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Forecasting Multivariate Volatility using the VARFIMA Model on Realized Covariance Cholesky Factors

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Author Info

  • Roxana Halbleib

    ()
    (Universite libre de Bruxelles)

  • Valeri Voev

    ()
    (Aarhus University)

Abstract

This paper analyzes the forecast accuracy of the multivariate realized volatility model introduced by Chiriac and Voev (2010), subject to different degrees of model parametrization and economic evaluation criteria. Bymodelling the Cholesky factors of the covariancematrices, the model generates positive definite, but biased covariance forecasts. In this paper, we provide empirical evidence that parsimonious versions of the model generate the best covariance forecasts in the absence of bias correction. Moreover, we show by means of stochastic dominance tests that any risk averse investor, regardless of the type of utility function or return distribution, would be better-off from using this model than from using some standard approaches.

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Bibliographic Info

Article provided by Justus-Liebig University Giessen, Department of Statistics and Economics in its journal Journal of Economics and Statistics.

Volume (Year): 231 (2011)
Issue (Month): 1 (February)
Pages: 134-152

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Handle: RePEc:jns:jbstat:v:231:y:2011:i:1:p:134-152

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Keywords: Forecasting; fractional integration; stochastic dominance; portfolio optimization; realized covariance;

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References

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Cited by:
  1. Matthias R. Fengler & Ostap Okhrin, 2012. "Realized Copula," SFB 649 Discussion Papers SFB649DP2012-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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