Telling the Good from the Bad and the Ugly: How to Evaluate Backtested Investment Strategies

19 Pages Posted: 30 Oct 2013  

Patrick Beaudan

Belvedere Advisors LLC

Date Written: October 28, 2013

Abstract

A growing share of the world’s trading activity is generated by algorithmic investment strategies. Algorithms require development, backtesting, and investors that assume the initial performance risk. Evaluating the likelihood that backtested strategies will maintain their risk return profile in the future is an endeavor that requires experience and insight. In this paper, we describe a practical, non-technical approach to evaluating backtests that should help investors weed out those strategies the least likely to be profitable once launched in the marketplace. We also try to provide insight into why for most experienced investors the details of the statistical methods used to develop backtests are not the most critical immediate considerations when evaluating a potential investment.

Keywords: back-test, historical simulation, probability of back-test over-fitting, investment strategy, optimization, Sharpe ratio, minimum back-test length, performance degradation

JEL Classification: G0, G1, G2, G15, G24, E44

Suggested Citation

Beaudan, Patrick, Telling the Good from the Bad and the Ugly: How to Evaluate Backtested Investment Strategies (October 28, 2013). Available at SSRN: https://ssrn.com/abstract=2346600 or http://dx.doi.org/10.2139/ssrn.2346600

Patrick B. Beaudan (Contact Author)

Belvedere Advisors LLC ( email )

1896 Mountain View Dr
Tiburon, CA 94920
United States
415 839-5239 (Phone)

HOME PAGE: http://www.beladv.com

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