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Credibilistic Multi-Period Mean-Entropy Rolling Portfolio Optimization Problem Based on Multi-Stage Scenario Tree

Author

Listed:
  • Pejman Peykani

    (School of Industrial Engineering, Iran University of Science and Technology, Tehran 1684613114, Iran)

  • Mojtaba Nouri

    (School of Industrial Engineering, Iran University of Science and Technology, Tehran 1684613114, Iran)

  • Mir Saman Pishvaee

    (School of Industrial Engineering, Iran University of Science and Technology, Tehran 1684613114, Iran)

  • Camelia Oprean-Stan

    (Faculty of Economic Sciences, Lucian Blaga University of Sibiu, 550324 Sibiu, Romania)

  • Emran Mohammadi

    (School of Industrial Engineering, Iran University of Science and Technology, Tehran 1684613114, Iran)

Abstract

This study considers a time-consistent multi-period rolling portfolio optimization issue in the context of a fuzzy situation. Rolling optimization with a risk aversion component attempts to separate the time periods and psychological effects of one’s investment in a mathematical model. Furthermore, a resilient portfolio selection may be attained by taking into account fuzzy scenarios. Credibilistic entropy of fuzzy returns is used to measure portfolio risk because entropy, as a measure of risk, is not dependent on any certain sort of symmetric membership function of stock returns and may be estimated using nonmetric data. Mathematical modeling is performed to compare the Rolling Model (RM) and the Unified Model (UM). Two empirical studies from the Tehran stock market (10 stocks from April 2017 to April 2019) and the global stock market (20 stocks from April 2021 to April 2023) are utilized to illustrate the applicability of the suggested strategy. The findings reveal that RM can limit the risk of the portfolio at each time, but the portfolio’s return is smaller than that of UM. Furthermore, the suggested models outperform the standard deterministic model.

