International Journal of Fuzzy Logic and Intelligent Systems

  • 제13권1호
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  • Pages.19-30
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  • 2013
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  • 1598-2645(pISSN)
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  • 2093-744X(eISSN)
한국지능시스템학회 (Korean Institute of Intelligent Systems)
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Approximate Dynamic Programming-Based Dynamic Portfolio Optimization for Constrained Index Tracking

  • Park, Jooyoung (Department of Control & Instrumentation Engineering, Korea University) ;
  • Yang, Dongsu (Department of Control & Instrumentation Engineering, Korea University) ;
  • Park, Kyungwook (School of Business Administration, Korea University)
  • 투고 : 2013.02.15
  • 심사 : 2013.03.05
  • 발행 : 2013.03.25
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초록

Recently, the constrained index tracking problem, in which the task of trading a set of stocks is performed so as to closely follow an index value under some constraints, has often been considered as an important application domain for control theory. Because this problem can be conveniently viewed and formulated as an optimal decision-making problem in a highly uncertain and stochastic environment, approaches based on stochastic optimal control methods are particularly pertinent. Since stochastic optimal control problems cannot be solved exactly except in very simple cases, approximations are required in most practical problems to obtain good suboptimal policies. In this paper, we present a procedure for finding a suboptimal solution to the constrained index tracking problem based on approximate dynamic programming. Illustrative simulation results show that this procedure works well when applied to a set of real financial market data.

키워드

참고문헌

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피인용 문헌

  1. Some Observations for Portfolio Management Applications of Modern Machine Learning Methods vol.16, pp.1, 2016, https://doi.org/10.5391/IJFIS.2016.16.1.44