[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/31715.html
   My bibliography  Save this paper

What is the actual shape of perception utility?

Author

Listed:
  • Kontek, Krzysztof
Abstract
Cumulative Prospect Theory (Kahneman, Tversky, 1979, 1992) holds that the value function is described using a power function, and is concave for gains and convex for losses. These postulates are questioned on the basis of recently reported experiments, paradoxes (gain-loss separability violation), and brain activity research. This paper puts forward the hypothesis that perception utility is generally logarithmic in shape for both gains and losses, and only happens to be convex for losses when gains are not present in the problem context. This leads to a different evaluation of mixed prospects than is the case with Prospect Theory: losses are evaluated using a concave, rather than a convex, utility function. In this context, loss aversion appears to be nothing more than the result of applying a logarithmic utility function over the entire outcome domain. Importantly, the hypothesis enables a link to be established between perception utility and Portfo-lio Theory (Markowitz, 1952A). This is not possible in the case of the Prospect Theory value function due its shape at the origin.

Suggested Citation

  • Kontek, Krzysztof, 2011. "What is the actual shape of perception utility?," MPRA Paper 31715, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:31715
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/31715/1/MPRA_paper_31715.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mohammed Abdellaoui & Han Bleichrodt & Olivier L’Haridon, 2008. "A tractable method to measure utility and loss aversion under prospect theory," Journal of Risk and Uncertainty, Springer, vol. 36(3), pages 245-266, June.
    2. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    3. Amos Tversky & Daniel Kahneman, 1991. "Loss Aversion in Riskless Choice: A Reference-Dependent Model," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(4), pages 1039-1061.
    4. Harry Markowitz, 1952. "The Utility of Wealth," Journal of Political Economy, University of Chicago Press, vol. 60(2), pages 151-151.
    5. Michael H. Birnbaum & Jeffrey P. Bahra, 2007. "Gain-Loss Separability and Coalescing in Risky Decision Making," Management Science, INFORMS, vol. 53(6), pages 1016-1028, June.
    6. George Wu & Alex B. Markle, 2008. "An Empirical Test of Gain-Loss Separability in Prospect Theory," Management Science, INFORMS, vol. 54(7), pages 1322-1335, July.
    7. Helga Fehr-Duda & Manuele Gennaro & Renate Schubert, 2006. "Gender, Financial Risk, and Probability Weights," Theory and Decision, Springer, vol. 60(2), pages 283-313, May.
    8. John W. Payne & Dan J. Laughhunn & Roy Crum, 1980. "Translation of Gambles and Aspiration Level Effects in Risky Choice Behavior," Management Science, INFORMS, vol. 26(10), pages 1039-1060, October.
    9. Mohammed Abdellaoui & Han Bleichrodt & Corina Paraschiv, 2007. "Loss Aversion Under Prospect Theory: A Parameter-Free Measurement," Management Science, INFORMS, vol. 53(10), pages 1659-1674, October.
    10. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    11. Nathalie Etchart-Vincent, 2009. "The shape of the utility function under risk in the loss domain and the "ruinous losses" hypothesis: some experimental results," Economics Bulletin, AccessEcon, vol. 29(2), pages 1393-1402.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Peter Brooks & Simon Peters & Horst Zank, 2014. "Risk behavior for gain, loss, and mixed prospects," Theory and Decision, Springer, vol. 77(2), pages 153-182, August.
    2. Kpegli, Yao Thibaut & Corgnet, Brice & Zylbersztejn, Adam, 2023. "All at once! A comprehensive and tractable semi-parametric method to elicit prospect theory components," Journal of Mathematical Economics, Elsevier, vol. 104(C).
    3. Eyal Ert & Ido Erev, 2010. "On the Descriptive Value of Loss Aversion in Decisions under Risk," Harvard Business School Working Papers 10-056, Harvard Business School.
