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An Analytic Network Process to Support Financial Decision-Making in the Context of Behavioural Finance

Author

Listed:
  • Roberta Martino

    (Department of Mathematics and Physics, University of Campania Luigi Vanvitelli, Viale A. Lincoln, 5, 81100 Caserta, Italy)

  • Viviana Ventre

    (Department of Mathematics and Physics, University of Campania Luigi Vanvitelli, Viale A. Lincoln, 5, 81100 Caserta, Italy)

Abstract

Following the financial crisis of the last decade and the increasing complexity of financial products, the European Union has introduced investor protection tools that require professionals to carry out a client profiling process. The aim is to offer products that are in line with the characteristics of the individual. The classes of variables for comprehensive profiling are obtained by matching the elements proposed by the Markets in Financial Instruments Directive and studies of classical finance. However, behavioural finance studies, which emphasise the importance of behavioural attitudes, are not clearly considered in this structured profiling. The present paper discusses the implementation of an analytic network process to support financial decision-making in a behavioural context, combining regulatory guidance and qualitative and quantitative evidence from the literature. The Kersey Temperament Model is used as the behavioural model to construct the network cluster that incorporates personality into the valuation. Uncertainty management is incorporated through recent studies in the context of intertemporal choice theory. The functionality of the network is verified through a case study, where two alternatives with different characteristics are considered to meet the same investment objective. The present approach proves how the generated structure can provide strong support for financial decision-making.

Suggested Citation

  • Roberta Martino & Viviana Ventre, 2023. "An Analytic Network Process to Support Financial Decision-Making in the Context of Behavioural Finance," Mathematics, MDPI, vol. 11(18), pages 1-30, September.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:18:p:3994-:d:1243840
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    References listed on IDEAS

    as
    1. Viviana Ventre & Roberta Martino, 2022. "Quantification of Aversion to Uncertainty in Intertemporal Choice through Subjective Perception of Time," Mathematics, MDPI, vol. 10(22), pages 1-16, November.
    2. repec:eme:mfppss:v:36:y:2010:i:6:p:474-481 is not listed on IDEAS
    3. Robert J. Shiller, 2003. "From Efficient Markets Theory to Behavioral Finance," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 83-104, Winter.
    4. Anderson, Evan W. & Ghysels, Eric & Juergens, Jennifer L., 2009. "The impact of risk and uncertainty on expected returns," Journal of Financial Economics, Elsevier, vol. 94(2), pages 233-263, November.
    5. Thomas L. Saaty & Luis G. Vargas, 2013. "Decision Making with the Analytic Network Process," International Series in Operations Research and Management Science, Springer, edition 2, number 978-1-4614-7279-7, December.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Kyriaki Tsilika, 2024. "A Mathematica-Based Interface for the Exploration of Inter- and Intra-Regional Financial Flows," Mathematics, MDPI, vol. 12(6), pages 1-15, March.
    2. Rui Ding & Zehua Liu, 2024. "An IT2FS-ANP- and IT2FS-CM-Based Approach for Conducting Safety Risk Assessments of Nuclear Power Plant Building Projects," Mathematics, MDPI, vol. 12(7), pages 1-20, March.
    3. Annamaria Porreca & Viviana Ventre & Roberta Martino & Salvador Cruz Rambaud & Fabrizio Maturo, 2024. "Functional Clustering of Discount Functions for Behavioral Investor Profiling," Papers 2410.16307, arXiv.org.

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