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.

中文翻译：

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高维近似因子模型中的正则协方差矩阵估计

当因子数量与样本大小相比较大时，我们提出了一种新颖的基于因子的正则化协方差矩阵估计器，并得出了估计器的收敛率。经验结果表明我们提出的估计器在有限样本中表现良好。