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dc.contributor.authorKara, Emel Kızılok
dc.contributor.authorGebizlioǧlu, Ömer Lütfi
dc.date.accessioned2019-06-27T08:03:16Z
dc.date.available2019-06-27T08:03:16Z
dc.date.issued2014
dc.identifier.issn0377-0427
dc.identifier.issn1879-1778
dc.identifier.urihttps://hdl.handle.net/20.500.12469/764
dc.identifier.urihttps://doi.org/10.1016/j.cam.2013.04.050
dc.description.abstractThis paper attempts to determine the Value at Risk (VaR) and Conditional Value at Risk (CVaR) measures for the sum of bivariate risks under dependence. The computation of these risk measures is performed by the north-south quantile points of bivariate distributions. The Farlie-Gumbel-Morgenstern (FGM) copula model is chosen to express dependence of bivariate risks. The behaviors of VaR and CVaR are examined by varying dependence parameter values of the copula model and probability levels of the risk measures. The findings are interpreted from the view point of portfolio risk management. (C) 2013 Elsevier B.V. All rights reserved.
dc.language.isoEnglish
dc.publisherElsevier Science
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectRisk measures
dc.subjectCopula
dc.subjectBivariate quantiles
dc.subjectNorth-south quantile points
dc.titleMeasurement of bivariate risks by the north-south quantile points approach
dc.typeArticle
dc.identifier.startpage208
dc.identifier.endpage215
dc.relation.journalJournal of Computational and Applied Mathematics
dc.identifier.volume255
dc.identifier.wosWOS:000326201800017
dc.identifier.doi10.1016/j.cam.2013.04.050
dc.contributor.khasauthorGebizlioǧlu, Ömer Lütfi


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