Using the extremal index for value-at-risk backtesting

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dc.contributor.authorBücher, Axel
dc.contributor.authorPosch, Peter N.
dc.contributor.authorSchmidtke, Philipp
dc.date.accessioned2018-10-19T14:45:07Z
dc.date.available2018-10-19T14:45:07Z
dc.date.issued2018
dc.description.abstractWe introduce a set of new Value-at-Risk independence backtests by establishing a connection between the independence property of Value-at-Risk forecasts and the extremal index, a general measure of extremal clustering of stationary sequences. We introduce a sequence of relative excess returns whose extremal index has to be estimated. We compare our backtest to both popular and recent competitors using Monte-Carlo simulations and find considerable power in many scenarios. In an applied section we perform realistic out-of-sample forecasts with common forecasting models and discuss advantages and pitfalls of our approach.en
dc.identifier.urihttp://hdl.handle.net/2003/37201
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-19196
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB823;24/2018
dc.subjectVaR backtestingen
dc.subjectrisk measuresen
dc.subjectindependenceen
dc.subjectextremal indexen
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.subject.rswkValue at Riskde
dc.subject.rswkStatistischer Testde
dc.subject.rswkSchätzverfahrende
dc.subject.rswkExtremwertstatistikde
dc.titleUsing the extremal index for value-at-risk backtestingen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access
eldorado.secondarypublicationfalsede

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