Backtesting

Forthcoming in “Numerical Methods and Optimization in Finance (2nd ed),” by M. Gilli, D. Maringer and E. Schumann

89 Pages Posted: 17 May 2019 Last revised: 25 Jul 2019

Date Written: December 31, 2018

Abstract

We discuss the backtesting of investment and trading strategies. We start with the challenges and pitfalls: overfitting, data preparation, and the effects of randomness. Then, we introduce and describe R software for backtesting. We demonstrate how to use the software for univariate and multivariate strategies (i.e. portfolio strategies) for two equity data sets. Specifically, we discuss the implementation and testing of momentum and portfolio optimization models. Throughout, we stress the analysis of sensitivity and robustness checks. Since such analyses require to run many backtests, we also discuss how backtests can be run in parallel.

Keywords: backtesting, portfolio optimization, trading, R, momentum, NMOF

Suggested Citation

Schumann, Enrico, Backtesting (December 31, 2018). Forthcoming in “Numerical Methods and Optimization in Finance (2nd ed),” by M. Gilli, D. Maringer and E. Schumann. Available at SSRN: https://ssrn.com/abstract=3374195 or http://dx.doi.org/10.2139/ssrn.3374195

Enrico Schumann (Contact Author)

Independent ( email )

No Address Available

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