Behavioral mean-variance portfolio selection

  • Junna Bi
  • , Hanqing Jin
  • , Qingbin Meng*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

In this paper, a behavioral mean-variance portfolio selection problem in continuous time is formulated and studied. Unlike in the standard mean-variance portfolio selection problem, the cumulative distribution function of the cash flow is distorted by the probability distortion function used in the behavioral mean-variance portfolio selection problem. With the presence of distortion functions, the convexity of the optimization problem is ruined, and the problem is no longer a conventional linear-quadratic (LQ) problem, and we cannot apply conventional optimization tools like convex optimization and dynamic programming. To address this challenge, we propose and demonstrate a solution scheme by taking the quantile function of the terminal cash flow as the decision variable, and then replace the corresponding optimal terminal cash flow with the optimal quantile function. This allows the efficient frontier and the efficient strategy to be exploited.

Original languageEnglish
Pages (from-to)644-663
Number of pages20
JournalEuropean Journal of Operational Research
Volume271
Issue number2
DOIs
StatePublished - 1 Dec 2018

Keywords

  • Applied probability
  • Behavioural OR
  • Mean-variance portfolio selection
  • Probability distortion
  • Quantile approach

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