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dc.contributor.authorWOŹNIAK, Tomasz
dc.date.accessioned2012-08-30T13:27:28Z
dc.date.available2012-08-30T13:27:28Z
dc.date.issued2012
dc.identifier.issn1725-6704
dc.identifier.urihttps://hdl.handle.net/1814/23337
dc.description.abstractSpillover and contagion effects have gained significant interest in the recent years of financial crisis. Attention has not only been directed to relations between returns of financial variables, but to spillovers in risk as well. I use the family of Constant Conditional Correlation GARCH models to model the risk associated with financial time series and to make inferences about Granger causal relations between second conditional moments. The restrictions for second-order Granger noncausality between two vectors of variables are derived. To assess the credibility of the noncausality hypotheses, I employ posterior odds ratios. This Bayesian method constitutes an alternative for classical tests that makes such testing possible, regardless of the form of the restrictions on the parameters of the model. Moreover, it relaxes the assumptions about the existence of higher-order moments of the processes required in classical tests. In the empirical example, I find that the pound-to-Euro exchange rate second-order causes the US dollar-to-Euro exchange rate, which confirms the meteor shower hypothesis of Engle, Ito & Lin (1990).en
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.relation.ispartofseriesEUI ECOen
dc.relation.ispartofseries2012/20en
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectSecond-Order Causalityen
dc.subjectVolatility Spilloversen
dc.subjectPosterior Oddsen
dc.subjectGARCH Modelsen
dc.subjectC11en
dc.subjectC12en
dc.subjectC32en
dc.subjectC53en
dc.titleTesting Causality between Two Vectors in Multivariate GARCH Modelsen
dc.typeWorking Paperen
dc.neeo.contributorWOŹNIAK|Tomasz|aut|
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