Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/32175
Authors: 
Voev, Valeri
Year of Publication: 
2007
Series/Report no.: 
Discussion paper series // Zentrum für Finanzen und Ökonometrie, Universität Konstanz 2007,01
Abstract: 
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.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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