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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/76900
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dc.contributor.authorMoralles, Herick Fernando-
dc.contributor.authorRebelatto, Daisy Aparecida do Nascimento-
dc.contributor.authorSartoris, Alexandre-
dc.date.accessioned2014-05-27T11:30:52Z-
dc.date.accessioned2016-10-25T18:55:05Z-
dc.date.available2014-05-27T11:30:52Z-
dc.date.available2016-10-25T18:55:05Z-
dc.date.issued2013-11-01-
dc.identifierhttp://dx.doi.org/10.1016/j.mcm.2013.07.002-
dc.identifier.citationMathematical and Computer Modelling, v. 58, n. 9-10, p. 1648-1658, 2013.-
dc.identifier.issn0895-7177-
dc.identifier.urihttp://hdl.handle.net/11449/76900-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/76900-
dc.description.abstractParametric VaR (Value-at-Risk) is widely used due to its simplicity and easy calculation. However, the normality assumption, often used in the estimation of the parametric VaR, does not provide satisfactory estimates for risk exposure. Therefore, this study suggests a method for computing the parametric VaR based on goodness-of-fit tests using the empirical distribution function (EDF) for extreme returns, and compares the feasibility of this method for the banking sector in an emerging market and in a developed one. The paper also discusses possible theoretical contributions in related fields like enterprise risk management (ERM). © 2013 Elsevier Ltd.en
dc.format.extent1648-1658-
dc.language.isoeng-
dc.sourceScopus-
dc.subjectAnderson-Darling-
dc.subjectGoodness-of-fit tests-
dc.subjectKolmogorov-Smirnov-
dc.subjectParametric Value-at-Risk-
dc.subjectTails-
dc.subjectGoodness-of-fit test-
dc.subjectValue at Risk-
dc.subjectRisk management-
dc.subjectValue engineering-
dc.subjectParameter estimation-
dc.titleParametric VaR with goodness-of-fit tests based on EDF statistics for extreme returnsen
dc.typeoutro-
dc.contributor.institutionUniversidade de São Paulo (USP)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationDepartment of Production Engineering University of São Paulo-
dc.description.affiliationDepartment of Economics Universidade Estadual Paulista Júlio de Mesquita Filho-
dc.description.affiliationUnespDepartment of Economics Universidade Estadual Paulista Júlio de Mesquita Filho-
dc.identifier.doi10.1016/j.mcm.2013.07.002-
dc.identifier.wosWOS:000325306700007-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofMathematical and Computer Modelling-
dc.identifier.scopus2-s2.0-84883557862-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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