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2012-08-17Buch DOI: 10.18452/4420
Nonparametric Kernel Density Estimation Near the Boundary
dc.contributor.authorMalec, Peter
dc.contributor.authorSchienle, Melanie
dc.date.accessioned2017-06-16T00:42:28Z
dc.date.available2017-06-16T00:42:28Z
dc.date.created2012-11-16
dc.date.issued2012-08-17
dc.date.submitted2012-08-17
dc.identifier.issn1860-5664
dc.identifier.urihttp://edoc.hu-berlin.de/18452/5072
dc.description.abstractStandard fixed symmetric kernel type density estimators are known to encounter problems for positive random variables with a large probability mass close to zero. We show that in such settings, alternatives of asymmetric gamma kernel estimators are superior but also differ in asymptotic and finite sample performance conditional on the shape of the density near zero and the exact form of the chosen kernel. We therefore suggest a refined version of the gamma kernel with an additional tuning parameter according to the shape of the density close to the boundary. We also provide a data-driven method for the appropriate choice of the modified gamma kernel estimator. In an extensive simulation study we compare the performance of this refined estimator to standard gamma kernel estimates and standard boundary corrected and adjusted fixed kernels. We find that the finite sample performance of the proposed new estimator is superior in all settings. Two empirical applications based on high-frequency stock trading volumes and realized volatility forecasts demonstrate the usefulness of the proposed methodology in practice.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectKernel density estimationeng
dc.subjectboundary correctioneng
dc.subjectasymmetric kerneleng
dc.subject.ddc310 Statistik
dc.subject.ddc330 Wirtschaft
dc.titleNonparametric Kernel Density Estimation Near the Boundary
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-100205631
dc.identifier.doihttp://dx.doi.org/10.18452/4420
local.edoc.container-titleSonderforschungsbereich 649: Ökonomisches Risiko
local.edoc.pages36
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume2012
local.edoc.container-issue47
local.edoc.container-year2012
local.edoc.container-erstkatid2195055-6

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