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SUMMARY This paper introduces a new class of multivariate volatility models that utilizes high‐frequency data. We discuss the models' dynamics and highlight their differences from multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models. We also discuss their covariance targeting specification and provide closed‐form formulas for multi‐step forecasts. Estimation and inference strategies are outlined. Empirical results suggest that the HEAVY model outperforms the multivariate GARCH model out‐of‐sample, with the gains being particularly significant at short forecast horizons. Forecast gains are obtained for both forecast variances and correlations. Copyright © 2011 John Wiley & Sons, Ltd.
Noureldin et al. (Thu,) studied this question.
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