Abstract
Fixed odds betting is a popular mechanism in sports game betting. In this paper, we aim to decipher actual group belief on contingent future events from the dynamics of fixed odds betting. Different from previous studies, we adopt the prospect theory rather than the expected utility (EU) theory to model bettor behaviors. Thus, we do not need to make assumptions on how much each bettor stake on their preferred events. We develop a model that captures the heterogeneity of bettors with behavior parameters drawn from beta distributions. We evaluate our proposed model on a real-world dataset collected from online betting games for 2008 Olympic Game events. In the empirical study, our model significantly outperforms expert (bookmaker) predictions. Our study shows the possibility of developing a light-weight derivative prediction market upon fixed odds betting for collective information analysis and decision making.
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References
Arrow, K.J., et al.: The Promise of Prediction Markets. Science 320(5878), 877–878 (2008)
Schrieber, J.M.: The Application of Prediction Markets to Business. Engineering Systems Division (2004)
Servan-Schreiber, E., et al.: Prediction Markets: Does Money Matter? Electronic Markets 14(3), 243–251 (2004)
Gray, P.K., Gray, S.F.: Testing Market Efficiency: Evidence from the NFL Sports Betting Market. Journal of Finance 52(4), 1725–1737 (1997)
Kuypers, T.: Information and Efficiency: An Empirical Study of a Fixed Odds Betting Market. Applied Economics 32(11), 1353–1363 (2000)
Steven, D.L.: Why are gambling markets organised so differently from financial markets? Economic Journal 114(495), 223–246 (2004)
Erik, S., Justin, W.: Explaining the Favorite-Long Shot Bias: Is it Risk-Love or Misperceptions? In: Chicago, IL, ETATS-UNIS, vol. 118, pp. 723–746. University of Chicago Press, Chicago (2010)
Quandt, R.E.: Betting and Equilibrium. The Quarterly Journal of Economics 101(1), 201–207 (1986)
Kahneman, D., Tversky, A.: Prospect Theory: An Analysis of Decision under Risk. Econometrica 47(2), 263–291 (1979)
Justin, W., Eric, Z.: Interpreting Prediction Market Prices as Probabilities. Institute for the Study of Labor, IZA (2006)
Tversky, A., Kahneman, D.: Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty 5(4), 297–323 (1992)
Bruno, J., Bernard, S.: Estimating Preferences under Risk: The Case of Racetrack Bettors. Journal of Political Economy 108(3), 503–530 (2000)
Wang, F.-Y.: Toward a Paradigm Shift in Social Computing: The ACP Approach. IEEE Intelligent Systems 22(5), 65–67 (2007)
Wang, F.-Y., et al.: Social Computing: From Social Informatics to Social Intelligence. IEEE Intelligent Systems 22(2), 79–83 (2007)
Chen, Y., et al.: Information markets vs. opinion pools: an empirical comparison. In: 6th ACM Conference on Electronic Commerce. ACM Press, Vancsouver (2005)
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Chen, W., Li, X., Zeng, D. (2011). Estimating Collective Belief in Fixed Odds Betting. In: Chau, M., Wang, G.A., Zheng, X., Chen, H., Zeng, D., Mao, W. (eds) Intelligence and Security Informatics. PAISI 2011. Lecture Notes in Computer Science, vol 6749. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22039-5_6
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DOI: https://doi.org/10.1007/978-3-642-22039-5_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22038-8
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