Value at risk for risk management with normal-logDagum mixture distribution

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dc.contributor.authorErisoglu, Ulku
dc.contributor.authorKoroglu, Yasemin
dc.date.accessioned2024-02-23T14:20:22Z
dc.date.available2024-02-23T14:20:22Z
dc.date.issued2021
dc.departmentNEÜen_US
dc.description.abstractIn this article, we aimed to calculate the value at risk (VaR), which is one of the financial risk calculation methods, by using mixture of two different distributions when the financial data does not fit the normal distribution. The normal-logDagum distribution consisting of mixture of Normal and log-Dagum distributions is proposed to calculate the VaR for non-normal financial data in the study. The expected-maximization (EM) algorithm for the maximum likelihood estimates of the parameters of normal-logDagum was defined. In application, the stocks of bank and telecommunication companies were examined. VaR values obtained with different distributions are compared numerically. As a result of the comparison, it was seen that the modeling based on normal-logDagum distribution is more successful in the statistical modeling of financial data.en_US
dc.identifier.doi10.1080/09720510.2020.1826630
dc.identifier.endpage1501en_US
dc.identifier.issn0972-0510
dc.identifier.issn2169-0014
dc.identifier.issue7en_US
dc.identifier.startpage1489en_US
dc.identifier.urihttps://doi.org/10.1080/09720510.2020.1826630
dc.identifier.urihttps://hdl.handle.net/20.500.12452/13138
dc.identifier.volume24en_US
dc.identifier.wosWOS:000629820300001en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherTaylor & Francis Ltden_US
dc.relation.ispartofJournal Of Statistics & Management Systemsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMixture Distributionen_US
dc.subjectEm Algorithmen_US
dc.subjectNormal-Logdagumen_US
dc.subjectValue At Risk (Var)en_US
dc.titleValue at risk for risk management with normal-logDagum mixture distributionen_US
dc.typeArticleen_US

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