Modelling and Forecasting Multivariate Realized Volatility

Journal of Applied Econometrics, Vol. 26, pp. 922-947, 2011

40 Pages Posted: 3 Sep 2008 Last revised: 7 Jan 2015

See all articles by Roxana Halbleib

Roxana Halbleib

University of Konstanz

Valeri Voev

Aarhus University - CREATES

Date Written: September 2, 2008

Abstract

This paper proposes a methodology for modelling time series of realized covariance matrices in order to forecast multivariate risks. The approach allows for flexible dynamic dependence patterns and guarantees positive definiteness of the resulting forecasts without imposing parameter restrictions. We provide an empirical application of the model, in which we show by means of stochastic dominance tests that the returns from an optimal portfolio based on the model's forecasts second-order dominate returns of portfolios optimized on the basis of traditional MGARCH models. This result implies that any risk-averse investor, regardless of the type of utility function, would be better-off using our model.

Keywords: Forecasting, Fractional integration, Stochastic dominance, Portfolio optimization, Realized covariance

JEL Classification: C32, C53, G11

Suggested Citation

Halbleib, Roxana and Voev, Valeri, Modelling and Forecasting Multivariate Realized Volatility (September 2, 2008). Journal of Applied Econometrics, Vol. 26, pp. 922-947, 2011, Available at SSRN: https://ssrn.com/abstract=1262160

Roxana Halbleib (Contact Author)

University of Konstanz ( email )

Universitaetsstr. 10
Box: D 124
78457 Konstanz
Germany

HOME PAGE: http://econometrics.wiwi.uni-konstanz.de/staff/halbleib.htm

Valeri Voev

Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

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