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A Parametric Sharpe Ratio Optimization Approach for Fuzzy Portfolio Selection Problem

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  • Ying Liu
  • Ya-Nan Li

Abstract

When facing to make a portfolio decision, investors may care more about every portfolio’s performance on a return and risk trade-off. In this paper, a new low partial moment measurement that only punishes the loss risk is defined for selection variables based on L-S integral. Furthermore, a new performance measure for portfolio evaluation is proposed to generalize the Sharpe ratio in the fuzzy context. With the optimal performance criterion, a new parametric Sharpe ratio portfolio optimization model is developed wherein uncertain returns are presented as parametric interval-valued fuzzy variables. To make the proposed model easy to solve, we transform the fractional programming into an equivalent form and solve it with domain decomposition method (DDM). Finally, we apply the proposed performance measure into a portfolio selection problem, compare the computational results in different cases, and analyze the influence of different parameters on the optimal portfolio.

Suggested Citation

  • Ying Liu & Ya-Nan Li, 2017. "A Parametric Sharpe Ratio Optimization Approach for Fuzzy Portfolio Selection Problem," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-17, January.
    • Handle: RePEc:hin:jnlmpe:6279859
    DOI: 10.1155/2017/6279859
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