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How accurate do markets predict the outcome of an event? The Euro 2000 soccer championships experiment

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  • Schmidt, Carsten
  • Werwatz, Axel

Abstract

For the Euro 2000 Soccer Championships an experimental asset market was condueted, with traders buying and selling contracts on the winners of individual matches. Market-generated probabilities are compared to professional bet quotas, and factors that are responsible for the quality of the market prognosis are identified. The comparison shows, that the market is more accurate than the random predictor and slightly better than professional bet quotas, in the sense of mean square error. Moreover, the more certain the market predicts the outcome of an event the more accurate is the prediction. --

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Bibliographic Info

Paper provided by Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes in its series SFB 373 Discussion Papers with number 2002,29.

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Date of creation: 2002
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Handle: RePEc:zbw:sfb373:200229

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Keywords: experimental asset markets; prognosis; market efficiency;

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  1. Forsythe, Robert & Forrest Nelson & George R. Neumann & Jack Wright, 1992. "Anatomy of an Experimental Political Stock Market," American Economic Review, American Economic Association, American Economic Association, vol. 82(5), pages 1142-61, December.
  2. Plott, Charles R & Sunder, Shyam, 1988. "Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets," Econometrica, Econometric Society, Econometric Society, vol. 56(5), pages 1085-1118, September.
  3. repec:wop:humbsf:2001-57 is not listed on IDEAS
  4. Forsythe, Robert & Rietz, Thomas A. & Ross, Thomas W., 1999. "Wishes, expectations and actions: a survey on price formation in election stock markets," Journal of Economic Behavior & Organization, Elsevier, Elsevier, vol. 39(1), pages 83-110, May.
  5. Berlemann, Michael & Schmidt, Carsten, 2001. "Predictive accuracy of political stock markets: Empirical evidence from a European perspective," SFB 373 Discussion Papers 2001,57, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  6. Forsythe, Robert & Lundholm, Russell, 1990. "Information Aggregation in an Experimental Market," Econometrica, Econometric Society, Econometric Society, vol. 58(2), pages 309-47, March.
  7. John M. Gandar & William H. Dare & Craig R. Brown & Richard A. Zuber, 1998. "Informed Traders and Price Variations in the Betting Market for Professional Basketball Games," Journal of Finance, American Finance Association, American Finance Association, vol. 53(1), pages 385-401, 02.
  8. Gray, Philip K & Gray, Stephen F, 1997. " Testing Market Efficiency: Evidence from the NFL Sports Betting Market," Journal of Finance, American Finance Association, American Finance Association, vol. 52(4), pages 1725-37, September.
  9. Gandar, John, et al, 1988. " Testing Rationality in the Point Spread Betting Market," Journal of Finance, American Finance Association, American Finance Association, vol. 43(4), pages 995-1008, September.
  10. Roger C. Vergin & Michael Scriabin, 1978. "Winning Strategies for Wagering on National Football League Games," Management Science, INFORMS, INFORMS, vol. 24(8), pages 809-818, April.
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Cited by:
  1. Jens Grossklags & Carsten Schmidt, 2002. "Artificial Software Agents on Thin Double Auction Markets - A Human Trader Experiment," Papers on Strategic Interaction, Max Planck Institute of Economics, Strategic Interaction Group 2002-45, Max Planck Institute of Economics, Strategic Interaction Group.
  2. Stefan Luckner & Christof Weinhardt, 2007. "How to pay traders in information markets? Results from a field experiment," Artefactual Field Experiments, The Field Experiments Website 00107, The Field Experiments Website.

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