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Determining the number of change-points in high-dimensional factor models by cross-validation with matrix completion

Author

Listed:
  • Zhou, Ruichao
  • Wu, Jianhong

Abstract

This paper focuses on the determination of the number of change-points in high-dimensional factor models via cross-validation with matrix completion. An imputed method is proposed to predict the validation data set which is seen as the “missing” data of the training set. The number of change-points can be determined by minimizing the prediction error on the validation set. The consistency of the estimator is established under some mild conditions. Monte Carlo simulation results show desired performance of the proposed method compared to the existing competitors.

Suggested Citation

  • Zhou, Ruichao & Wu, Jianhong, 2023. "Determining the number of change-points in high-dimensional factor models by cross-validation with matrix completion," Economics Letters, Elsevier, vol. 232(C).
    • Handle: RePEc:eee:ecolet:v:232:y:2023:i:c:s0165176523003750
    DOI: 10.1016/j.econlet.2023.111350
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    More about this item

    Keywords

    Cross-validation; High-dimensional factor models; Matrix completion; Structural changes; The number of change-points;
    All these keywords.

    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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