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Erscheinungsjahr: 
2007
Schriftenreihe/Nr.: 
CoFE Discussion Paper No. 07/01
Verlag: 
University of Konstanz, Center of Finance and Econometrics (CoFE), Konstanz
Zusammenfassung: 
Modelling and forecasting the covariance of financial return series has always been a challenge due to the so-called curse of dimensionality. This paper proposes a methodology that is applicable in large dimensional cases and is based on a time series of realized covariance matrices. Some solutions are also presented to the problem of non-positive definite forecasts. This methodology is then compared to some traditional models on the basis of its forecasting performance employing Diebold-Mariano tests. We show that our approach is better suited to capture the dynamic features of volatilities and covolatilities compared to the sample covariance based models.
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