dc.contributor.author | Eroğlu, Ergün | |
dc.contributor.author | Adıgüzel Mercangöz, Burcu | |
dc.date.accessioned | 2023-05-29T13:42:15Z | |
dc.date.available | 2023-05-29T13:42:15Z | |
dc.identifier.citation | Adıgüzel 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.other | av_3a64e3de-4694-469d-9663-d3510be33ea1 | |
dc.identifier.other | vv_1032021 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12627/189091 | |
dc.identifier.uri | https://www.igi-global.com/ | |
dc.description.abstract | The 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.iso | eng | |
dc.publisher | IGI Global | |
dc.subject | Sosyal Bilimler (SOC) | |
dc.subject | Sosyal ve Beşeri Bilimler | |
dc.title | Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms | |
dc.type | Kitapta Bölüm | |
dc.contributor.department | İstanbul Üniversitesi , Ulaştırma Ve Lojistik Fakültesi , Ulaştırma Ve Lojistik Bölümü | |
dc.contributor.firstauthorID | 4253821 | |