摘要：In this article the Fama-French-Carhart factor model is used to obtain short selling-constrained and unconstrained minimum variance portfolios. For that purpose, conditional covariance matrices are obtained based on a recent multivariate factor GARCH specification with a flexible modeling strategy for the common factors, for the individual assets, and for the factor loads proposed by Santos & Moura (2012). An application involving 61 stocks traded on the São Paulo stock exchange (BM\&FBovespa) shows that the proposed specification delivers less risky portfolios on an out-of-sample basis in comparison to several benchmark models, including existing factor approaches.
其他摘要：In this article the Fama-French-Carhart factor model is used to obtain short selling-constrained and unconstrained minimum variance portfolios. For that purpose, conditional covariance matrices are obtained based on a recent multivariate factor GARCH specification with a flexible modeling strategy for the common factors, for the individual assets, and for the factor loads proposed by Santos & Moura (2012). An application involving 61 stocks traded on the São Paulo stock exchange (BM\&FBovespa) shows that the proposed specification delivers less risky portfolios on an out-of-sample basis in comparison to several benchmark models, including existing factor approaches.
关键词：correlação condicional dinâmica (DCC); previsão; Filtro de Kalman; CAPM com aprendizagem; otimização de carteiras; avaliação de performance
