Multivariate High-Frequency-Based Volatility (HEAVY) Models

Diaa Noureldin, Neil Shephard () and Kevin Sheppard ()

No 533, Economics Series Working Papers from University of Oxford, Department of Economics

Abstract: This paper introduces a new class of multivariate volatility models that utilizes high-frequency data. We discuss the models' dynamics and highlight their differences frommultivariate 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.

Keywords: HEAVY model; GARCH; multivariate volatility; realized covariance; covariance targeting; multi-step forecasting; Wishart distribution (search for similar items in EconPapers)
JEL-codes: C32 C52 C58 (search for similar items in EconPapers)
Date: 2011-02-01
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-ets, nep-for, nep-mst and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (33)

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Related works:
Journal Article: Multivariate high‐frequency‐based volatility (HEAVY) models (2012)
Working Paper: Multivariate High-Frequency-Based Volatility (HEAVY) Models (2011)
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