RWP 25-17, November 2025; updated December 2025
It is well known that model selection via cross validation can be biased for time series models. However, many researchers have argued that this bias does not apply when using cross-validation with vector autoregressions (VARs) or with time series models whose errors follow a martingale-like structure. I show that even under these circumstances, performing cross-validation on time series data will still generate bias in general.
JEL Classifications: C52, C50, C10
Article Citation
Lusompa, Amaze. 2025. "A Note on the Finite Sample Bias in Time Series Cross-Validation." Federal Reserve Bank of Kansas City, Research Working Paper no. 25-17. Available at External Linkhttps://doi.org/10.18651/RWP2025-17
The views expressed are those of the authors and do not necessarily reflect the positions of the Federal Reserve Bank of Kansas City or the Federal Reserve System.