Dynamic Factor Multivariate GARCH Model

Factor models are well established as promising alternatives to obtain covariance matrices of portfolios containing a very large number of assets. In this paper, we consider a novel multivariate factor GARCH specication with a flexible modeling strategy for the common factors, for the individual assets, and for the factor loads. We apply the proposed model to obtain minimum variance portfolios of all stocks that belonged to the S&P100 during the sample period and show that it delivers less risky portfolios in comparison to benchmark models, including existing factor approaches.