Fuzzy Systems and its Applications

Fuzzy Systems and its Applications

Multi-objective optimization with fuzzy parameters to choose investment portfolio in emerging financial markets (case study: cryptocurrency market)

Document Type : Original Article

Authors
1 Department of Industrial Engineering, Yazd University, P.O. BOX 89195-741, Pejoohesh Street, Safa-ieh, Yazd, Iran
2 Department of Industrial Engineering, Yazd University, P.O. BOX 89195-741, Pejoo
10.22034/jfsa.2025.493869.1251
Abstract
Generally, in a portfolio selection problem, the decision maker simultaneously considers conflicting objectives such as rate of return, liquidity, risk, portfolio size or composition, social responsibility, or profit size. The investor usually intends to make the optimal decision based on several conflicting objectives in emerging financial markets, such as return, risk, and liquidity. in this research, fuzzy goals and its combination with satisfaction functions are formulated in order to obtain a suitable portfolio using ideal values based on the maximum possible deviations. The model can suggest the best portfolio according to the opinion of financial market experts, taking into account the uncertainty of the goals. Finally, the proposed model for choosing a portfolio in emerging financial markets is applied to the cryptocurrencies market and a portfolio with a satisfaction rate of 88.15% is determined. The results denote the excellent performance of proposed model.
Keywords
Subjects

[1]    Aouni, B., Abdelaziz, F.B., Martel, J.M. (2005). “Decision-maker’s preferences modeling in the stochastic goal programming”. European Journal of Operational Research. 162(3), 610–618.
[2]    Aouni, B, Colapinto, C, La Torre, D. (2013). A cardinality constrained stochastic goal programming model with satisfaction function for venture capital investment decision making. Annals of Operations Research, 205 (1), 77–88.
[3]    Arenas-Parra, M. , Bilbao-Terol, A. , Rodriguez-Uria,M.V. (1999).Solution of a possibilistic multi- objective linear programming problem. European Journal of Operational Research, 119 (2), 338–344.
[4]    Arenas-Parra, M, Bilbao-Terol, A, Jiménez, M, Rodriguez-Uria, M. V. (1998). A theory of possibilistic approach to the solution of a fuzzy linear programming. In J. Giron (Ed.), Applied decision analysis (pp. 147–157). Kluwer Academic Publishers.
[5]    Bellman, R. E, Zadeh, L. A. (1970). Decision-making in a fuzzy environment. Management Science, 17 (4), 141–164.
[6]    Ben Abdelaziz, F, Aouni, B, El Fayedh, R. (2007). Multi-objective stochastic programming for portfolio selection. European Journal of Operational Research, 177 (3), 1811–1823.
[7]    Ben Abdelaziz, F, Masmoudi, M. (2014). A multiple objective stochastic portfolio selection problem with random beta. International Transactions in Operational Research, 21, 919–933.
[8]    Calvo, C, Ivora, C, Liern, V. (2016). Fuzzy portfolio selection with non-financial goals: Exploring the efficient frontier. Annals of Operations Research, 245, 31–46.
[9]    Chen, D. S, Batson R. G, Dang Y., (2010). Applied integer programming, John wiley sons, inc., publication.
[10]    Cherif, M. S, Chabchoub, H, Belaid, A. (2008). Quality control system design through the goal programming model and satisfaction functions. European Journal of Operational Research, 186, 1084–1098.
[11]    Cherif, M. S. (2024). A novel behavioral penalty function for interval goal programming with post- optimality analysis. Decision Analytics Journal. 12, 100511.
[12]    Fang F, Ventre C, Basios M, Kanthan L, Martinez-Rego D, Wu F, Li L (2022) Cryptocurrency trading: a comprehensive survey. Financ Innov 8(1):1–59.
[13]    Gladish, B, Jones, D, Tamiz, M, Terol, B. (2007). An interactive three-stage model for mutual funds portfolio selection. Omega, 35 (1), 75–88.
[14]    Gupta, P, Mehlawat, M. K., Saxena, A. (2008). Asset portfolio optimization using fuzzy mathematical programming. Information sciences, 178, 1734–1755.
[15]    Han, Y, Li, P. (2017). An empirical study of chance-constrained portfolio selection model. Procedia Computer Science, 122, 1189–1195.
[16]    Haseli, G., Sheikh, R., Sana, S. S. (2020). Extension of Base-criteria Method based on Fuzzy set theory. International Journal of Applied and Computational Mathematics. 6(2).
[17]    Heilpern, S. (1992). The expected value of a fuzzy number. Fuzzy Sets and Systems, 47 (1), 81–86.
[18]    Lee, S. M, Chesser, D. L. (1980). Goal programming for portfolio selection. The Journal of Portfolio Management, 6 (3),22–26.
 
