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dc.contributor.authorDette, Holgerde
dc.contributor.authorVetter, Mathiasde
dc.date.accessioned2009-10-29T09:59:14Z-
dc.date.available2009-10-29T09:59:14Z-
dc.date.issued2009-07-01de
dc.identifier.urihttp://hdl.handle.net/2003/26473-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-12662-
dc.description.abstractWe consider the problem of testing the parametric form of the volatility for high frequency data. It is demonstrated that in the presence of microstructure noise commonly used tests do not keep the preassigned level and are inconsistent. The concept of preaveraging is used to construct new tests, which do not suffer from these drawbacks. These tests are based on a Kolmogorov or Cramér-von-Mises functional of an integrated stochastic process, for which weak convergence to a (conditional) Gaussian process is established. The finite sample properties of a bootstrap version of the test are illustrated by means of a simulation study.en
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB 823; 1/2009de
dc.subjectgoodness-of-fit testen
dc.subjectheteroscedasticityen
dc.subjectmicrostructure noiseen
dc.subjectparametric bootstrapen
dc.subjectstable convergenceen
dc.subject.ddc310de
dc.subject.ddc330de
dc.subject.ddc620de
dc.titleModel checks for the volatility under microstructure noiseen
dc.typeTextde
dc.type.publicationtypereportde
dcterms.accessRightsopen access-
Appears in Collections:Sonderforschungsbereich (SFB) 823

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