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

Roxana Halbleib () and Valeri Voev ()

Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), 2011, vol. 231, issue 1, pages 134-152

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.

Keywords: Forecasting; fractional integration; stochastic dominance; portfolio optimization; realized covariance (search for similar items in EconPapers)
JEL-codes: C32 C53 G11 (search for similar items in EconPapers)
Date: 2011
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Working Paper: Forecasting Multivariate Volatility Using the VARFIMA Model on Realized Covariance Cholesky Factors (2010)
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Persistent link: http://EconPapers.repec.org/RePEc:jns:jbstat:v:231:y:2011:i:1:p:134-152

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