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Determining the number of breaks in high-dimensional factor models with interval-valued data

Author

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  • Guo, Yan
  • Chen, Jing
  • Wu, Jianhong

Abstract

The paper considers a high-dimensional interval-valued data factor model with potential structural changes. We verify that the number of factors is usually overestimated in the case with structural changes and then propose an estimator for the number of breaks by leveraging the finding. We establish the consistency of this estimator under certain conditions. Monte Carlo simulation results show that the proposed estimation procedure exhibits desired finite sample performance. In addition, an empirical application to S&P 100 stock return data further demonstrates the practical usefulness of the proposed method.

Suggested Citation

  • Guo, Yan & Chen, Jing & Wu, Jianhong, 2026. "Determining the number of breaks in high-dimensional factor models with interval-valued data," Economics Letters, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:ecolet:v:262:y:2026:i:c:s0165176526000637
    DOI: 10.1016/j.econlet.2026.112869
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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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