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A Fuzzy Entropy-Based Group Consensus Measure for Financial Investments

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  • József Dombi

    (Institute of Informatics, University of Szeged, 6720 Szeged, Hungary
    HUN-REN SZTE Research Group on Artificial Intelligence, 6720 Szeged, Hungary)

  • Jenő Fáró

    (Faculty of Economics, ELTE Eötvös Loránd University, 1088 Budapest, Hungary)

  • Tamás Jónás

    (Faculty of Economics, ELTE Eötvös Loránd University, 1088 Budapest, Hungary)

Abstract

This study presents a novel, fuzzy entropy-based approach to the measurement of consensus in group decision making. Here, the basic assumption is that the decision inputs are the ‘yes’ or ‘no’ votes of group members on a financial investment that has a particular expected rate of return. In this paper, using a class of fuzzy entropies, a novel consensus measure satisfying reasonable requirements is introduced for a case where the decision inputs are dichotomous variables. It is also shown here that some existing consensus measures are just special cases of the proposed fuzzy entropy-based consensus measure when the input variables are dichotomous. Next, the so-called group consensus map for financial investments is presented. It is demonstrated that this construction can be used to characterize the level of consensus among the members of a group concerning financial investments as a function of the expected rate of return. Moreover, it is described how a consensus map can be constructed from empirical data and how this map is connected with behavioral economics.

Suggested Citation

  • József Dombi & Jenő Fáró & Tamás Jónás, 2023. "A Fuzzy Entropy-Based Group Consensus Measure for Financial Investments," Mathematics, MDPI, vol. 12(1), pages 1-18, December.
    • Handle: RePEc:gam:jmathe:v:12:y:2023:i:1:p:4-:d:1302949
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    References listed on IDEAS

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    4. Gong, Zaiwu & Guo, Weiwei & Słowiński, Roman, 2021. "Transaction and interaction behavior-based consensus model and its application to optimal carbon emission reduction," Omega, Elsevier, vol. 104(C).
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