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Interval portfolio selection models within the framework of uncertainty theory

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  • Li, Xiang
  • Qin, Zhongfeng

Abstract

The expected returns for securities are traditionally estimated as crisp values. Since the improper values may bring on an unsuccessful investment decision, portfolio experts generally prefer offering interval estimations for expected returns rather than crisp ones. The portfolio selection problem with interval expected returns is widely studied recently. In this paper, by considering the security returns with interval expected returns as uncertain variables, a mean-semiabsolute deviation model is proposed within the framework of uncertainty theory, which is a crisp nonlinear programming model and can be well solved by the classical optimization algorithms. In order to illustrate the method, some numerical experiments are given and solved.

Suggested Citation

  • Li, Xiang & Qin, Zhongfeng, 2014. "Interval portfolio selection models within the framework of uncertainty theory," Economic Modelling, Elsevier, vol. 41(C), pages 338-344.
    • Handle: RePEc:eee:ecmode:v:41:y:2014:i:c:p:338-344
    DOI: 10.1016/j.econmod.2014.05.036
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    Cited by:

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    3. Lin Chen & Jin Peng & Bo Zhang & Isnaini Rosyida, 2017. "Diversified models for portfolio selection based on uncertain semivariance," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(3), pages 637-648, February.
    4. Wei Chen & Yuxi Gai & Pankaj Gupta, 2018. "Efficiency evaluation of fuzzy portfolio in different risk measures via DEA," Annals of Operations Research, Springer, vol. 269(1), pages 103-127, October.
    5. Fereshteh Vaezi & Seyed Jafar Sadjadi & Ahmad Makui, 2019. "A portfolio selection model based on the knapsack problem under uncertainty," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-19, May.

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