Forecasting Multivariate Volatility Using the Varfima Model on Realized Covariance Cholesky Factors
Journal of Economics and Statistics, Vol. 231, No. 1, pp. 134-152, 2011
ECARES working paper 2010‐041
26 Pages Posted: 3 Nov 2010 Last revised: 25 Oct 2011
Date Written: November 2, 2010
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. By modelling the Cholesky factors of the covariance matrices, 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, Stochastic dominance, Portfolio optimization, Realized covariance
JEL Classification: C32, C53, G11
Suggested Citation: Suggested Citation