Suggested Citation

  • Pejman Peykani & Mojtaba Nouri & Mir Saman Pishvaee & Camelia Oprean-Stan & Emran Mohammadi, 2023. "Credibilistic Multi-Period Mean-Entropy Rolling Portfolio Optimization Problem Based on Multi-Stage Scenario Tree," Mathematics, MDPI, vol. 11(18), pages 1-23, September.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:18:p:3889-:d:1238491
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    1. Vathana Ly Vath & Mohamed Mnif & Huyên Pham, 2007. "A model of optimal portfolio selection under liquidity risk and price impact," Finance and Stochastics, Springer, vol. 11(1), pages 51-90, January.
    2. Zhenlong Jiang & Ran Ji & Kuo-Chu Chang, 2020. "A Machine Learning Integrated Portfolio Rebalance Framework with Risk-Aversion Adjustment," JRFM, MDPI, vol. 13(7), pages 1-20, July.
    3. Pejman Peykani & Farhad Hosseinzadeh Lotfi & Seyed Jafar Sadjadi & Ali Ebrahimnejad & Emran Mohammadi, 2022. "Fuzzy chance-constrained data envelopment analysis: a structured literature review, current trends, and future directions," Fuzzy Optimization and Decision Making, Springer, vol. 21(2), pages 197-261, June.
    4. Nitin R. Patel & Marti G. Subrahmanyam, 1982. "A Simple Algorithm for Optimal Portfolio Selection with Fixed Transaction Costs," Management Science, INFORMS, vol. 28(3), pages 303-314, March.
    5. Jia Zhai & Manying Bai, 2017. "Uncertain Portfolio Selection with Background Risk and Liquidity Constraint," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-10, January.
    6. Antonio Díaz & Carlos Esparcia, 2021. "Dynamic optimal portfolio choice under time-varying risk aversion," International Economics, CEPII research center, issue 166, pages 1-22.
    7. Gulpinar, Nalan & Rustem, Berc, 2007. "Worst-case robust decisions for multi-period mean-variance portfolio optimization," European Journal of Operational Research, Elsevier, vol. 183(3), pages 981-1000, December.
    8. N. Edirisinghe & E. Patterson, 2007. "Multi-period stochastic portfolio optimization: Block-separable decomposition," Annals of Operations Research, Springer, vol. 152(1), pages 367-394, July.
    9. Eduardo Bered Fernandes Vieira & Tiago Pascoal Filomena, 2020. "Liquidity Constraints for Portfolio Selection Based on Financial Volume," Computational Economics, Springer;Society for Computational Economics, vol. 56(4), pages 1055-1077, December.
    10. Alex Sclip & Alberto Dreassi & Stefano Miani & Andrea Paltrinieri, 2016. "Dynamic correlations and volatility linkages between stocks and sukuk: Evidence from international markets," Review of Financial Economics, John Wiley & Sons, vol. 31(1), pages 34-44, November.
    11. Yuanyuan Zhang & Xiang Li & Sini Guo, 2018. "Portfolio selection problems with Markowitz’s mean–variance framework: a review of literature," Fuzzy Optimization and Decision Making, Springer, vol. 17(2), pages 125-158, June.
    12. Xiao, Helu & Zhou, Zhongbao & Ren, Teng & Liu, Wenbin, 2022. "Estimation of portfolio efficiency in nonconvex settings: A free disposal hull estimator with non-increasing returns to scale," Omega, Elsevier, vol. 111(C).
    13. Zhou, Zhongbao & Gao, Meng & Xiao, Helu & Wang, Rui & Liu, Wenbin, 2021. "Big data and portfolio optimization: A novel approach integrating DEA with multiple data sources," Omega, Elsevier, vol. 104(C).
    14. Ling, Aifan & Sun, Jie & Wang, Meihua, 2020. "Robust multi-period portfolio selection based on downside risk with asymmetrically distributed uncertainty set," European Journal of Operational Research, Elsevier, vol. 285(1), pages 81-95.
    15. Abdelouahed Hamdi & Arezou Karimi & Farshid Mehrdoust & Samir Brahim Belhaouari, 2022. "Portfolio Selection Problem Using CVaR Risk Measures Equipped with DEA, PSO, and ICA Algorithms," Mathematics, MDPI, vol. 10(15), pages 1-26, August.
    16. Amir Hosein Mahmoodi & Seyed Jafar Sadjadi & Soheil Sadi-Nezhad & Roya Soltani & Farzad Movahedi Sobhani, 2020. "Linguistic Z-number weighted averaging operators and their application to portfolio selection problem," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-34, January.
    17. Mulvey, John M. & Rosenbaum, Daniel P. & Shetty, Bala, 1997. "Strategic financial risk management and operations research," European Journal of Operational Research, Elsevier, vol. 97(1), pages 1-16, February.
    18. Najafi, Amir Abbas & Mushakhian, Siamak, 2015. "Multi-stage stochastic mean–semivariance–CVaR portfolio optimization under transaction costs," Applied Mathematics and Computation, Elsevier, vol. 256(C), pages 445-458.
    19. Simonelli, Maria Rosaria, 2005. "Indeterminacy in portfolio selection," European Journal of Operational Research, Elsevier, vol. 163(1), pages 170-176, May.
    20. Pejman Peykani & Emran Mohammadi & Armin Jabbarzadeh & Mohsen Rostamy-Malkhalifeh & Mir Saman Pishvaee, 2020. "A novel two-phase robust portfolio selection and optimization approach under uncertainty: A case study of Tehran stock exchange," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-43, October.
    21. Panos Xidonas & Ralph Steuer & Christis Hassapis, 2020. "Robust portfolio optimization: a categorized bibliographic review," Annals of Operations Research, Springer, vol. 292(1), pages 533-552, September.
    22. Pejman Peykani & Jafar Gheidar-Kheljani & Reza Farzipoor Saen & Emran Mohammadi, 2022. "Generalized robust window data envelopment analysis approach for dynamic performance measurement under uncertain panel data," Operational Research, Springer, vol. 22(5), pages 5529-5567, November.
    23. Hibiki, Norio, 2006. "Multi-period stochastic optimization models for dynamic asset allocation," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 365-390, February.
    24. Ceren Tuncer Şakar & Murat Köksalan, 2013. "A stochastic programming approach to multicriteria portfolio optimization," Journal of Global Optimization, Springer, vol. 57(2), pages 299-314, October.
    25. Shen, Ruijun & Zhang, Shuzhong, 2008. "Robust portfolio selection based on a multi-stage scenario tree," European Journal of Operational Research, Elsevier, vol. 191(3), pages 864-887, December.
    26. Mohebbi, Negin & Najafi, Amir Abbas, 2018. "Credibilistic multi-period portfolio optimization based on scenario tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1302-1316.
    27. Kolm, Petter N. & Tütüncü, Reha & Fabozzi, Frank J., 2014. "60 Years of portfolio optimization: Practical challenges and current trends," European Journal of Operational Research, Elsevier, vol. 234(2), pages 356-371.
    28. Liu, Jia & Chen, Zhiping, 2018. "Time consistent multi-period robust risk measures and portfolio selection models with regime-switching," European Journal of Operational Research, Elsevier, vol. 268(1), pages 373-385.
    29. Yunyun Sui & Jiangshan Hu & Fang Ma, 2020. "A Possibilistic Portfolio Model with Fuzzy Liquidity Constraint," Complexity, Hindawi, vol. 2020, pages 1-10, July.
    30. Sclip, Alex & Dreassi, Alberto & Miani, Stefano & Paltrinieri, Andrea, 2016. "Dynamic correlations and volatility linkages between stocks and sukuk: Evidence from international markets," Review of Financial Economics, Elsevier, vol. 31(C), pages 34-44.
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