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dc.contributor.authorIngo, Kleinen_US
dc.contributor.authorChristian, Köcken_US
dc.contributor.authorFabian, Tinklen_US
dc.date.accessioned2009-11-09en_US
dc.date.accessioned2010-01-13T14:01:54Z-
dc.date.available2010-01-13T14:01:54Z-
dc.date.issued2009en_US
dc.identifier.urihttp://hdl.handle.net/10419/29549-
dc.description.abstractThe serial dependency of multivariate financial data will often be filtered by considering the residuals of univariate GARCH models adapted to every single series. This is the correct filtering strategy if the multivariate process follows a so-called copula based multivariate dynamic model (CMD). These multivariate dynamic models combine univariate GARCH in a linear or nonlinear way. In these models the parameters of the marginal distribution (=univariate GARCH models) and the dependence parameter are separable in the sense that they can be estimated in two or more steps. In the first step the parameters of the marginal distribution will be estimated and in the second step the parameter(s) of dependence.To the class of CMD models belong several multivariate GARCH models like the CCC and the DCC model. In contrast the BEKK model, f.e., does not belong to this class. If the BEKK model is correctly specified the above mentioned filtering strategy could fail from a theoretical point of view. Up to now, it is not known which dynamic copula is incorporated in a BEKK model. We will show that if the distribution of the innovations (i.e. the residuals) of MGARCH models is spherical the conditional distribution of the whole MGARCH process belongs to the elliptical distribution family. Therefore estimating the dependence of a BEKK model by copulas from the elliptical family should be an appropriate strategy to identify the dependence (i.e. correlation) between the univariate time series. Furthermore we will show, that a diagonal BEKK model can be separated in its margins and a copula, but that this strategy falls short of investigating full BEKK models.en_US
dc.language.isoengen_US
dc.publisherUniv.; Inst. für Wirtschaftspolitik und Quantitative Wirtschaftsforschung Erlangenen_US
dc.relation.ispartofseriesIWQW discussion paper series 11/2009en_US
dc.subject.ddc330en_US
dc.subject.stwARCH-Modellen_US
dc.subject.stwZeitreihenanalyseen_US
dc.subject.stwKopula (Mathematik)en_US
dc.subject.stwFinanzmarkten_US
dc.subject.stwSimulationen_US
dc.subject.stwTheorieen_US
dc.titleSpatial-serial dependency in multivariate GARCH models and dynamic copulas: a simulation studyen_US
dc.typeWorking Paperen_US
dc.identifier.ppn612509605en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungen-
dc.identifier.repecRePEc:zbw:iwqwdp:112009-
Appears in Collections:IWQW Discussion Paper Series, FAU Erlangen-Nürnberg

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