Agile Decision-Making in Unstable Markets: A Soft Set Paradigm with Temporal Weighting

Mustafa Burç Kandemir

doi:10.32323/ujma.1716683

Agile Decision-Making in Unstable Markets: A Soft Set Paradigm with Temporal Weighting

Abstract

Navigating volatile financial markets requires decision-making frameworks that synergize analytical rigor with real-time adaptability. Traditional models, reliant on static criteria and fixed weights, falter in dynamically evolving economic landscapes where the relevance of parameters like risk, liquidity, and inflation sensitivity shifts rapidly. This study bridges this critical gap by introducing a novel decision-making model founded on soft set theory and augmented with a temporal weighting mechanism. The proposed framework incorporates a time-dependent decision core, $A(t)$, which captures the set of relevant alternatives in real-time. This dynamic core drives the construction of temporal equivalence relations, $R(t)$, that cluster parameters based on their current influence, and enables the computation of dynamic, support-based weights, $w(t,p)$. These elements culminate in a responsive scoring function, $S(u,t)$, that adapts to fluctuating market conditions. The model is rigorously validated through a comparative application to investment decision-making, demonstrating its superior ability to recalibrate parameter importance and optimize choices during regime shifts—such as from economic stability to inflationary crisis—compared to static soft set and fuzzy TOPSIS benchmarks. Theoretical analyses confirm the model's stability, computational efficiency, and robustness. Our approach thus offers a powerful, interpretable, and mathematically sound tool for agile financial decision support in complex, unstable environments.

Keywords

Financial decision-making, Investment strategy, Market volatility, Soft set theory, Temporal weighting

References

[1] P. Anand, Foundations of Rational Choice under Risk, Oxford University Press, Oxford, 1993.
[2] R. E. Bellman, L. A. Zadeh, Decision making in a fuzzy environment, Manag. Sci., 17(4) (1970), 141–164. https://doi.org/10.1287/mnsc.17.4.B141
[3] S. Greco, B. Matarazzo, R. Slowinski, Rough sets theory for multi-criteria decision analysis, Eur. J. Oper. Res., 129(1) (2001), 1–47. https://doi.org/10.1016/S0377-2217(00)00167-3
[4] D. W. North, A tutorial introduction to decision theory, IEEE Trans. Syst. Sci. Cybernet., 4(3) (1968), 200–210. https://doi.org/10.1109/TSSC.1968.300114
[5] M. Peterson, An Introduction to Decision Theory, Cambridge University Press, New York, 2009.
[6] H. J. Zimmermann, Fuzzy Set Theory and Its Applications, Springer Dordrecht, New York, 1996.
[7] D. A. Molodtsov, Soft set theory–First results, Comput. Math. Appl., 37(4-5) (1999), 19–31. https://doi.org/10.1016/S0898-1221(99)00056-5
[8] M. I. Ali, F. Feng, X. Y. Liu, W. K. Min, M. Shabir, On some new operations in soft set theory, Comput. Math. Appl., 57(9) (2009), 1547–1553. https://doi.org/10.1016/j.camwa.2008.11.009
[9] P. K. Maji, A. R. Roy, R. Biswas, An application of soft sets in a decision making problem, Comput. Math. Appl., 44(8-9) (2002), 1077–1083. https://doi.org/10.1016/S0898-1221(02)00216-X
[10] P. K. Maji, R. Biswas, A. R. Roy, Soft set theory, Comput. Math. Appl., 45(4-5) (2003), 555–562. https://doi.org/10.1016/S0898-1221(03)00016-6

