Optimal Trading Rules Without Backtesting

29 Pages Posted: 29 Sep 2014 Last revised: 5 Jul 2015

Marcos Lopez de Prado

Guggenheim Partners, LLC; Lawrence Berkeley National Laboratory; Harvard University - RCC

Date Written: September 28, 2014

Abstract

Calibrating a trading rule using a historical simulation (also called backtest) contributes to backtest overfitting, which in turn leads to underperformance. We propose a procedure for determining the optimal trading rule (OTR) without running alternative model configurations through a backtest engine. We present empirical evidence of the existence of such optimal solutions for the case of prices following a discrete Ornstein-Uhlenbeck process, and show how they can be computed numerically. Although we do not derive a closed-form solution for the calculation of OTRs, we conjecture its existence on the basis of the empirical evidence presented.

Keywords: Trading rule, backtest overfitting, profit-taking, stop-loss

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

Suggested Citation

Lopez de Prado, Marcos, Optimal Trading Rules Without Backtesting (September 28, 2014). Available at SSRN: https://ssrn.com/abstract=2502613 or http://dx.doi.org/10.2139/ssrn.2502613

Marcos Lopez de Prado (Contact Author)

Guggenheim Partners, LLC ( email )

330 Madison Avenue
New York, NY 10017
United States

HOME PAGE: http://www.QuantResearch.org

Lawrence Berkeley National Laboratory ( email )

1 Cyclotron Road
Berkeley, CA 94720
United States

HOME PAGE: http://www.lbl.gov

Harvard University - RCC ( email )

26 Trowbridge Street
Cambridge, MA 02138
United States

HOME PAGE: http://www.rcc.harvard.edu

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