[19]    Lee, E. S, Li, R. J. (1993). Fuzzy multiple objective programming and compromise programming with Pareto optimum. Fuzzy Sets and Systems, 53 (3), 275–288.
[20]    Lu. H. C, Tsai. S.C. (2024). Generalized robust goal programming model, European J. Oper. Res. (In Press).
[21]    Mansour, N, Rebai, A, Aouni, B. (2007). Portfolio selection through imprecise goal programming model: Integration of the manager’s preferences. Journal of Industrial Engineering International, 3 (5), 1–8.
[22]    Mansour, N., Cherif, M. S., Abdelfattah, W. (2019). Multi-objective imprecise programming for financial portfolio selection with fuzzy returns. Expert systems with applications, 138, 112810.
[23]    Markowitz, H. (1952). Portfolio selection. J Financ 7(1):77–91. https://doi.org/10.1111/j.1540- 6261.1952.tb01525.x.
[24]    Martel, J.-M, Aouni, B. (1998). Diverse imprecise goal programming model formulations. Journal of Global Optimization, 12, 127–138.
[25]    Messaoudi, L, Aouni, B, Rebaï, A. (2017). Fuzzy chance-constrained goal program- ming model for multi-attribute financial portfolio selection. Annals of Operations Research, 251 (2), 193–204.
[26]    Mohseny-Tonekabony. N, Sadjadi. S.J, Mohammadi. E. (2024). Robust, extended goal programming with uncertainty sets: an application to a multi-objective portfolio selection problem leveraging DEA, Ann. Oper. Res.
[27]    Najafabadi. M.M, Magazzino. C, Valente. D, Mirzaei. A, Petrosillo. I. (2023). A new interval meta- goal programming for sustainable planning of agricultural water-land use nexus, Ecol. Modell. 484, 110471.
[28]    Narang, M., Joshi, M.C., Bisht, K., Pal, A. (2022). Stock Portfolio selection using a new decision- making approach based on the integration of fuzzy cocoso with heronian mean operator. Decision Making: Applications in Management and Engineering.5(1), 90-112.
[29]    Narang, M., Joshi, M.C., Pal, A.K. (2021). A hybrid fuzzy COPRAS-base-criterion method for multi-criteria decision making. Soft Computing. 122(2), 315–326.
[30]    Pamučar, D., Žižović, M., Biswas, S., Božanić, D. (2021). A new Logarithm Methodology of Additive Weights (LMAW) for multi-criteria decision-making: Application in logistics, Facta Univer- sitatis, Series: Mechanical Engineering. 19(3), 361-380.
[31]    Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega. 53:49– 57.
[32]    Steuer, R, Qi, Y, Hirschberger, M. (2007). Suitable-portfolio investors, non dominated frontier sensitivity, and the effect of multiple objectives on standard portfolio selection. Annals of Operations Research, 152 (1), 297–317.
 
[33]    Tamiz, M. , Azmi, R. A. (2017). Goal programming with extended factors for portfolio selection. International Transactions in Operational Research, 00 , 1–13 .
[34]    Tamiz, M. , Hasham, R. , Jones, D. (1996). A two staged goal programming model for portfolio selection. Lecture Notes in Economics and Mathematical Systems, 432 , 286–299 .
[35]    Tanaka, H. , Guo, P. , Turksen, I. B. (2000). Portfolio selection based on fuzzy probabilities and possibility distributions. Fuzzy Sets and Systems, 111 , 387–397 .
[36]    Watada, J. (2001). Fuzzy portfolio model for decision making in investment, dynamical aspects in fuzzy decision making 141-162 . Heidelberg: Physica-Verlag .
[37]    Xidonas, P. , Mavrotas, G. , Hassapis, C. , Zopounidis, C. (2017). Robust multi-objective portfolio optimization: A minimax regret approach. European Journal of Op- erational Research, 262 (1), 299–305 .
[38]    Xu M, Chen X, Kou G. (2019). A systematic review of blockchain. Financ Innov. https://doi.org/10.1186/s40854-019-0147-z.
[39]    Zhao JL, Fan S, Yan J (2016) Overview of business innovations and research op- portunities in blockchain and introduction to the special issue. Financ Innov 2(1):1–7. https://doi.org/10.1186/s40854-016-0049-2
[40]    Zhou L, Zhang L, Zhao Y, Zheng R, Song K. (2021). A scientometric review of blockchain research. IseB 19(3):757–787.
Volume 8, Issue 1 - Serial Number 16
Open Access Statement
June 2025
Pages 61-91

  • Receive Date 14 December 2024
  • Revise Date 12 May 2025
  • Accept Date 14 June 2025