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dc.contributor.authorChiriac, Roxanaen
dc.contributor.authorVoev, Valerien
dc.date.accessioned2009-09-17-
dc.date.accessioned2010-05-14T12:00:37Z-
dc.date.available2010-05-14T12:00:37Z-
dc.date.issued2008-
dc.identifier.piurn:nbn:de:bsz:352-opus-116658en
dc.identifier.urihttp://hdl.handle.net/10419/32169-
dc.description.abstractThis 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.en
dc.language.isoengen
dc.publisher|aUniversity of Konstanz, Center of Finance and Econometrics (CoFE) |cKonstanzen
dc.relation.ispartofseries|aCoFE Discussion Paper |x08/06en
dc.subject.jelC32en
dc.subject.jelC53en
dc.subject.jelG11en
dc.subject.ddc330en
dc.subject.keywordForecastingen
dc.subject.keywordFractional integrationen
dc.subject.keywordStochastic dominanceen
dc.subject.keywordPortfolio optimizationen
dc.subject.keywordRealized covarianceen
dc.titleModelling and forecasting multivariate realized volatility-
dc.type|aWorking Paperen
dc.identifier.ppn608952109en
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen
dc.identifier.repecRePEc:zbw:cofedp:0806-

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