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Uncertain programming models for portfolio selection with uncertain returns

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  • Bo Zhang
  • Jin Peng
  • Shengguo Li

Abstract

In an indeterminacy economic environment, experts’ knowledge about the returns of securities consists of much uncertainty instead of randomness. This paper discusses portfolio selection problem in uncertain environment in which security returns cannot be well reflected by historical data, but can be evaluated by the experts. In the paper, returns of securities are assumed to be given by uncertain variables. According to various decision criteria, the portfolio selection problem in uncertain environment is formulated as expected-variance-chance model and chance-expected-variance model by using the uncertainty programming. Within the framework of uncertainty theory, for the convenience of solving the models, some crisp equivalents are discussed under different conditions. In addition, a hybrid intelligent algorithm is designed in the paper to provide a general method for solving the new models in general cases. At last, two numerical examples are provided to show the performance and applications of the models and algorithm.

Suggested Citation

  • Bo Zhang & Jin Peng & Shengguo Li, 2015. "Uncertain programming models for portfolio selection with uncertain returns," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(14), pages 2510-2519, October.
    • Handle: RePEc:taf:tsysxx:v:46:y:2015:i:14:p:2510-2519
    DOI: 10.1080/00207721.2013.871366
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    Cited by:

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    2. Pérez-Mesa, Juan Carlos & Pérez-Mesa, Fº Javier & Tapia-León, Juan José & Valera-Martínez, Diego, 2022. "Scheduling vegetable sales to supermarkets in Europe: The tomato case," MPRA Paper 119883, University Library of Munich, Germany.
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    4. Adam Borovička, 2022. "Stock portfolio selection under unstable uncertainty via fuzzy mean-semivariance model," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 595-616, June.
    5. Oleg Malafeyev & Achal Awasthi, 2017. "Dynamic optimization of a portfolio," Papers 1712.00585, arXiv.org.
    6. Li, Bo & Lu, Ziqiang, 2023. "Uncertain random enhanced index tracking for portfolio selection with parameter estimation and hypothesis test," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    7. Juan Carlos Pérez-Mesa & Francisco Javier Pérez-Mesa & Juan José Tapia-León & Diego Luis Valera, 2022. "Scheduling vegetable sales to supermarkets in Europe: The tomato case," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(11), pages 403-412.
    8. Jian Zhou & Yujiao Jiang & Athanasios A. Pantelous & Weiwen Dai, 2023. "A systematic review of uncertainty theory with the use of scientometrical method," Fuzzy Optimization and Decision Making, Springer, vol. 22(3), pages 463-518, September.

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