IDEAS home Printed from https://ideas.repec.org/a/bla/acctfi/v62y2022i1p645-665.html

Loss aversion and high stakes

Author

Listed:
  • Stephen Easton
  • Sean Pinder

Abstract

Following Kahneman and Tversky, studies such as those by Haigh and List, Ert and Erev and Mukherjee et al. find that loss aversion increases as stake increases. This study extends the 2011 work of Berger and Pope by analysing over 68,000 US professional basketball games played from the initial National Basketball Association (NBA) season in 1946/1947 to the 2018/2019 season, and over 69,000 National Collegiate Athletic Association (NCAA) games played from the 2007/2008 season to the 2018/2019 season. We posit that, a priori, stakes, and therefore loss aversion, will be greater for NBA teams than for NCAA teams, and higher for home teams than for away teams. Further, loss aversion is expected to be greater for favourites, that is, teams that are expected to win. We model outcomes using a digital call option. This model allows for necessary non‐linearity in the relation between halftime score and winning percentage. It also provides an analysis for which the result for home (favourite) teams is not simply the converse of that for away (underdog) teams. We find evidence of better‐than‐expected performance for NBA home teams that are behind by up to four points, and for favourites that are behind by between two and seven points. We find no evidence of this effect with respect to NBA away teams, NBA underdogs, nor for NCAA teams – whether home or away. Our results suggest that loss aversion is apparent when stakes are high.

Suggested Citation

  • Stephen Easton & Sean Pinder, 2022. "Loss aversion and high stakes," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(1), pages 645-665, March.
  • Handle: RePEc:bla:acctfi:v:62:y:2022:i:1:p:645-665
    DOI: 10.1111/acfi.12802
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/acfi.12802
    Download Restriction: no

    File URL: https://libkey.io/10.1111/acfi.12802?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Michael S. Haigh & John A. List, 2005. "Do Professional Traders Exhibit Myopic Loss Aversion? An Experimental Analysis," Journal of Finance, American Finance Association, vol. 60(1), pages 523-534, February.
    2. Sumitava Mukherjee & Arvind Sahay & V. S. Chandrasekhar Pammi & Narayanan Srinivasan, 2017. "Is loss-aversion magnitude-dependent? Measuring prospective affective judgments regarding gains and losses," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 12(1), pages 81-89, January.
    3. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    4. David S. Lee & Thomas Lemieux, 2010. "Regression Discontinuity Designs in Economics," Journal of Economic Literature, American Economic Association, vol. 48(2), pages 281-355, June.
    5. 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.
    6. Eyal Ert & Ido Erev, 2013. "On the descriptive value of loss aversion in decisions under risk: Six clarifications," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 8(3), pages 214-235, May.
    7. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
    8. Ran Kivetz & Oleg Urminsky & Yuhuang Zheng, 2006. "The Goal-Gradient Hypothesis Resurrected: Purchase Acceleration, Illusionary Goal Progress, and Customer Retention," Natural Field Experiments 00658, The Field Experiments Website.
    9. Jonah Berger & Devin Pope, 2011. "Can Losing Lead to Winning?," Management Science, INFORMS, vol. 57(5), pages 817-827, May.
    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. Jonah Berger & Devin Pope, 2011. "Can Losing Lead to Winning?," Management Science, INFORMS, vol. 57(5), pages 817-827, May.
    2. Shang, Xuesong & Duan, Hebing & Lu, Jingyi, 2021. "Gambling versus investment: Lay theory and loss aversion," Journal of Economic Psychology, Elsevier, vol. 84(C).
    3. Reio Tanji, 2021. "Reference Dependence and Monetary Incentives: Evidence from Major League Baseball," Discussion Papers in Economics and Business 20-23, Osaka University, Graduate School of Economics.
    4. van Dolder, Dennie & Vandenbroucke, Jurgen, 2024. "Behavioral risk profiling: Measuring loss aversion of individual investors," Journal of Banking & Finance, Elsevier, vol. 168(C).
    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. Meier, Pascal Flurin & Flepp, Raphael & Franck, Egon, 2025. "Expectational reference points and belief formation: Field evidence from financial analysts," Journal of Economic Behavior & Organization, Elsevier, vol. 229(C).
    7. Puerta, Inmaculada R. & Pinto, José Luis, 2025. "Can reference-dependent loss aversion explain choice behaviour?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 117(C).
    8. Walasek, Lukasz & Mullett, Timothy L. & Stewart, Neil, 2024. "A meta-analysis of loss aversion in risky contexts," Journal of Economic Psychology, Elsevier, vol. 103(C).
    9. Gerlinde Fellner & Matthias Sutter, 2009. "Causes, Consequences, and Cures of Myopic Loss Aversion - An Experimental Investigation," Economic Journal, Royal Economic Society, vol. 119(537), pages 900-916, April.
    10. Toritseju Begho & Kelvin Balcombe, 2023. "Attitudes to Risk and Uncertainty: New Insights From an Experiment Using Interval Prospects," SAGE Open, , vol. 13(3), pages 21582440231, July.
    11. Lovric, M. & Kaymak, U. & Spronk, J., 2008. "A Conceptual Model of Investor Behavior," ERIM Report Series Research in Management ERS-2008-030-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    12. Chen, Yanyan & Mandler, Timo & Meyer-Waarden, Lars, 2021. "Three decades of research on loyalty programs: A literature review and future research agenda," Journal of Business Research, Elsevier, vol. 124(C), pages 179-197.
    13. Schmidt, Ulrich & Friedl, Andreas & Lima de Miranda, Katharina, 2015. "Social comparison and gender differences in risk taking," Kiel Working Papers 2011, Kiel Institute for the World Economy.
    14. Thomas Epper & Helga Fehr-Duda, 2012. "The missing link: unifying risk taking and time discounting," ECON - Working Papers 096, Department of Economics - University of Zurich, revised Oct 2018.
    15. Stefano DellaVigna, 2009. "Psychology and Economics: Evidence from the Field," Journal of Economic Literature, American Economic Association, vol. 47(2), pages 315-372, June.
    16. Iñigo Iturbe-Ormaetxe & Giovanni Ponti & Josefa Tomás, 2016. "Myopic Loss Aversion under Ambiguity and Gender Effects," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-11, December.
    17. Eriksen, Kristoffer W. & Kvaløy, Ola, 2014. "Myopic risk-taking in tournaments," Journal of Economic Behavior & Organization, Elsevier, vol. 97(C), pages 37-46.
    18. Jakusch, Sven Thorsten, 2017. "On the applicability of maximum likelihood methods: From experimental to financial data," SAFE Working Paper Series 148, Leibniz Institute for Financial Research SAFE, revised 2017.
    19. Devin G. Pope & Maurice E. Schweitzer, 2011. "Is Tiger Woods Loss Averse? Persistent Bias in the Face of Experience, Competition, and High Stakes," American Economic Review, American Economic Association, vol. 101(1), pages 129-157, February.
    20. Daniel Gottlieb & Olivia S. Mitchell, 2020. "Narrow Framing and Long‐Term Care Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 87(4), pages 861-893, December.

    More about this item

    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:bla:acctfi:v:62:y:2022:i:1:p:645-665. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/aaanzea.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.