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Ranking Multivariate GARCH Models by Problem Dimension

  • Massimiliano Caporin

    ()

    (Università di Padova)

  • Michael McAleer

    ()

    (Erasmus University Rotterdam)

In the last 15 years, several Multivariate GARCH (MGARCH) models have appeared in the literature. Some recent research has begun to examine MGARCH specifications in terms of their out-of-sample forecasting performance. In this paper, we provide an empirical comparison of a set of models, namely BEKK, DCC, Corrected DCC (cDCC) of Aeilli (2008), CCC, Exponentially Weighted Moving Average, and covariance shrinking, using the historical data of 89 US equities. Our methods follow some of the approach described in Patton and Sheppard (2009), and contribute to the literature in several directions. First, we consider a wide range of models, including the recent cDCC model and covariance shrinking. Second, we use a range of tests and approaches for direct and indirect model comparison, including the Weighted Likelihood Ratio test of Amisano and Giacomini (2007). Third, we examine how the model rankings are influenced by the cross-sectional dimension of the problem.

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Paper provided by Dipartimento di Scienze Economiche "Marco Fanno" in its series "Marco Fanno" Working Papers with number 0124.

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Length: 43 pages
Date of creation: Dec 2010
Date of revision:
Handle: RePEc:pad:wpaper:0124
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  1. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
  2. Caporin, M. & McAleer, M.J., 2010. "Do We Really Need Both BEKK and DCC? A Tale of Two Multivariate GARCH Models," Econometric Institute Research Papers EI 2010-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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  8. Massimiliano Caporin & Michael McAleer, 2009. "Do We Really Need Both BEKK and DCC? A Tale of Two Covariance Models," CIRJE F-Series CIRJE-F-638, CIRJE, Faculty of Economics, University of Tokyo.
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