Portfolio selection based on fuzzy cross-entropy

  • Authors:
  • Zhongfeng Qin;Xiang Li;Xiaoyu Ji

  • Affiliations:
  • Department of Mathematical Sciences, Tsinghua University, Beijing 100084, China;Department of Mathematical Sciences, Tsinghua University, Beijing 100084, China;School of Business, Renmin University of China, Beijing 100872, China

  • Venue:
  • Journal of Computational and Applied Mathematics
  • Year:
  • 2009

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Abstract

In this paper, the Kapur cross-entropy minimization model for portfolio selection problem is discussed under fuzzy environment, which minimizes the divergence of the fuzzy investment return from a priori one. First, three mathematical models are proposed by defining divergence as cross-entropy, average return as expected value and risk as variance, semivariance and chance of bad outcome, respectively. In order to solve these models under fuzzy environment, a hybrid intelligent algorithm is designed by integrating numerical integration, fuzzy simulation and genetic algorithm. Finally, several numerical examples are given to illustrate the modeling idea and the effectiveness of the proposed algorithm.