Comparison of evolutionary techniques for Value-at-Risk calculation

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dc.authorid0000-0003-1440-3831
dc.authorid0000-0003-4496-5149
dc.authorid0000-0001-6252-1870
dc.contributor.authorUludağ, Gönülen_US
dc.contributor.authorEtaner Uyar, Ayşe Şimaen_US
dc.contributor.authorSenel, Keremen_US
dc.contributor.authorDağ, Hasanen_US
dc.date.accessioned2019-08-31T12:10:23Z
dc.date.accessioned2019-08-05T16:03:06Z
dc.date.available2019-08-31T12:10:23Z
dc.date.available2019-08-05T16:03:06Z
dc.date.issued2007
dc.departmentIşık Üniversitesi, Fen Edebiyat Fakültesi, Enformasyon Teknolojileri Bölümüen_US
dc.departmentIşık University, Faculty of Arts and Sciences, Department of Information Technologiesen_US
dc.description.abstractThe Value-at-Risk (VaR) approach has been used for measuring and controlling the market risks in financial institutions. Studies show that the t-distribution is more suited to representing the financial asset returns in VaR calculations than the commonly used normal distribution. The frequency of extremely positive or extremely negative financial asset returns is higher than that is suggested by normal distribution. Such a leptokurtic distribution can better be approximated by a t-distribution. The aim of this study is to asses the performance of a real coded Genetic Algorithm (CA) with Evolutionary Strategies (ES) approach for Maximum Likelihood (ML) parameter estimation. Using Monte Carlo (MC) simulations, we compare the test results of VaR simulations using the t-distribution, whose optimal parameters are generated by the Evolutionary Algorithms (EAs), to that of the normal distribution. It turns out that the VaR figures calculated with the assumption of normal distribution significantly understate the VaR figures computed from the actual historical distribution at high confidence levels. On the other hand, for the same confidence levels, the VaR figures calculated with the assumption of t-distribution are very close to the results found using the actual historical distribution. Finally, in order to speed up the MC simulation technique, which is not commonly preferred in financial applications due to its time consuming algorithm, we implement a parallel version of it.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationUludağ, G., Uyar, A. S., Şenel, K. & Dağ, H. (2007). Comparison of evolutionary techniques for value-at-risk calculation. Paper presented at the Applications Of Evolutionary Computing, Proceedings, 4448, 218-227.en_US
dc.identifier.endpage227
dc.identifier.isbn9783540718048
dc.identifier.isbn3540718044
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.scopus2-s2.0-34548092210
dc.identifier.scopusqualityQ3
dc.identifier.startpage218
dc.identifier.urihttps://hdl.handle.net/11729/1812
dc.identifier.volume4448
dc.identifier.wosWOS:000246103300024
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakConference Proceedings Citation Index – Science (CPCI-S)en_US
dc.institutionauthorSenel, Keremen_US
dc.institutionauthorDağ, Hasanen_US
dc.institutionauthorid0000-0003-4496-5149
dc.institutionauthorid0000-0001-6252-1870
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherSpringer-Verlag Berlinen_US
dc.relation.ispartofApplications Of Evolutionary Computing, Proceedingsen_US
dc.relation.ispartofseriesLecture Notes in Computer Scienceen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBanksen_US
dc.subjectEvolutionary algorithmen_US
dc.subjectEvolutionary algorithmsen_US
dc.subjectEvolutionary strategiesen_US
dc.subjectFinanceen_US
dc.subjectFinancial crisisen_US
dc.subjectGenetic algorithmen_US
dc.subjectLiquidityen_US
dc.subjectMarketingen_US
dc.subjectMaximum likelihooden_US
dc.subjectMaximum likelihood estimationen_US
dc.subjectMonte Carlo simulationen_US
dc.subjectParameter estimationen_US
dc.subjectRisk analysisen_US
dc.subjectT-distributionen_US
dc.subjectValue-at-risken_US
dc.titleComparison of evolutionary techniques for Value-at-Risk calculationen_US
dc.typeConference Objecten_US
dspace.entity.typePublication

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