Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/54327
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dc.contributor.authorJirakom Sirisrisakulchaien_US
dc.contributor.authorKittawit Autchariyapanitkulen_US
dc.contributor.authorNapat Harnpornchaien_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2018-09-04T10:12:03Z-
dc.date.available2018-09-04T10:12:03Z-
dc.date.issued2015-09-01en_US
dc.identifier.issn18838014en_US
dc.identifier.issn13430130en_US
dc.identifier.other2-s2.0-84943392205en_US
dc.identifier.other10.20965/jaciii.2015.p0619en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84943392205&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/54327-
dc.description.abstractThis paper applied possibilistic approaches to a portfolio selection model. We considered a return rate as fuzzy variables. Based on the concept of possibilistic moments of fuzzy numbers, fuzzy stock returns and market risks are quantified by possibilistic mean and lower possibilistic semivariance, respectively. The non-dominated sorting genetic algorithm II (NSGA-II) was used to obtain the pareto optimal investment strategies for the integrated oil and gas company stocks.en_US
dc.subjectComputer Scienceen_US
dc.titlePortfolio optimization of financial returns using fuzzy approach with NSGA-II algorithmen_US
dc.typeJournalen_US
article.title.sourcetitleJournal of Advanced Computational Intelligence and Intelligent Informaticsen_US
article.volume19en_US
article.stream.affiliationsChiang Mai Universityen_US
article.stream.affiliationsMaejo Universityen_US
Appears in Collections:CMUL: Journal Articles

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