Dynamic Portfolio Optimization Using Generalized Dynamic Conditional Heteroskedastic Factor Models

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  • Shiohama Takayuki
    Department of Management Science, Faculty of Engineering, Tokyo University of Science, Kagurazaka 1-3, Shinjuku, Tokyo 162-8601, Japan.
  • Hallin Marc
    Institut de Recherche en Statistique, ECARES, Université libre de Bruxelles, CP 114, B-1050, Bruxelles, Belgium, ORFE, Princeton University, CentER, Tilburg University, and ECORE.
  • Veredas David
    ECARES and Solvay Brussels School of Economics and Management, Université libre de Bruxelles, CP 114, B-1050, Bruxelles, Belgium, and ECORE.
  • Taniguchi Masanobu
    Department of Applied Mathematics, School of Fundamental Science and Engineering, Waseda University, 3 -4-1, Okubo, Shinjuku, Tokyo 169-8555, Japan.

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Abstract

We model large panels of financial time series by means of generalized dynamic factor models with multivariate GARCH idiosyncratic components. Such models combine the features of dynamic factors with those of a generalized smooth transition conditional correlation (GSTCC) model, which belongs to the class of time-varying conditional correlation models. The model is applied to dynamic portfolio allocation with Value at Risk constraints on 6.5 years of daily TOPIX Sector Indexes. Results show that the proposed model yields better portfolio performance than other multivariate models proposed in the literature, including the traditional mean-variance approach.

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