    4. George Wu & Alex B. Markle, 2008. "An Empirical Test of Gain-Loss Separability in Prospect Theory," Management Science, INFORMS, vol. 54(7), pages 1322-1335, July.
    5. Simon Gächter & Eric J. Johnson & Andreas Herrmann, 2022. "Individual-level loss aversion in riskless and risky choices," Theory and Decision, Springer, vol. 92(3), pages 599-624, April.
    6. Attema, Arthur E. & Brouwer, Werner B.F. & l’Haridon, Olivier, 2013. "Prospect theory in the health domain: A quantitative assessment," Journal of Health Economics, Elsevier, vol. 32(6), pages 1057-1065.
    7. Ranoua Bouchouicha & Lachlan Deer & Ashraf Galal Eid & Peter McGee & Daniel Schoch & Hrvoje Stojic & Jolanda Ygosse-Battisti & Ferdinand M. Vieider, 2019. "Gender effects for loss aversion: Yes, no, maybe?," Journal of Risk and Uncertainty, Springer, vol. 59(2), pages 171-184, October.
    8. Han Bleichrodt & Ulrich Schmidt & Horst Zank, 2009. "Additive Utility in Prospect Theory," Management Science, INFORMS, vol. 55(5), pages 863-873, May.
    9. Géraldine Bocquého & Julien Jacob & Marielle Brunette, 2020. "Prospect theory in experiments : behaviour in loss domain and framing effects," Working Papers hal-02987294, HAL.
    10. Adam Booij & Bernard Praag & Gijs Kuilen, 2010. "A parametric analysis of prospect theory’s functionals for the general population," Theory and Decision, Springer, vol. 68(1), pages 115-148, February.
    11. Philip Bromiley, 2009. "A Prospect Theory Model of Resource Allocation," Decision Analysis, INFORMS, vol. 6(3), pages 124-138, September.
    12. Charles-Cadogan, G., 2016. "Expected utility theory and inner and outer measures of loss aversion," Journal of Mathematical Economics, Elsevier, vol. 63(C), pages 10-20.
    13. Alex Markle & George Wu & Rebecca White & Aaron Sackett, 2018. "Goals as reference points in marathon running: A novel test of reference dependence," Journal of Risk and Uncertainty, Springer, vol. 56(1), pages 19-50, February.
    14. Géraldine Bocquého & Julien Jacob & Marielle Brunette, 2023. "Prospect theory in multiple price list experiments: further insights on behaviour in the loss domain," Theory and Decision, Springer, vol. 94(4), pages 593-636, May.
    15. Horst Zank, 2010. "On probabilities and loss aversion," Theory and Decision, Springer, vol. 68(3), pages 243-261, March.
    16. Simon Gaechter & Eric Johnson & Andreas Herrmann, 2007. "Individual-Level Loss Aversion In Riskless And Risky Choices," Discussion Papers 2007-02, The Centre for Decision Research and Experimental Economics, School of Economics, University of Nottingham.
    17. Mohammed Abdellaoui & Emmanuel Kemel, 2014. "Eliciting Prospect Theory When Consequences Are Measured in Time Units: “Time Is Not Money”," Management Science, INFORMS, vol. 60(7), pages 1844-1859, July.
    18. Jakusch, Sven Thorsten & Meyer, Steffen & Hackethal, Andreas, 2019. "Taming models of prospect theory in the wild? Estimation of Vlcek and Hens (2011)," SAFE Working Paper Series 146, Leibniz Institute for Financial Research SAFE, revised 2019.
    19. Ulrich Schmidt & Horst Zank, 2012. "A genuine foundation for prospect theory," Journal of Risk and Uncertainty, Springer, vol. 45(2), pages 97-113, October.
    20. Peters, Hans, 2012. "A preference foundation for constant loss aversion," Journal of Mathematical Economics, Elsevier, vol. 48(1), pages 21-25.

    More about this item

    Keywords

    Prospect Theory; value function; perception utility; loss aversion; gain-loss separability violation; neuroscience; Portfolio Theory; Decision Utility Theory.;
    All these keywords.

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • D87 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Neuroeconomics
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

    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:pra:mprapa:31715. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.