Implementation Risk in Portfolio Backtesting: A Previously Unquantified Source of Error

Battle Count: 64

Highly relevant to quantitative trading. The paper directly addresses a fundamental question in quant research: whether backtest results are robust to the choice of simulation engine. Findings show that for high-turnover/cost-intensive strategies, engine choice can produce up to 3.71% divergence in total return (equivalent to ~$37M/year per $1B AUM), which is material for strategy selection and risk budgeting. The proposed metrics (ES, IUI, DAF, CSI) provide actionable acceptance criteria for practitioners. The forensic analysis revealing 7 undocumented defects (including Backtrader's 100x commission undercharge) demonstrates real-world impact. The recommendation for multi-engine validation is directly applicable to any quant workflow. The connection to SR 11-7 model risk regulation makes it relevant for institutional compliance.

Moderate complexity. The framework itself is well-defined with clear metrics and a reference algorithm (Algorithm 1). However, practical implementation requires: (1) configuring multiple backtesting engines to match a common specification, (2) handling engine-specific quirks (e.g., Backtrader's percabs parameter, cvxportfolio's forward-return convention), (3) constructing stratified asset buckets via rerandomization, (4) running 15 strategies x 5 engines x 30 buckets x 4 cost regimes, and (5) performing multiple statistical tests with FDR correction. The released code significantly reduces implementation burden. The main challenge is ensuring faithful strategy translation across engines with different APIs and architectures.

Exceptionally high reproducibility. The authors release a fully reusable open benchmark suite including a purpose-built reference implementation, strategy definitions, data-sampling protocol, and evaluation code at GitHub (MIT license). Raw price data can be reproduced via an included download script from Yahoo Finance. Derived data will be deposited at Zenodo. The analysis plan was specified before any engine outputs were compared. All engine configurations are documented in detail (Appendix B). The reference implementation (Algorithm 1) is provided as pseudocode.