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A Model of Casino Gambling

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  • Nicholas Barberis

    (School of Management, Yale University, New Haven, Connecticut 06511)

Abstract

We show that prospect theory offers a rich theory of casino gambling, one that captures several features of actual gambling behavior. First, we demonstrate that for a wide range of preference parameter values, a prospect theory agent would be willing to gamble in a casino even if the casino offers only bets with no skewness and with zero or negative expected value. Second, we show that the probability weighting embedded in prospect theory leads to a plausible time inconsistency: at the moment he enters a casino, the agent plans to follow one particular gambling strategy; but after he starts playing, he wants to switch to a different strategy. The model therefore predicts heterogeneity in gambling behavior: how a gambler behaves depends on whether he is aware of the time inconsistency; and, if he is aware of it, on whether he can commit in advance to his initial plan of action. This paper was accepted by Brad Barber, Teck Ho, and Terrance Odean, special issue editors.

Suggested Citation

  • Nicholas Barberis, 2012. "A Model of Casino Gambling," Management Science, INFORMS, vol. 58(1), pages 35-51, January.
    • Handle: RePEc:inm:ormnsc:v:58:y:2012:i:1:p:35-51
    DOI: 10.1287/mnsc.1110.1435
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    References listed on IDEAS

    as
    1. 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.
    2. Nicholas Barberis & Ming Huang, 2008. "Stocks as Lotteries: The Implications of Probability Weighting for Security Prices," American Economic Review, American Economic Association, vol. 98(5), pages 2066-2100, December.
    3. Terrance Odean, 1998. "Are Investors Reluctant to Realize Their Losses?," Journal of Finance, American Finance Association, vol. 53(5), pages 1775-1798, October.
    4. 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..
    5. Shlomo Benartzi & Richard H. Thaler, 1995. "Myopic Loss Aversion and the Equity Premium Puzzle," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 110(1), pages 73-92.
    6. Machina, Mark J, 1989. "Dynamic Consistency and Non-expected Utility Models of Choice under Uncertainty," Journal of Economic Literature, American Economic Association, vol. 27(4), pages 1622-1668, December.
    7. Milton Friedman & L. J. Savage, 1948. "The Utility Analysis of Choices Involving Risk," Journal of Political Economy, University of Chicago Press, vol. 56(4), pages 279-279.
    8. Conlisk, John, 1993. "The Utility of Gambling," Journal of Risk and Uncertainty, Springer, vol. 6(3), pages 255-275, June.
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