Determining Optimal Trading Rules Without Backtesting

39 Pages Posted: 12 Sep 2015

See all articles by Peter Carr

Peter Carr

New York University Finance and Risk Engineering

Marcos Lopez de Prado

Cornell University - Operations Research & Industrial Engineering; AQR Capital Management, LLC

Date Written: August 2014

Abstract

Calibrating a trading rule using a historical simulation (also called backtest) contributes to backtest overfitting, which in turn leads to underperformance. In this paper 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, optimization, backtesting, overfitting, simulation

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

Suggested Citation

Carr, Peter P. and López de Prado, Marcos, Determining Optimal Trading Rules Without Backtesting (August 2014). Available at SSRN: https://ssrn.com/abstract=2658641 or http://dx.doi.org/10.2139/ssrn.2658641

Peter P. Carr (Contact Author)

New York University Finance and Risk Engineering ( email )

6 MetroTech Center
Brooklyn, NY 11201
United States
9176217733 (Phone)

HOME PAGE: http://engineering.nyu.edu/people/peter-paul-carr

Marcos López de Prado

Cornell University - Operations Research & Industrial Engineering ( email )

237 Rhodes Hall
Ithaca, NY 14853
United States

HOME PAGE: http://www.orie.cornell.edu

AQR Capital Management, LLC

One Greenwich Plaza
Greenwich, CT 06830
United States

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

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