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On the statistical analysis of high-dimensional factor models

Author

Listed:
  • Junfan Mao

    (Northeast Normal University)

  • Zhigen Gao

    (Northeast Normal University)

  • Bing-Yi Jing

    (Southern University of Science and Technology)

  • Jianhua Guo

    (Beijing Technology and Business University)

Abstract

High-dimensional factor models have received much attention with the rapid development in big data. We make several contributions to the asymptotic properties of Quasi Maximum Likelihood estimations (QMLE) as both the sample size T and the variable dimension N go to infinity. First we eliminate one of rather unnatural assumptions on the variance estimates which is commonly assumed in the literature. Secondly, we give unified results on the asymptotic properties of the QMLE, which greatly expand the scope of earlier studies. Simulations are given to illustrate these results.

Suggested Citation

  • Junfan Mao & Zhigen Gao & Bing-Yi Jing & Jianhua Guo, 2024. "On the statistical analysis of high-dimensional factor models," Statistical Papers, Springer, vol. 65(8), pages 4991-5019, October.
    • Handle: RePEc:spr:stpapr:v:65:y:2024:i:8:d:10.1007_s00362-024-01557-x
    DOI: 10.1007/s00362-024-01557-x
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    References listed on IDEAS

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