Nonparametric tests for constant tail dependence with an application to energy and finance

dc.contributor.authorBücher, Axel
dc.contributor.authorJäschke, Stefan
dc.contributor.authorWied, Dominik
dc.date.accessioned2013-08-14T09:15:16Z
dc.date.available2013-08-14T09:15:16Z
dc.date.issued2013-08-14
dc.description.abstractThe present paper proposes new tests for detecting structural breaks in the tail dependence of multivariate time series using the concept of tail copulas. To obtain asymptotic properties, we derive a new limit result for the sequential empirical tail copula process. Moreover, consistency of both the tests and a change-point estimator are proven. We analyze the finite sample behavior of the tests by Monte Carlo simulations. Finally, and crucial from a risk management perspective, we apply the new findings to datasets from energy and financial markets.en
dc.identifier.urihttp://hdl.handle.net/2003/30479
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-5511
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823;28/2013
dc.subjectChange-point detectionen
dc.subjectMultiplier bootstrapen
dc.subjectTail dependenceen
dc.subjectWeak convergenceen
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.titleNonparametric tests for constant tail dependence with an application to energy and financeen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access

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