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What to Look for in a Backtest

58 Pages Posted: 12 Aug 2013 Last revised: 5 Jul 2015

Marcos Lopez de Prado

Lawrence Berkeley National Laboratory; Guggenheim Partners; Harvard University

Date Written: August 11, 2013


A large number of quantitative hedge funds have historically sustained losses. In this study we argue that the backtesting methodology at the core of their strategy selection process may have played a role.

* Most firms and portfolio managers rely on backtests (or historical simulations of performance) to allocate capital to investment strategies.

* After trying only 7 strategy configurations, a researcher is expected to identify at least one 2-year long backtest with an annualized Sharpe ratio of over 1, when the expected out of sample Sharpe ratio is 0.

* If the researcher tries a large enough number of strategy configurations, a backtest can always be fit to any desired performance for a fixed sample length. Thus, there is a minimum backtest length (MinBTL) that should be required for a given number of trials.

* Standard statistical techniques designed to prevent regression over-fitting, such as hold-out, are inaccurate in the context of backtest evaluation.

* The practical totality of published backtests do not report the number of trials involved.

* Under memory effects, over-fitting leads to systematic losses, not noise.

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

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

Suggested Citation

Lopez de Prado, Marcos, What to Look for in a Backtest (August 11, 2013). Available at SSRN: or

Marcos Lopez de Prado (Contact Author)

Lawrence Berkeley National Laboratory ( email )

1 Cyclotron Road
Berkeley, CA 94720
United States


Guggenheim Partners ( email )

330 Madison Avenue
New York, NY 10017
United States


Harvard University ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States


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