Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Investigations on Dynamic Trading Strategy Utilizing Stochastic Optimal Control and Machine Learning

확률론적 최적제어와 기계학습을 이용한 동적 트레이딩 전략에 관한 고찰

  • 박주영 (고려대학교 과학기술대학 제어계측공학과) ;
  • 양동수 (고려대학교 과학기술대학 제어계측공학과) ;
  • 박경욱 (고려대학교 경상대학 경영학부)
  • Received : 2013.03.31
  • Accepted : 2013.05.19
  • Published : 2013.08.25
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Abstract

Recently, control theory including stochastic optimal control and various machine-learning-based artificial intelligence methods have become major tools in the field of financial engineering. In this paper, we briefly review some recent papers utilizing stochastic optimal control theory in the fields of the pair trading for mean-reverting markets and the trend-following strategy, and consider a couple of strategies utilizing both stochastic optimal control theory and machine learning methods to acquire more flexible and accessible tools. Illustrative simulations show that the considered strategies can yield encouraging results when applied to a set of real financial market data.

최근들어, 확률론적 최적제어를 포함한 제어이론과 각종 기계학습 기반 인공지능 방법론은 금융공학 분야의 주요 도구로 자리를 잡아 가고 있다. 본 논문에서는 평균회귀 현상을 보이는 시장을 위한 페어 트레이딩 전략 분야와 추세 추종형 트레이딩 전략 분야에 대해 확률론적 최적제어 이론을 활용한 최신 논문 몇 편을 간단히 살펴보고, 보다 융통성 있고 접근성이 좋은 도구를 확보하기 위하여 확률론적 최적제어이론과 기계학습 기법을 동시에 응용하는 전략을 고려한다. 예시를 위하여 실시한 시뮬레이션은 본 논문에서 고려한 전략이 실제 금융시장 데이터를 대상으로 적용될 때 고무적인 결과를 제공할 수 있음을 보여준다.

Keywords

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