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dc.contributor.authorGribisch, Bastianen_US
dc.date.accessioned2012-11-15en_US
dc.date.accessioned2012-11-16T10:16:25Z-
dc.date.available2012-11-16T10:16:25Z-
dc.date.issued2012en_US
dc.identifier.urihttp://hdl.handle.net/10419/66205-
dc.description.abstractThis paper generalizes the basic Wishart multivariate stochastic volatility model of Philipov and Glickman (2006) and Asai and McAleer (2009) to encompass regime switching behavior. The latent state variable is driven by a first-order Markov process. The model allows for state-dependent (co)variance and correlation levels and state-dependent volatility spillover effects. Parameter estimates are obtained using Bayesian Markov Chain Monte Carlo procedures and filtered estimates of the latent variances and covariances are generated by particle filter techniques. The model is applied to five European stock index return series. The results show that the proposed regime-switching specification substantially improves the in-sample fit and the VaR forecasting performance relative to the basic model.en_US
dc.language.isoengen_US
dc.publisherUniv., Dep. of Economics Kielen_US
dc.relation.ispartofseriesEconomics Working Paper, Christian-Albrechts-Universität Kiel, Department of Economics 2012-14en_US
dc.subject.jelC32en_US
dc.subject.jelC58en_US
dc.subject.jelG17en_US
dc.subject.ddc330en_US
dc.subject.keywordMultivariate stochastic volatilityen_US
dc.subject.keywordDynamic correlationsen_US
dc.subject.keywordWishart distributionen_US
dc.subject.keywordMarkov switchingen_US
dc.subject.keywordMarkov chain Monte Carloen_US
dc.titleMultivariate wishart stochastic volatility and changes in regimeen_US
dc.typeWorking Paperen_US
dc.identifier.ppn729892808en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
dc.identifier.repecRePEc:zbw:cauewp:201214-
Appears in Collections:Economics Working Papers, Department of Economics, CAU Kiel

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