Strict Uncertainty Analysis with Fuzzy Payoffs and its Application to Portfolio Selection

Salas-Molina, Francisco; Dutta, Bapi; Martínez, Luis

doi:10.15388/26-INFOR625

Informatica

Strict Uncertainty Analysis with Fuzzy Payoffs and its Application to Portfolio Selection

Francisco Salas-Molina

Bapi Dutta Luis Martínez

https://doi.org/10.15388/26-INFOR625

Pub. online: 27 March 2026 Type: Research Article

Open Access

Received
1 June 2025

Accepted
1 March 2026

Published
27 March 2026

Abstract

Decision-making under strict uncertainty involves evaluating a set of alternatives without knowledge of the probability of scenarios using crisp evaluations. Our work reformulates traditional decision rules to a fuzzy environment, retaining the interpretability of classical principles while incorporating imprecision. Our methodological proposal provides a unified, flexible, and mathematically consistent framework for decision-making under imprecise payoffs. We adapt a total ordering mechanism for trapezoidal fuzzy numbers and admissible interval orders. Our application case study to portfolio selection under fuzzy strict uncertainty demonstrates how the proposed fuzzy generalization can handle financial imprecision and investor risk attitudes through ranking functions.

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Biographies

Salas-Molina Francisco

https://orcid.org/0000-0002-1168-7931

frasamo@upv.es

F. Salas-Molina is a professor at the Technical University of Valencia within the Department of Economics and Social Sciences. He obtained his PhD in industrial engineering and finance from the Technical University of Valencia in 2017. His research interests include artificial intelligence, operations research, multiple-criteria decision-making, and their applications to economic and financial problems.

Dutta Bapi

bdutta@ujaen.es

B. Dutta is a Ramón y Cajal researcher at the University of Jaén. His research focuses on decision-making, soft computing, simulation, optimization, and machine learning, with particular emphasis on developing advanced computational models and methodologies to address complex real-world problems.

Martínez Luis

martin@ujaen.es

L. Martínez (senior member, IEEE) is a full professor with the Department of Computer Science, University of Jaén, Spain. He is also a visiting professor with the University of Technology Sydney, the University of Portsmouth (Isambard Kingdom Brunel Fellowship Scheme), and Wuhan University of Technology (Chutian Scholar). He has been the leading researcher in 16 research and development projects, published more than 190 papers in journals indexed by SCI, and made more than 200 contributions to international/national conferences related to his areas. His research interests include multiple-criteria decision-making, fuzzy logic-based systems, computing with words, and recommender systems. He is an IFSA Fellow, in 2021 and a senior member of European Society for Fuzzy Logic and Technology. He was a Recipient of the IEEE Transactions on Fuzzy Systems Outstanding Paper Award, in 2008 and 2012 (bestowed in 2011 and 2015, respectively). He was classified as a Highly Cited Researcher 2017–2021 in computer sciences. He is the co-editor-in-chief of International Journal of Computational Intelligence Systems and an associate editor of Information Sciences, Knowledge-Based Systems, and Information Fusion.

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Keywords

quantitative finance fuzzy intervals decision rules moderate pessimism portfolio selection

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