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A Note on the Finite Sample Bias in Time Series Cross-Validation

Amaze Lusompa

Abstract

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 (VAR) 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.

A Note on the Finite Sample Bias in Time Series Cross-Validation

Abstract

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 (VAR) 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.

Paper Structure

This paper contains 4 sections, 16 equations.

Table of Contents

  1. 1 Introduction
  2. 2 How Cross-Validation Works
  3. 3 Bias in Time Series Cross-Validation
  4. 4 Conclusion

Theorems & Definitions (1)

  • Remark 1