Introduction With the recent advent of large financial datasets, machine learning, and high-performance computing, analysts can backtest millions of alternative investment strategies. Backtest optimizers search for combinations of parameters to maximize a strategy's simulated historical performance, leading to backtest overfitting. The performance inflation problem goes beyond backtesting. More generally, researchers and investment managers tend to report only positive results, a phenomenon is known as selection bias. Failure to control the number of tests involved in a given finding can lead to overly optimistic performance expectations. The Deflated Sharpe Ratio (DSR) corrects for two major sources of performance inflation: selection bias under multiple tests and non-normally distributed returns . By doing so, DSR helps separate legitimate empirical results from statistical deception. Backtesting is a good example. Backtesting is a historical simulation of how a particular inv
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