The Deflated Sharpe Ratio: Correcting for Selection Bias, Backtest Overfitting and Non-normality

With the advent in recent years of large financial data sets, machine learning and highperformance computing, analysts can backtest millions (if not billions) of alternative investment strategies. Backtest optimizers search for combinations of parameters that maximize the simulated historical performance of a strategy, leading to backtest overfitting. The problem of performance inflation extends beyond backtesting. More generally, researchers and investment managers tend to report only positive outcomes, a phenomenon known as selection bias. Not controlling for the number of trials involved in a particular discovery leads to over-optimistic performance expectations. The Deflated Sharpe Ratio (DSR) corrects for two leading sources of performance inflation: Selection bias under multiple testing and non-Normally distributed returns. In doing so, DSR helps separate legitimate empirical findings from statistical flukes.