Nonparametric inference of gradual changes in the jump behaviour of time-continuous processes

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dc.contributor.authorHoffmann, Michael
dc.contributor.authorVetter, Mathias
dc.contributor.authorDette, Holger
dc.date.accessioned2016-10-10T10:46:10Z
dc.date.available2016-10-10T10:46:10Z
dc.date.issued2016
dc.description.abstractIn applications changes of the properties of a stochastic feature occur often gradually rather than abruptly, that is: after a constant phase for some time they slowly start to change. Efficient analysis for change points should address the specific features of such a smooth change. In this paper we discuss statistical inference for localizing and detecting gradual changes in the jump characteristic of a discretely observed Ito semimartingale. We propose a new measure of time variation for the jump behaviour of the process. The statistical uncertainty of a corresponding estimate is analyzed deriving new results on the weak convergence of a sequential empirical tail integral process and a corresponding multiplier bootstrap procedure.en
dc.identifier.urihttp://hdl.handle.net/2003/35233
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-17276
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB823;49, 2016en
dc.subjectLevy measureen
dc.subjectgradual changesen
dc.subjectweak convergenceen
dc.subjectempirical processesen
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.titleNonparametric inference of gradual changes in the jump behaviour of time-continuous processesen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access

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