The Three Types of Backtests

Abstract

Backtesting stands as a cornerstone technique in the development of systematic investment strategies, but its successful use is often compromised by methodological pitfalls and common biases. These shortcomings can lead to false discoveries and strategies that fail to perform out-of-sample. This article provides practitioners with guidance on adopting more reliable backtesting techniques by reviewing the three principal types of backtests (walk-forward testing, the resampling method, and Monte Carlo simulations), detailing their unique challenges and benefits. Additionally, it discusses methods to enhance the quality of simulations and presents approaches to Sharpe ratio calculations which mitigate the negative consequences of running multiple trials. Thus, it aims to equip practitioners with the necessary tools to generate more accurate and dependable investment strategies.

Keywords: Backtesting, simulation, selection bias under multiple testing, evaluation, G1, G2, G11, G15, G17, G24, C58, best practices

JEL Classification: G0, G1, G2, G11, G15, G17, G24, C58