Download or read book High-Dimensional Covariance Matrix Estimation: Shrinkage Toward a Diagonal Target written by Mr. Sakai Ando and published by International Monetary Fund. This book was released on 2023-12-08 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proposes a novel shrinkage estimator for high-dimensional covariance matrices by extending the Oracle Approximating Shrinkage (OAS) of Chen et al. (2009) to target the diagonal elements of the sample covariance matrix. We derive the closed-form solution of the shrinkage parameter and show by simulation that, when the diagonal elements of the true covariance matrix exhibit substantial variation, our method reduces the Mean Squared Error, compared with the OAS that targets an average variance. The improvement is larger when the true covariance matrix is sparser. Our method also reduces the Mean Squared Error for the inverse of the covariance matrix.