Rates of almost sure convergence of plug-in estimates for distortion risk measures

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dc.contributor.authorZähle, Henryk
dc.date.accessioned2010-03-02T13:33:16Z
dc.date.available2010-03-02T13:33:16Z
dc.date.issued2010-03-02T13:33:16Z
dc.description.abstractIn this article, we consider plug-in estimates for distortion risk measures as for instance the Value-at-Risk, the Expected Shortfall or the Wang transform. We allow for fairly general estimates of the underlying unknown distribution function (beyond the classical empirical distribution function) to be plugged in the risk measure. We establish strong consistency of the estimates, we investigate the rate of almost sure convergence, and we study the small sample behavior by means of simulations.en
dc.identifier.urihttp://hdl.handle.net/2003/26949
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-8694
dc.language.isoen
dc.relation.ispartofseriesPreprints der Fakultät für Mathematik ; 2010-01de
dc.subjectrisk measureen
dc.subjectplug-in estimationen
dc.subjectempirical distribution functionen
dc.subjectsmoothingen
dc.subjectcensoringen
dc.subjectGlivenko-Cantelli theorem for weighted errorsde
dc.subject.ddc610
dc.titleRates of almost sure convergence of plug-in estimates for distortion risk measuresen
dc.typeTextde
dc.type.publicationtypepreprinten
dcterms.accessRightsopen access

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