Forecasting large covariance matrix with high-frequency data: A factor approach for the correlation matrix

• Main Authors: DONG, Yingjie, TSE, Yiu Kuen
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Dimension reduction; Eigenanalysis; Factor model; High-frequency data; Large correlation matrix; Nonlinear shrinkage; Econometrics
• Online Access: https://ink.library.smu.edu.sg/soe_research/2473; https://ink.library.smu.edu.sg/context/soe_research/article/3472/viewcontent/Forecasting_large_covar_matrix_2020_av.pdf
• Institution: Singapore Management University

We apply the factor approach to the correlation matrix to forecast large covariance matrix of asset returns using high-frequency data, using the principal component method to model the underlying latent factors of the correlation matrix. The realized variances are separately forecasted using the Het...