A reproducible approach to equity backtesting

• Main Author: Arbi, Riaz
• Other Authors: Gebbie, Timothy
• Format: Dissertation
• Language: English
• Published: Faculty of Science 2020
• Subjects: Equity Backtesting; Reproducible Research; Event-based Backtesting; R; RStudio
• Online Access: http://hdl.handle.net/11427/31158

Research findings relating to anomalous equity returns should ideally be repeatable by others. Usually, only a small subset of the decisions made in a particular backtest workflow are released, which limits reproducability. Data collection and cleaning, parameter setting, algorithm development and report generation are often done with manual point-and-click tools which do not log user actions. This problem is compounded by the fact that the trial-and-error approach of researchers increases the probability of backtest overfitting. Borrowing practices from the reproducible research community, we introduce a set of scripts that completely automate a portfolio-based, event-driven backtest. Based on free, open source tools, these scripts can completely capture the decisions made by a researcher, resulting in a distributable code package that allows easy reproduction of results.