Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Using cluster analysis and genetic algorithm to develop portfolio investment strategy based on investor information

군집분석과 유전자 알고리즘을 활용한 투자자 거래정보 기반 포트폴리오 투자전략

  • Cheong, Donghyun (Department of Information and Industrial Engineering, Yonsei University) ;
  • Oh, Kyong Joo (Department of Information and Industrial Engineering, Yonsei University)
  • 정동현 (연세대학교 정보산업공학과) ;
  • 오경주 (연세대학교 정보산업공학과)
  • Received : 2013.12.02
  • Accepted : 2014.01.06
  • Published : 2014.01.31
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Abstract

The main purpose of this study is to propose a portfolio investment strategy based on investor types information. For improvement of investment performance, artificial intelligence techniques are used to construct a portfolio. Among many artificial intelligence techniques, cluster analysis is applied to select securities and genetic algorithm is applied to assign the respective weight within the portfolio. Empirical experiments in the Korean stock market show that proposed portfolio investment strategy is practicable and superior strategy. This result implies that analysis of investor's trading behavior may assist investors to make an investment decision and to get superior performance.

본 연구에서는 투자자 거래 정보를 활용한 포트폴리오 투자전략을 제안했다. 포트폴리오를 구성하는 과정에서 군집분석을 활용하여 기대수익이 높은 종목을 선정하고, 유전자 알고리즘으로 포트폴리오를 최적화하여 투자성과를 높이고자 했다. 2007년 4월부터 2013년 6월까지의 국내 주식시장을 대상으로 한 실증분석을 통하여, 본 연구에서 제안한 포트폴리오 투자전략의 유용성과 우수성을 확인 했다. 본 연구의 결과는 특정 투자 주체의 매매행태를 분석하여 투자 의사결정에 이용할 수 있으며, 이를 통하여 높은 투자성과를 얻을 수 있음을 보여준다. 또한 인공지능 기법이 투자 의사결정에 유용하게 사용될 수 있음을 시사한다.

Keywords

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