Multivariate high-frequency-based volatility (HEAVY) models

Working paper

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.

Authors: Noureldin, D; Shephard, N; Sheppard, K

• Publication status: Published
• Publisher: University of Oxford
• Series: Department of Economics Discussion Paper Series
• Publication date: 2011-02-01
• Paper number: 533
• Keywords: realized covariance; GARCH; HEAVY model; Wishart distribution; covariance targeting; multi-step forecasting; multivariate volatility