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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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Paper provided by University of Oxford, Department of Economics in its series Economics Series Working Papers with number 533.

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Date of creation: 01 Feb 2011
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Handle: RePEc:oxf:wpaper:533
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