A note on statistical analysis of factor models of high dimension

Linear factor models are familiar tools used in many fields. Several pioneering literatures established foundational theoretical results of the quasi-maximum likelihood estimator for high-dimensional linear factor models. Their results are based on a critical assumption: The error variance estimators are uniformly bounded in probability. Instead of making such an assumption, we provide a rigorous proof of this result under some mild conditions.

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Work Title A note on statistical analysis of factor models of high dimension
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Open Access
Creators
  1. Zhigen Gao
  2. Jianhua Guo
  3. Yanyuan Ma
License In Copyright (Rights Reserved)
Work Type Article
Publisher
  1. Science China Mathematics
Publication Date August 1, 2021
Publisher Identifier (DOI)
  1. https://doi.org/10.1007/s11425-019-1698-1
Deposited November 15, 2021

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