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Forecasting Conditional Covariance Matrices in High-Dimensional Time Series: a General Dynamic Factor Approach

par Hallin, Marc ;Hotta, Luis K.;Mazzeu, João H. G;Trucios-Maza, Carlos Cesar ;Valls Pereira, Pedro L.;Zevallos, Mauricio
Publication Publié, 2019-06

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Résumé :

Based on a General Dynamic Factor Model with infinite-dimensional factor space, we develop a new estimation and forecasting procedures for conditional covariance matrices in high-dimensional time series. The performance of our approach is evaluated via Monte Carlo experiments, outperforming many alternative methods. The new procedure is used to construct minimum variance portfolios for a high-dimensional panel of assets. The results are shown to achieve better out-of-sample portfolio performance than alternative existing procedures.