Probability of Backtest Overfitting (PBO): It computes the probability that the best in-sample strategy will underperform out-of-sample a randomly chosen alternative.
Deflated Sharpe Ratio (DSR): It deflates the predicted performance of a strategy by controlling for the number of trials involved in a discovery. In the example above, the “buy on Tuesday and sell on Friday” strategy would be discarded because of the large number of combinations tried.
Optimal Trading Rule (OTR): This empirical procedure determines the optimal trading rule on a large amount of synthetic data generated by the distribution that characterizes the observed data.
CPCV: It derives the full distribution of the strategy’s performance (rather than a single path) under thousands of alternative scenarios.
Goals
As a developer, I want to prevent backtest overfitting, so that I can find more True Positives and eliminate False Positives.
Consider
Inspiration
Backtest overfitting is an industry-wide problem (Financial Times, 2014).
Source: The 7 Reasons Most Machine Learning Funds Fail (Presentation Slides), 2018
True Positive Technologies, lead by Marcos Lopez de Prado, developed multiple solutions to the backtest overfitting problem, including: