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A multiobjective credibilistic portfolio selection model. Empirical study in the Latin American integrated market

Author

Listed:
  • Fernando García

    (Polytechnic University of Valencia, Spain)

  • Jairo González-Bueno

    (Pontifical Bolivarian University, Colombia)

  • Francisco Guijarro

    (Polytechnic University of Valencia, Spain)

  • Javier Oliver

    (Polytechnic University of Valencia, Spain)

Abstract

This paper extends the stochastic mean-semivariance model to a fuzzy multiobjective model, where apart from return and risk, also liquidity is considered to measure the performance of a portfolio. Uncertainty of future return and liquidity of each asset are modeled using L-R type fuzzy numbers that belong to the power reference function family. The decision process of this novel approach takes into account not only the multidimensional nature of the portfolio selection problem but also realistic constraints by investors. Particularly, it optimizes the expected return, the semivariance and the expected liquidity of a given portfolio, considering cardinality constraint and upper and lower bound constraints. The constrained portfolio optimization problem resulting is solved using the algorithm NSGA-II. As a novelty, in order to select the optimal portfolio, this study defines the credibilistic Sortino ratio as the ratio between the credibilistic risk premium and the credibilistic semivariance. An empirical study is included to show the effectiveness and efficiency of the model in practical applications using a data set of assets from the Latin American Integrated Market.

Suggested Citation

  • Fernando García & Jairo González-Bueno & Francisco Guijarro & Javier Oliver, 2020. "A multiobjective credibilistic portfolio selection model. Empirical study in the Latin American integrated market," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 8(2), pages 1027-1046, December.
    • Handle: RePEc:ssi:jouesi:v:8:y:2020:i:2:p:1027-1046
    DOI: 10.9770/jesi.2020.8.2(62)
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    References listed on IDEAS

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    1. Bawa, Vijay S., 1975. "Optimal rules for ordering uncertain prospects," Journal of Financial Economics, Elsevier, vol. 2(1), pages 95-121, March.
    2. Gupta, Pankaj & Mittal, Garima & Mehlawat, Mukesh Kumar, 2013. "Expected value multiobjective portfolio rebalancing model with fuzzy parameters," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 190-203.
    3. Fishburn, Peter C, 1977. "Mean-Risk Analysis with Risk Associated with Below-Target Returns," American Economic Review, American Economic Association, vol. 67(2), pages 116-126, March.
    4. Arenas Parra, M. & Bilbao Terol, A. & Rodriguez Uria, M. V., 2001. "A fuzzy goal programming approach to portfolio selection," European Journal of Operational Research, Elsevier, vol. 133(2), pages 287-297, January.
    5. Omar Masood & Manuela Tvaronavičienė & Kiran Javaria, 2019. "Impact of oil prices on stock return: evidence from G7 countries," Post-Print hal-02163013, HAL.
    6. Fernando García & Jairo González-Bueno & Javier Oliver & Nicola Riley, 2019. "Selecting Socially Responsible Portfolios: A Fuzzy Multicriteria Approach," Sustainability, MDPI, vol. 11(9), pages 1-14, April.
    7. Fei Ren & Ya-Nan Lu & Sai-Ping Li & Xiong-Fei Jiang & Li-Xin Zhong & Tian Qiu, 2017. "Dynamic Portfolio Strategy Using Clustering Approach," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-23, January.
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    Cited by:

    1. Zdravka Aljinović & Branka Marasović & Tea Šestanović, 2021. "Cryptocurrency Portfolio Selection—A Multicriteria Approach," Mathematics, MDPI, vol. 9(14), pages 1-21, July.

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    More about this item

    Keywords

    fuzzy portfolio selection; L-R fuzzy numbers; credibility theory; mean-semivariance-liquidity; evolutionary multiobjective optimization; emerging financial markets;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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