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Evaluating Trading Strategies

16 Pages Posted: 3 Aug 2014 Last revised: 26 Aug 2014

Campbell R. Harvey

Duke University - Fuqua School of Business; National Bureau of Economic Research (NBER); Duke Innovation & Entrepreneurship Initiative

Yan Liu

Texas A&M University, Department of Finance

Date Written: August 25, 2014

Abstract

We provide some new tools to evaluate trading strategies. When it is known that many strategies and combinations of strategies have been tried, we need to adjust our evaluation method for these multiple tests. Sharpe Ratios and other statistics will be overstated. Our methods are simple to implement and allow for the real-time evaluation of candidate trading strategies.

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Keywords: Sharpe ratio, Multiple tests, Holm, BHY, Bonferroni, Strategy selection, Backtest, Haircut, Haircut Sharpe Ratio, Data Mining, Machine Learning, Higgs Boson, Trading Strategies, Out-of-Sample tests, In-Sample tests, FDR, FWER, Capital IQ, PBO

JEL Classification: G12, G14, G30, G00, C12, C20, B41

Suggested Citation

Harvey, Campbell R. and Liu, Yan, Evaluating Trading Strategies (August 25, 2014). Available at SSRN: https://ssrn.com/abstract=2474755 or http://dx.doi.org/10.2139/ssrn.2474755

Campbell Harvey (Contact Author)

Duke University - Fuqua School of Business ( email )

Box 90120
Durham, NC 27708-0120
United States
919-660-7768 (Phone)
919-660-8030 (Fax)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Duke Innovation & Entrepreneurship Initiative ( email )

215 Morris St., Suite 300
Durham, NC 27701
United States

Yan Liu

Texas A&M University, Department of Finance ( email )

Wehner 401Q, MS 4353
College Station, TX 77843-4218
United States

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