesting and forward testing platform that allows you to code, run, and evaluate your system with flexibility and efficiency. Some popular platforms include Python, R, MATLAB, AmiBroker, and MetaTrader.

3 Avoid overfitting and curve fitting

One of the biggest pitfalls of backtesting and forward testing mean reversion systems is overfitting and curve fitting, which means that your system is too tailored to the past data and does not perform well in new or unseen market conditions. To avoid this, you need to use robust and simple methods, such as linear regression, cointegration, or Bollinger bands, rather than complex and arbitrary ones. You also need to use a reasonable number of parameters, avoid optimizing them too much, and test your system on different data sets, such as in-sample, out-of-sample, and walk-forward.

4 Consider transaction costs and slippage

Another common mistake of backtesting and forward testing mean reversion systems is ignoring or underestimating the transaction costs and slippage that can erode your profits and increase your losses. Transaction costs include commissions, fees, spreads, and taxes that you pay when you execute a trade. Slippage is the difference between the expected price and the actual price of a trade, due to market volatility, liquidity, or delays. You need to account for these factors in your backtesting and forward testing, by using realistic assumptions and incorporating them into your system.

5 Evaluate your results and refine your system

The final step of backtesting and forward testing mean reversion systems is to evaluate your results and refine your system based on the feedback and insights you gain. You need to use various performance metrics, such as returns, drawdowns, Sharpe ratio, win rate, profit factor, and maximum adverse excursion, to measure the profitability, risk, and consistency of your system. You also need to use various diagnostic tools, such as charts, tables, statistics, and reports, to analyze the behavior, strengths, and weaknesses of your system. Based on your evaluation, you can modify, improve, or reject your system.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?