A novel entropy of intuitionistic fuzzy sets based on similarity and its application in finance

Article type: Research Article

Authors: Tran, Duc Quynh^{a; *} | Nguyen, Xuan Thao^b | Nguyen, Doan Dong^a | Nguyen, Quang Thuan^a

Affiliations: [a] International School, Vietnam National University, Hanoi | [b] Faculty of Information Technology, Vietnam National University of Agriculture

Correspondence: [*] Corresponding author. Duc Quynh Tran, International School, Vietnam National University, Hanoi. E-mail: ducquynh@vnu.edu.vn.

Abstract: In this paper, we propose a new formula for the entropy based on similarity measures of intuitionistic fuzzy sets (IFS). The contribution of this work is the proof that the new formula satisfies all the conditions of entropy. The experimentation on some examples shows that the new entropy is useful. Besides, we use the new entropy and similarity measures to design an algorithm for ranking assets in stock markets. The numerical results on 5 benchmark data sets were reported. It points out that the entropy and the similarity measures of IFS may provide an alternative tool for solving portfolio selection problems.

Keywords: Intuitionistic fuzzy set, similarity measures, stock markets, assets ranking, entropy

DOI: 10.3233/JIFS-211563

Journal: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 4, pp. 3899-3909, 2022