Evolving profitable trading rules with genetic algorithms

Kyung Shik Shin, Kyoung Jae Kim

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


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.

Original languageEnglish
Pages (from-to)3313-3321
Number of pages9
JournalInformation (Japan)
Issue number8
StatePublished - Aug 2012


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


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