Regularized covariance matrix estimation in high dimensional approximate factor models
STATISTICS & PROBABILITY LETTERS(2024)
摘要
We propose a novel factor-based regularized covariance matrix estimator when the number of factors is large compared to the sample size and derive the convergence rates of our estimator. Empirical results demonstrate our proposed estimator performs well in finite samples.
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关键词
High dimensionality,Factor model,Lasso,Adaptive thresholding,Entropy loss
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