[11] D. A. Molodtsov, Equivalence and correct operations for soft sets, Int. Rob. Auto. J., 4(1) (2018), 18–21. https://doi.org/10.15406/iratj.2018.04.00086
[12] G. Ali, H. Alolaiyan, D. Pamucar, M. Asif, N. Lateef, A novel MADM framework under q-rung orthopair fuzzy bipolar soft sets, Mathematics, 9(17) (2021), Article ID 2163. https://doi.org/10.3390/math9172163
[13] M. Ali, A. Kılıc¸man, On interval-valued fuzzy soft preordered sets and associated applications in decision-making, Mathematics, 9(23) (2021), Article ID 3142. https://doi.org/10.3390/math9233142
[14] S. Ali, M. Kousar, Q. Xin, D. Pamucar, M.S. Hameed, R. Fayyaz, Belief and possibility belief interval-valued N-soft set and their applications in multi-attribute decision-making problems, Entropy, 23(11) (2021), Article ID 1498. https://doi.org/10.3390/e23111498
[15] Z. Ali, T. Mahmood, M. Aslam, R. Chinram, Another view of complex intuitionistic fuzzy soft sets based on prioritized aggregation operators and their applications to multiattribute decision making, Mathematics, 9(16) (2021), Article ID 1922. https://doi.org/10.3390/math9161922
[16] N. Çağman, S. Karataş, Intuitionistic fuzzy soft set theory and its decision making, J. Intell. Fuzzy Syst., 24(4) (2013), 829–836. https://doi.org/10.3233/IFS-2012-0601
[17] A. Z. Khameneh, A. Kılıçman, A. R. Salleh, An adjustable approach to multi-criteria group decision-making based on a preference relationship under fuzzy soft information, Int. J. Fuzzy Syst., 19 (2017), 1840–1865. https://doi.org/10.1007/s40815-016-0280-z
[18] O. Dalkılıç, A novel approach to soft set theory in decision making under uncertainty, Int. J. Comput. Math., 98(10) (2021), 1935–1945. https://doi.org/10.1080/00207160.2020.1868445
[19] A. O. Atagün, H. Kamacı, O. Oktay, Reduced soft matrices and generalized products with applications in decision making, Neural Comput. Appl., 29 (2018), 445–456. https://doi.org/10.1007/s00521-016-2542-y
[20] N. Çağman, S. Enginoğlu, Soft matrix theory and its decision making, Comput. Math. Appl., 59(10) (2010), 3308–3314. https://doi.org/10.1016/j.camwa.2010.03.015
[21] H. Kamacı, A. O. Atagün, A. Sönmezoğlu, Row-products of soft matrices with applications in multiple-disjoint decision making, Appl. Soft Comput., 62 (2018), 892–914. https://doi.org/10.1016/j.asoc.2017.09.024
[22] J. Kannan, V. Jayakumar, M. Riaz, D. Pamucar, N. S. Shanmugam, V. Simic, Exploring land subsidence factors with linear Diophantine multi-fuzzy soft information: A hybrid CRITIC-TOPSIS framework, Nat. Hazards, 121 (2025), 17991–18031. https://doi.org/10.1007/s11069-025-07502-x
[23] M. Riaz, S. Tariq, Z. A Khan, S. H. Zolfani, D. Pamucar, Synergy of Machine Learning and IoT for Healthcare: Enhancing Sustainable Societies in Uncertain Environments, International Journal of Information Technology & Decision Making, (2025) Preprint. https://doi.org/10.1142/S021962202550083X
[24] M. B. Kandemir, Monotonic soft sets and its applications, Ann. Fuzzy Math. Inform., 12(2) (2016), 295–307.
[25] M. B. Kandemir, The concept of $\sigma$-algebraic soft set, Soft Comput., 22 (2018), 4353–4360. https://doi.org/10.1007/s00500-017-2901-3
[26] M. B. Kandemir, Some notes on $\sigma$-algebraic soft sets, An. Univ. Craiova Ser. Mat. Inform., 47(2) (2020), 387–396.
[27] K. Taşköprü, E. Karaköse, A soft set approach to relations and its application to decision making, Math. Sci. Appl. E-Notes, 11(1) (2023), 1–13. https://doi.org/10.36753/mathenot.1172408
[28] W. Xu, Z. Xiao, X. Dang, D. Yang, X. Yang, Financial ratio selection for business failure prediction using soft set theory, Knowl.-Based Syst., 63 (2014), 59–67. https://doi.org/10.1016/j.knosys.2014.03.007
[29] C. L. Hwang, K. Yoon, Multiple Attribute Decision Making: Methods and Applications, Springer-Verlag, Berlin, 1981.
[30] C. T. Chen, Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets Syst., 114(1) (2000), 1–9. https://doi.org/10.1016/S0165-0114(97)00377-1

Details

Primary Language

English

Subjects

Soft Computing, Risk Analysis

Journal Section

Research Article

Authors

Mustafa Burç Kandemir ^*
0000-0002-0159-5670
Türkiye

Early Pub Date

January 12, 2026

Publication Date

January 12, 2026

Submission Date

June 10, 2025

Acceptance Date

December 19, 2025

Published in Issue

Year 2026 Volume: 9 Number: 1

DOI

https://doi.org/10.32323/ujma.1716683

IZ

https://izlik.org/JA29HG27XX

APA

Kandemir, M. B. (2026). Agile Decision-Making in Unstable Markets: A Soft Set Paradigm with Temporal Weighting. Universal Journal of Mathematics and Applications, 9(1), 32-43. https://doi.org/10.32323/ujma.1716683

AMA

1.Kandemir MB. Agile Decision-Making in Unstable Markets: A Soft Set Paradigm with Temporal Weighting. Univ. J. Math. Appl. 2026;9(1):32-43. doi:10.32323/ujma.1716683

Chicago

Kandemir, Mustafa Burç. 2026. “Agile Decision-Making in Unstable Markets: A Soft Set Paradigm With Temporal Weighting”. Universal Journal of Mathematics and Applications 9 (1): 32-43. https://doi.org/10.32323/ujma.1716683.

EndNote

Kandemir MB (March 1, 2026) Agile Decision-Making in Unstable Markets: A Soft Set Paradigm with Temporal Weighting. Universal Journal of Mathematics and Applications 9 1 32–43.

IEEE

[1]M. B. Kandemir, “Agile Decision-Making in Unstable Markets: A Soft Set Paradigm with Temporal Weighting”, Univ. J. Math. Appl., vol. 9, no. 1, pp. 32–43, Mar. 2026, doi: 10.32323/ujma.1716683.

ISNAD

Kandemir, Mustafa Burç. “Agile Decision-Making in Unstable Markets: A Soft Set Paradigm With Temporal Weighting”. Universal Journal of Mathematics and Applications 9/1 (March 1, 2026): 32-43. https://doi.org/10.32323/ujma.1716683.

JAMA

1.Kandemir MB. Agile Decision-Making in Unstable Markets: A Soft Set Paradigm with Temporal Weighting. Univ. J. Math. Appl. 2026;9:32–43.

MLA

Kandemir, Mustafa Burç. “Agile Decision-Making in Unstable Markets: A Soft Set Paradigm With Temporal Weighting”. Universal Journal of Mathematics and Applications, vol. 9, no. 1, Mar. 2026, pp. 32-43, doi:10.32323/ujma.1716683.

Vancouver

1.Mustafa Burç Kandemir. Agile Decision-Making in Unstable Markets: A Soft Set Paradigm with Temporal Weighting. Univ. J. Math. Appl. 2026 Mar. 1;9(1):32-43. doi:10.32323/ujma.1716683