32 Pages Posted: 27 Oct 2013 Last revised: 30 Jul 2015
Date Written: July 28, 2015
When evaluating a trading strategy, it is routine to discount the Sharpe ratio from a historical backtest. The reason is simple: there is inevitable data mining by both the researcher and by other researchers in the past. Our paper provides a statistical framework that systematically accounts for these multiple tests. We propose a method to determine the appropriate haircut for any given reported Sharpe ratio. We also provide a profit hurdle that any strategy needs to achieve in order to be deemed "significant".
Keywords: Sharpe ratio, Multiple tests, Backtest, Haircut, Trading Strategies, Out-of-Sample tests, In-Sample tests
JEL Classification: G12, G14, G30, G00, C12, C20, B41
Suggested Citation: Suggested Citation
By Andrew Ang
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