摘要：We apply a parsimonious multivariate GARCH speci cation based on the Fama-French-Carhart factor model to generate high-dimensional conditional covariance matrices and to obtain shortselling-constrained and unconstrained minimum variance portfolios. An application involving 61 stocks traded on the S~ao Paulo stock exchange (BM&FBovespa) shows that the proposed speci cation delivers less risky portfolios on an out-of-sample basis in comparison to several benchmark models, including existing factor approaches.
关键词：portfolio optimization; forecasting; performance evaluation; Sharpe ratio
