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dc.contributor.authorVetter, Mathias-
dc.date.accessioned2013-04-23T13:19:51Z-
dc.date.available2013-04-23T13:19:51Z-
dc.date.issued2013-04-23-
dc.identifier.urihttp://hdl.handle.net/2003/30179-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-10476-
dc.description.abstractIn this paper we are concerned with inference on the Lévy measure of a Lévy process in case of noisy high frequency observations. It is known that standard techniques for denoising, developed for diffusion settings, do not work in this case. For this reason, we provide an extension of the pre-averaging method which allows for a consistent estimation of the Lévy distribution function even under microstructure noise. Interestingly, the asymptotic behaviour of the novel estimator is the same as in the no-noise case. This is in sharp contrast to what is known for diffusions.en
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823;16/2013en
dc.subjectLévy processen
dc.subjectmicrostructure noiseen
dc.subjectnonparametric statisticsen
dc.subjectweak convergenceen
dc.subject.ddc310-
dc.subject.ddc330-
dc.subject.ddc620-
dc.titleInference on the Lévy measure in case of noisy observationsen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 823

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