Estimating High Dimensional Covariance Matrices and its Applications

By Jushan Bai, Shuzhong Shi. 2011

141 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/9ed3d907de93a1f54ef3539007a026a498cd2b20

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Citations in the corpus

Large Covariance Estimation by Thresholding Principal Orthogonal Complements (2011, unknown): “One of the key assumptions is that the covariance matrix is sparse, namely, many entries are zero or nearly so (Bickel and Levina, 2008, Rothman et al, 2009, Lam and Fan 2009, Cai and Zhou, 2010, Cai and Liu, 2011). In many applications, however, the sparsity assumption directly on Σ is not appropri”
Factor Models for Portfolio Selection in Large Dimensions: The Good, the Better and the Ugly (2019, background): “But many other factors have been proposed in the literature; for example, see Bai and Shi (2011, Section 4) and Feng, Giglio, and Xiu (2017). Latent factors are unknown and must be estimated from the data along with the factor loadings.”
Optimal Shrinkage-Based Portfolio Selection in High Dimensions (2016, background): “The sample covariance matrix is very unstable and tends to under- or overestimate the true parameters for c smaller but close to 1 (see, Bai and Shi (2011)). For c > 1 the inverse sample covariance does not exist and the portfolio cannot be constructed in the traditional way. Taking the above mentio”
Selective review of offline change point detection methods (2020, background): “Nevertheless, several authors have 942 observed that for high dimensional signals, certain statistical quantities are no 943 longer so easily estimated: for instance, the inverse of the sample covariance 944 matrix is not necessarily an unbiased estimator of the precision matrix, when 945 d is large”
Incorporating Global Industrial Classification Standard Into Portfolio Allocation: A Simple Factor-Based Large Covariance Matrix Estimator With High-Frequency Data (2016, unknown): “Bai and Shi (2011) provided a detailed review of the literature.”