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Multivariate high‐frequency‐based volatility (HEAVY) models

  • Diaa Noureldin
  • Neil Shephard
  • Kevin Sheppard

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 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.

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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 27 (2012)
Issue (Month): 6 (09)
Pages: 907-933

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Handle: RePEc:wly:japmet:v:27:y:2012:i:6:p:907-933
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