The Genetic Algorithm

Burcu Adigüzel Mercangöz, Ergün Eroğlu
{"title":"The Genetic Algorithm","authors":"Burcu Adigüzel Mercangöz, Ergün Eroğlu","doi":"10.4018/978-1-5225-8103-1.CH007","DOIUrl":null,"url":null,"abstract":"The portfolio optimization is an important research field of the financial sciences. In portfolio optimization 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.","PeriodicalId":345892,"journal":{"name":"Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/978-1-5225-8103-1.CH007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

The portfolio optimization is an important research field of the financial sciences. In portfolio optimization 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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
遗传算法
投资组合优化是金融科学的一个重要研究领域。在投资组合优化问题中,其目的是从资产池中获得一定风险水平下的最佳收益,或者选择在一定收益水平下风险最低的资产来创建投资组合。投资组合的多样性提供了通过最小化风险来增加回报的机会。作为数学模型的有力替代,启发式方法被广泛应用于解决投资组合优化问题。遗传算法(GA)是一种受到生物进化启发的技术。虽然本书考虑了投资组合优化问题的启发式方法,但本章将给出遗传算法的实现步骤,并将该方法应用于一个基本示例中的投资组合优化问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A Novel Approach for Business Process Model Matching Using Genetic Algorithms A Modified Kruskal's Algorithm to Improve Genetic Search for Open Vehicle Routing Problem Missing Value Imputation Using ANN Optimized by Genetic Algorithm Optimization of Windspeed Prediction Using an Artificial Neural Network Compared With a Genetic Programming Model The Genetic Algorithm
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1