Modelling and Forecasting Multivariate Realized Volatility

Roxana Chiriac () and Valeri Voev ()
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Roxana Chiriac: Universität Konstanz

No 08-06, CoFE Discussion Paper from Center of Finance and Econometrics, University of Konstanz

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.

New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for, nep-ore and nep-upt
Date: 2008-09-01
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Working Paper: Modelling and Forecasting Multivariate Realized Volatility (2008)
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