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2005-01-12Buch DOI: 10.18452/8332
Stress Testing for VaR an CVaR
dc.contributor.authorDupacová, Jitka
dc.contributor.authorPolivka, Jan
dc.contributor.editorHigle, Julie L.
dc.contributor.editorRömisch, Werner
dc.contributor.editorSen, Surrajeet
dc.date.accessioned2017-06-16T20:02:59Z
dc.date.available2017-06-16T20:02:59Z
dc.date.created2005-09-08
dc.date.issued2005-01-12
dc.date.submitted2004-12-06
dc.identifier.urihttp://edoc.hu-berlin.de/18452/8984
dc.description.abstractPractical use of the contamination technique in stress testing for risk measures Value at Risk (VaR) and Conditional Value at Risk (CVaR) and for optimization problems with these risk criteria is discussed. Whereas for CVaR its application is straightforward, the presence of the simple chance constraint in the definition of VaR requires that various distributional and structural properties are fulfilled, namely, for the unperturbed problem. These requirements rule out direct applications of the contamination technique in the case of discrete distributions, which includes the empirical VaR. On the other hand, in the case of a normal distribution and parametric VaR one may exploit stability results valid for quadratic programs.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, Institut für Mathematik
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectScenario-based stochastic programseng
dc.subjectvalidation of resultseng
dc.subjectstress testingeng
dc.subjectcontamination boundseng
dc.subjectVaReng
dc.subjectCVaReng
dc.subject.ddc510 Mathematik
dc.titleStress Testing for VaR an CVaR
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-10046365
dc.identifier.doihttp://dx.doi.org/10.18452/8332
local.edoc.pages21
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-year2005
dc.identifier.zdb2936317-2
bua.series.nameStochastic Programming E-Print Series
bua.series.issuenumber2005,3

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