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Copula-Based Factor Models for Multivariate Asset Returns

Author

Listed:
  • Eugen Ivanov

    (Department of Economics, University of Augsburg, Universitätsstr. 16, 86159 Augsburg, Germany)

  • Aleksey Min

    (Department of Mathematics, Technical University of Munich, Boltzmannstr. 3, 85748 Garching, Germany)

  • Franz Ramsauer

    (Department of Mathematics, Technical University of Munich, Boltzmannstr. 3, 85748 Garching, Germany)

Abstract

Recently, several copula-based approaches have been proposed for modeling stationary multivariate time series. All of them are based on vine copulas, and they differ in the choice of the regular vine structure. In this article, we consider a copula autoregressive (COPAR) approach to model the dependence of unobserved multivariate factors resulting from two dynamic factor models. However, the proposed methodology is general and applicable to several factor models as well as to other copula models for stationary multivariate time series. An empirical study illustrates the forecasting superiority of our approach for constructing an optimal portfolio of U.S. industrial stocks in the mean-variance framework.

Suggested Citation

  • Eugen Ivanov & Aleksey Min & Franz Ramsauer, 2017. "Copula-Based Factor Models for Multivariate Asset Returns," Econometrics, MDPI, vol. 5(2), pages 1-24, May.
    • Handle: RePEc:gam:jecnmx:v:5:y:2017:i:2:p:20-:d:98854
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    References listed on IDEAS

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    Cited by:

    1. Monica Defend & Aleksey Min & Lorenzo Portelli & Franz Ramsauer & Francesco Sandrini & Rudi Zagst, 2021. "Quantifying Drivers of Forecasted Returns Using Approximate Dynamic Factor Models for Mixed-Frequency Panel Data," Forecasting, MDPI, vol. 3(1), pages 1-35, February.
    2. Emma Apps, 2020. "Application of the Absorption Ratio to Illustrate Financial Connectedness and Interlinkages," Working Papers 202022, University of Liverpool, Department of Economics.

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