2025/01/07 by Antoine Jacquier, Jacquier, Antoine, Johannes Muhle‐Karbe +3
Mathematics · #Advanced Statistical Methods and Models #FOS: Economics and business #Mathematical Finance (q-fin.MF) #Portfolio Management (q-fin.PM) #Statistical Methods and Inference
paper · pdf · doi:10.48550/arxiv.2501.03938
openalex publication_date 2025/01/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We study how much the in-sample performance of trading strategies based on linear predictive models is reduced out-of-sample due to overfitting. More specifically, we compute the in- and out-of-sample means and variances of the corresponding PnLs and use these to derive a closed-form approximation for the corresponding Sharpe ratios. We find that the out-of-sample "replication ratio" diminishes for complex strategies with many assets based on many weak rather than a few strong trading signals, and increases when more training data is used. The substantial quantitative importance of these effects is illustrated with a simulation case study for commodity futures following the methodology of Gârleanu and Pedersen, and an empirical case study using the dataset compiled by Goyal, Welch and Zafirov.