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Multivariate High-Frequency-Based Volatility (HEAVY) Models

  • Diaa Noureldin

    ()

    (Dept of Economics and Oxford-Man Institute of Quantitative Finance, University of Oxford)

  • Neil Shephard

    ()

    (Dept of Economics and Oxford-Man Institute of Quantitative Finance, University of Oxford.)

  • Kevin Sheppard

    ()

    (Dept of Economics and Oxford-Man Institute of Quantitative Finance, University of Oxford.)

This paper introduces a new class of multivariate volatility models that utilizes high-frequency data. We discuss the models dynamics and highlight their di¤erences 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 ob- tained for both forecast variances and correlations.

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File URL: http://www.nuffield.ox.ac.uk/economics/papers/2011/w1/Heavy_18022011.pdf
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Paper provided by Economics Group, Nuffield College, University of Oxford in its series Economics Papers with number 2011-W01.

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Length: 41 pages
Date of creation: 18 Feb 2011
Date of revision:
Handle: RePEc:nuf:econwp:1101
Contact details of provider: Web page: http://www.nuff.ox.ac.uk/economics/

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