Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/32169 
Year of Publication: 
2008
Series/Report no.: 
CoFE Discussion Paper No. 08/06
Publisher: 
University of Konstanz, Center of Finance and Econometrics (CoFE), 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.
Subjects: 
Forecasting
Fractional integration
Stochastic dominance
Portfolio optimization
Realized covariance
JEL: 
C32
C53
G11
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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