Block-diagonal idiosyncratic covariance estimation in high-dimensional factor models for financial time series
高维金融时间序列因子模型中的块对角特异协方差估计
Estimation of high-dimensional covariance matrices in latent factor models is an important topic in many fields and especially in finance. Since the number of financial assets grows while the estimation window length remains of limited size, the often used sample estimator yields noisy estimates which are not even positive definite. Under the assumption of latent factor models, the covariance matrix is decomposed into a common low-rank component and a full-rank idiosyncratic…