IDEAS home Printed from https://ideas.repec.org/p/chf/rpseri/rp1609.html
   My bibliography  Save this paper

Quantum Decision Theory in Simple Risky Choices

Author

Listed:
  • Maroussia Favre

    (ETH Zürich - Department of Management, Technology, and Economics (D-MTEC))

  • Amrei Wittwer

    (University of Zurich - Collegium Helveticum)

  • Hans Rudolf Heinimann

    (ETH Zurich)

  • Vyacheslav I. Yukalov

    (Joint Institute for Nuclear Research; D-MTEC, ETH Zurich)

  • Didier Sornette

    (Swiss Finance Institute; ETH Zürich - Department of Management, Technology, and Economics (D-MTEC))

Abstract

Quantum decision theory (QDT) is a novel theory of decision making based on the mathematics of Hilbert spaces, a framework known in physics for its application to quantum mechanics. This framework formalizes the concept of uncertainty and other effects that are particularly manifest in cognitive processes, which makes it well suited for the study of decision making. QDT describes a decision maker's choice as a stochastic event occurring with a probability that is the sum of an objective utility factor and a subjective attraction factor. This article offers a practical guide to researchers who are interested in applying QDT to a data set of binary lotteries in the domain of gains. We find that our results are in good agreement with the quarter law, a quantitative prediction of QDT. We examine gender differences in our sample in order to illustrate how QDT can be used to differentiate between different groups. We find that women in our sample are on average more risk-averse than men, but stress that our sample is too small to generalize this result to the population outside our sample.

Suggested Citation

  • Maroussia Favre & Amrei Wittwer & Hans Rudolf Heinimann & Vyacheslav I. Yukalov & Didier Sornette, 2016. "Quantum Decision Theory in Simple Risky Choices," Swiss Finance Institute Research Paper Series 16-09, Swiss Finance Institute.
  • Handle: RePEc:chf:rpseri:rp1609
    as

    Download full text from publisher

    File URL: http://ssrn.com/abstract=2731774
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fellnhofer, Katharina & Sornette, Didier, 2022. "Embracing The Intuitive-Analytical Paradox? How Intuitive And Analytical Decision-Making Drive Paradoxes In Simple And Complex Environments," OSF Preprints evjd6, Center for Open Science.
    2. Ferro, Giuseppe M. & Kovalenko, Tatyana & Sornette, Didier, 2021. "Quantum decision theory augments rank-dependent expected utility and Cumulative Prospect Theory," Journal of Economic Psychology, Elsevier, vol. 86(C).
    3. Haven, Emmanuel & Khrennikova, Polina, 2018. "A quantum-probabilistic paradigm: Non-consequential reasoning and state dependence in investment choice," Journal of Mathematical Economics, Elsevier, vol. 78(C), pages 186-197.
    4. Yukalov, V.I. & Yukalova, E.P. & Sornette, D., 2022. "Role of collective information in networks of quantum operating agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).

    More about this item

    Keywords

    decision making; quantum decision theory; risk; uncertainty; how-to guide;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:chf:rpseri:rp1609. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ridima Mittal (email available below). General contact details of provider: https://edirc.repec.org/data/fameech.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.