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

• المؤلفون الرئيسيون: DONG, Yingjie, TSE, Yiu Kuen
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2020
• الموضوعات: Dimension reduction; Eigenanalysis; Factor model; High-frequency data; Large correlation matrix; Nonlinear shrinkage; Econometrics
• الوصول للمادة أونلاين: 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

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...