Abstract

http://ssrn.com/abstract=2345489
 
 

References (38)



 
 

Citations (1)



 


 



Backtesting


Campbell R. Harvey


Duke University - Fuqua School of Business; National Bureau of Economic Research (NBER)

Yan Liu


Texas A&M University, Department of Finance

October 4, 2014


Abstract:     
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".

Note: Related papers: Multiple Testing in Economics and …and the Cross-Section of Expected Returns

Number of Pages in PDF File: 28

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

working papers series





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Date posted: October 27, 2013 ; Last revised: October 7, 2014

Suggested Citation

Harvey, Campbell R. and Liu, Yan, Backtesting (October 4, 2014). Available at SSRN: http://ssrn.com/abstract=2345489 or http://dx.doi.org/10.2139/ssrn.2345489

Contact Information

Campbell R. 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
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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