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dc.contributor.authorEroğlu, Ergün
dc.contributor.authorAdıgüzel Mercangöz, Burcu
dc.date.accessioned2023-05-29T13:42:15Z
dc.date.available2023-05-29T13:42:15Z
dc.identifier.citationAdıgüzel Mercangöz B., Eroğlu E., The Genetic Algorithm: An Application on Portfolio Optimization, "Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms", Information Resources Management Association, Editör, IGI Global, Pennsylvania, ss.790-810, 2021
dc.identifier.otherav_3a64e3de-4694-469d-9663-d3510be33ea1
dc.identifier.othervv_1032021
dc.identifier.urihttp://hdl.handle.net/20.500.12627/189091
dc.identifier.urihttps://www.igi-global.com/
dc.description.abstractThe portfolio optimization is an important research field of the financial sciences. In portfolio optimiza- tion problems, it is aimed to create portfolios by giving the best return at a certain risk level from the asset pool or by selecting assets that give the lowest risk at a certain level of return. The diversity of the portfolio gives opportunity to increase the return by minimizing the risk. As a powerful alternative to the mathematical models, heuristics is used widely to solve the portfolio optimization problems. The genetic algorithm (GA) is a technique that is inspired by the biological evolution. While this book considers the heuristics methods for the portfolio optimization problems, this chapter will give the implementing steps of the GA clearly and apply this method to a portfolio optimization problem in a basic example.
dc.language.isoeng
dc.publisherIGI Global
dc.subjectSosyal Bilimler (SOC)
dc.subjectSosyal ve Beşeri Bilimler
dc.titleResearch Anthology on Multi-Industry Uses of Genetic Programming and Algorithms
dc.typeKitapta Bölüm
dc.contributor.departmentİstanbul Üniversitesi , Ulaştırma Ve Lojistik Fakültesi , Ulaştırma Ve Lojistik Bölümü
dc.contributor.firstauthorID4253821


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