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Estimation of high dimensional factor model with multiple threshold-type regime shifts

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  • Wu, Jianhong

Abstract

This paper considers the estimation of high dimensional factor model with multiple threshold-type regime shifts in factor loadings. Firstly, the number of thresholds is determined by comparing the number of factors in the adjacent subintervals. Secondly, the thresholds are estimated one by one by concentrated least squares, and then the factors and loadings are obtained by the principal component method in the augmented subgroups with a single threshold. Under some regularity conditions, the consistency of these estimators can be obtained. Monte Carlo simulation results demonstrate that the proposed method has desirable performance in finite samples. A real data analysis is carried out for illustration.

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  • Wu, Jianhong, 2021. "Estimation of high dimensional factor model with multiple threshold-type regime shifts," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    • Handle: RePEc:eee:csdana:v:157:y:2021:i:c:s0167947320302449
    DOI: 10.1016/j.csda.2020.107153
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    References listed on IDEAS

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    Cited by:

    1. Xialu Liu & Elynn Y. Chen, 2022. "Identification and estimation of threshold matrix‐variate factor models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1383-1417, September.
    2. Ma, Chenchen & Tu, Yundong, 2023. "Shrinkage estimation of multiple threshold factor models," Journal of Econometrics, Elsevier, vol. 235(2), pages 1876-1892.

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