The Gumbel test and jumps in the volatility process

dc.contributor.authorPalmes, Christian
dc.contributor.authorWoerner, Jeannette H.C.
dc.date.accessioned2013-12-10T15:09:30Z
dc.date.available2013-12-10T15:09:30Z
dc.date.issued2013-12-10
dc.description.abstractIn the framework of jump detection in stochastic volatility models the Gumbel test based on extreme value theory has recently been introduced. Compared to other jump tests it possesses the advantages that the direction and location of jumps may also be detected. Furthermore, compared to the Barndorff-Nielsen and Shephard test based on bipower variation the Gumbel test possesses a larger power. However, so far one assumption was that the volatility process is Hölder continuous, though there is empirical evidence for jumps in the volatility as well. In this paper we derive that the Gumbel test still works under the setting of finitely many jumps not exceeding a certain size. Furthermore, we show that the given bound on the jump size is sharp.en
dc.identifier.urihttp://hdl.handle.net/2003/31294
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-13114
dc.language.isoen
dc.subjectjump testde
dc.subjectstochastic volatility modelen
dc.subjectvolatility process with jumpsen
dc.subjectGumbel distributionen
dc.subjectextreme value theoryen
dc.subjecthigh-frequency dataen
dc.subject.ddc610
dc.titleThe Gumbel test and jumps in the volatility processen
dc.typeTextde
dc.type.publicationtypepreprinten
dcterms.accessRightsopen access

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