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Multicriteria Decision Aid/Analysis in Finance

In: Multiple Criteria Decision Analysis

Author

Listed:
  • Jaap Spronk

    (Erasmus University Rotterdam)

  • Ralph E. Steuer

    (University of Georgia)

  • Constantin Zopounidis

    (Technical University of Crete
    Audencia Nantes School of Management)

Abstract

Over the past decades the complexity of financial decisions has increased rapidly, thus highlighting the importance of developing and implementing sophisticated and efficient quantitative analysis techniques for supporting and aiding financial decision making. Multicriteria decision aid (MCDA), an advanced branch of operations research, provides financial decision makers and analysts with a wide range of methodologies well-suited for the complexity of modern financial decision making. The aim of this chapter is to provide an in-depth presentation of the contributions of MCDA in finance focusing on the methods used, applications, computation, and directions for future research.

Suggested Citation

  • Jaap Spronk & Ralph E. Steuer & Constantin Zopounidis, 2016. "Multicriteria Decision Aid/Analysis in Finance," International Series in Operations Research & Management Science, in: Salvatore Greco & Matthias Ehrgott & José Rui Figueira (ed.), Multiple Criteria Decision Analysis, edition 2, chapter 0, pages 1011-1065, Springer.
    • Handle: RePEc:spr:isochp:978-1-4939-3094-4_24
    DOI: 10.1007/978-1-4939-3094-4_24
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    Cited by:

    1. Wątróbski, Jarosław & Bączkiewicz, Aleksandra & Sałabun, Wojciech, 2022. "New multi-criteria method for evaluation of sustainable RES management," Applied Energy, Elsevier, vol. 324(C).
    2. Garcia-Bernabeu, Ana & Hilario-Caballero, Adolfo & Tardella, Fabio & Pla-Santamaria, David, 2024. "ESG integration in portfolio selection: A robust preference-based multicriteria approach," Operations Research Perspectives, Elsevier, vol. 12(C).
    3. Doumpos, Michalis & Zopounidis, Constantin & Gounopoulos, Dimitrios & Platanakis, Emmanouil & Zhang, Wenke, 2023. "Operational research and artificial intelligence methods in banking," European Journal of Operational Research, Elsevier, vol. 306(1), pages 1-16.

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