Evolving Profitable Trading Rules with Genetic Algorithms

被引：0

作者：

Shin, Kyung-shik ^{[2
]}

Kim, Kyoung-jae ^{[1
]}

机构：

[1] Dongguk Univ, Dept Management Informat Syst, Seoul 100715, South Korea

[2] Ewha Womans Univ, Coll Business Adm, Seoul 120750, South Korea

来源：

INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL | 2012年 / 15卷 / 08期

关键词：

Genetic algorithms; Stock market prediction; Trading rule extraction; Technical indicators; Buy & hold strategy;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The goal of this study is to mine reasonable trading rules using genetic algorithms (GAs) for the Korea Stock Price Index 200 (KOSPI 200) futures. During the course of this study, we have found trading rules that would have yielded the highest returns over a certain time period using historical data. The simulated results of buying and selling according to the trading rules were outstanding. These experimental results suggest that genetic algorithms are promising methods for extracting profitable trading rules.

引用

页码：3313 / 3321

页数：9

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