Dynamic factor multivariate GARCH model

被引:14
|
作者
Santos, Andre A. P. [1 ]
Moura, Guilherme V. [1 ]
机构
[1] Univ Fed Santa Catarina, Dept Econ, BR-88049970 Florianopolis, SC, Brazil
关键词
Dynamic conditional correlation (DCC); Forecasting; Kalman filter; Learning CAPM; Performance evaluation; Sharpe ratio; AUTOREGRESSIVE CONDITIONAL HETEROSKEDASTICITY; MAXIMUM-LIKELIHOOD-ESTIMATION; PORTFOLIO OPTIMIZATION; PERFORMANCE; VOLATILITY; RETURNS; COVARIANCES; ALLOCATION; STOCKS; ARCH;
D O I
10.1016/j.csda.2012.09.010
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
A novel multivariate factor GARCH specification is used to obtain conditional covariance matrices of minimum variance portfolios containing a very large number of assets. The approach allows for time varying factor loads, and achieves great flexibility by allowing alternative specifications for the covariance among factors and for the variance of the asset-specific part of return. Minimum variance portfolios based on the proposed conditional covariance matrix specification are shown to deliver less risky portfolios in comparison to benchmark models, including existing factor approaches. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:606 / 617
页数:12
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