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A new rank dependent utility approach to model risk averse preferences in portfolio optimization

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  • Leili Javanmardi
  • Yuri Lawryshyn

Abstract

In this paper we introduce a new rank dependent utility approach, which unlike existing models, provides an SSD efficient portfolio as a function of the investors’ quantified risk aversion degrees. A parametric family of distortion functions is considered to model various levels of risk aversion. Under assumptions of equally probable scenarios, for any distortion function the corresponding optimization models can be expressed as linear program and easily solved. An empirical study is performed to compare the performance of our proposed model to the previously proposed portfolio selection models in the literature. Copyright Springer Science+Business Media New York 2016

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  • Leili Javanmardi & Yuri Lawryshyn, 2016. "A new rank dependent utility approach to model risk averse preferences in portfolio optimization," Annals of Operations Research, Springer, vol. 237(1), pages 161-176, February.
    • Handle: RePEc:spr:annopr:v:237:y:2016:i:1:p:161-176:10.1007/s10479-014-1761-9
    DOI: 10.1007/s10479-014-1761-9
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    Cited by:

    1. Cristiano Arbex Valle & Diana Roman & Gautam Mitra, 2017. "Novel approaches for portfolio construction using second order stochastic dominance," Computational Management Science, Springer, vol. 14(2), pages 257-280, April.

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