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Is one price enough to value a state-contingent asset correctly? Evidence from a gambling market

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  • Michael Cain
  • David Law
  • David Peel

Abstract

The answer to this question, based on a study of 1000 greyhound races, is 'no'. Although the efficient markets hypothesis asserts that speculative market prices optimally encapsulate all relevant information, it is found that 'Shin probabilities' (based on Shin, 1993), in which a dog's winning probability is a complicated function of the winning probabilities of all contenders in the race, correct the favouritelongshot bias, and in doing so dominate the predictive abilities of individual market prices, and of linear and non-linear functions of them. Since there is an equivalent bias in at least some financial markets, the finding may have wider application.

Suggested Citation

  • Michael Cain & David Law & David Peel, 2002. "Is one price enough to value a state-contingent asset correctly? Evidence from a gambling market," Applied Financial Economics, Taylor & Francis Journals, vol. 12(1), pages 33-38.
    • Handle: RePEc:taf:apfiec:v:12:y:2002:i:1:p:33-38
    DOI: 10.1080/09603100110102682
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    References listed on IDEAS

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    1. Hyun Song Shin, 2008. "Prices Of State Contingent Claims With Insider Traders, And The Favourite-Longshot Bias," World Scientific Book Chapters, in: Donald B Hausch & Victor SY Lo & William T Ziemba (ed.), Efficiency Of Racetrack Betting Markets, chapter 34, pages 343-352, World Scientific Publishing Co. Pte. Ltd..
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    5. Martin Weitzman, 2008. "Utility Analysis And Group Behavior An Empirical Study," World Scientific Book Chapters, in: Donald B Hausch & Victor SY Lo & William T Ziemba (ed.), Efficiency Of Racetrack Betting Markets, chapter 9, pages 47-55, World Scientific Publishing Co. Pte. Ltd..
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    Cited by:

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    2. Sperb, Luis Felipe Costa & Sung, Ming-Chien & Johnson, Johnnie E.V. & Ma, Tiejun, 2019. "Keeping a weather eye on prediction markets: The influence of environmental conditions on forecasting accuracy," International Journal of Forecasting, Elsevier, vol. 35(1), pages 321-335.
    3. Jason P. Berkowitz & Craig A. Depken II & John M. Gandar, 2018. "The Conversion of Money Lines Into Win Probabilities," Journal of Sports Economics, , vol. 19(7), pages 990-1015, October.
    4. Berkowitz, Jason P. & Depken II, Craig A. & Gandar, John M., 2018. "Market evidence against widespread point shaving in college basketball," Journal of Economic Behavior & Organization, Elsevier, vol. 153(C), pages 283-292.
    5. Lionel Page & Robert T. Clemen, 2013. "Do Prediction Markets Produce Well‐Calibrated Probability Forecasts?-super-," Economic Journal, Royal Economic Society, vol. 123(568), pages 491-513, May.
    6. Erik Å trumbelj, 2016. "A Comment on the Bias of Probabilities Derived From Betting Odds and Their Use in Measuring Outcome Uncertainty," Journal of Sports Economics, , vol. 17(1), pages 12-26, January.

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