New Possibilistic Mean - Variance Model Based on the Principal Components Analysis: An Application on the Turkish Holding Stocks

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dc.authoridGoktas, Furkan/0000-0001-9291-3912
dc.authoridDURAN, AHMET/0000-0001-9835-0006
dc.contributor.authorGoktas, Furkan
dc.contributor.authorDuran, Ahmet
dc.date.accessioned2024-09-29T16:12:17Z
dc.date.available2024-09-29T16:12:17Z
dc.date.issued2019
dc.departmentKarabük Üniversitesien_US
dc.description.abstractPossibility Theory is a great tool to deal with the imprecise probability. However, the possibilistic counterpart of the mean - variance (MV) model has serious shortcomings. Thus, we propose a new possibilistic MV model, which depends on the Principal Components Analysis. The proposed model enables to incorporate subjective judgments into the portfolio selection. In addition, it captures the asymmetry in the return data unlike the MV model. The proposed model is also tractable as the MV model since it can be expressed as a concave quadratic maximization problem. After laying down the theoretical points, we illustrate it by using a real data set of six holding stocks trading on the Borsa Istanbul (BIST). We also compare the profitability and performance results of the proposed model and the MV model.en_US
dc.identifier.endpage476en_US
dc.identifier.issn1542-3980
dc.identifier.issn1542-3999
dc.identifier.issue5-6en_US
dc.identifier.startpage455en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14619/8644
dc.identifier.volume32en_US
dc.identifier.wosWOS:000466982400005en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherOld City Publishing Incen_US
dc.relation.ispartofJournal of Multiple-Valued Logic and Soft Computingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPortfolio selectionen_US
dc.subjectimprecise probabilityen_US
dc.subjectpossibility theoryen_US
dc.subjectfuzzy logicen_US
dc.subjecttriangular fuzzy numbersen_US
dc.subjectsubjective judgmentsen_US
dc.subjectprincipal components analysisen_US
dc.subjectmean-variance modelen_US
dc.titleNew Possibilistic Mean - Variance Model Based on the Principal Components Analysis: An Application on the Turkish Holding Stocksen_US
dc.typeArticleen_US

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