Campbell R. Harvey
Duke University - Fuqua School of Business; National Bureau of Economic Research (NBER); Duke Innovation & Entrepreneurship Initiative
Texas A&M University, Department of Finance
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".
Number of Pages in PDF File: 32
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
Date posted: October 27, 2013 ; Last revised: July 30, 2015
© 2015 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollo2 in 0.359 seconds