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Risk Aversion, Beliefs, and Prediction Market Equilibrium

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  • Steven Gjerstad

    (University of Arizona)

Abstract

Manski [2004] analyzes the relationship between the distribution of traders’ beliefs and the equilibrium price in a prediction market with risk neutral traders. He finds that there can be a substantial difference between the mean belief that an event will occur, and the price of an asset that pays one dollar if the event occurs and otherwise pays nothing. This result is puzzling, since these markets frequently produce excellent predictions. This paper resolves the apparent puzzle by demonstrating that both risk aversion and the distribution of traders’ beliefs significantly affect the equilibrium price. For coeffcients of relative risk aversion near those estimated in empirical studies and for plausible belief distributions, the equilibrium price is very near the traders’ mean belief.

Suggested Citation

  • Steven Gjerstad, 2004. "Risk Aversion, Beliefs, and Prediction Market Equilibrium," Microeconomics 0411002, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpmi:0411002
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    References listed on IDEAS

    as
    1. Manski, Charles F., 2006. "Interpreting the predictions of prediction markets," Economics Letters, Elsevier, vol. 91(3), pages 425-429, June.
    2. Charles A. Holt & Susan K. Laury, 2002. "Risk Aversion and Incentive Effects," American Economic Review, American Economic Association, vol. 92(5), pages 1644-1655, December.
    3. Charles R. Plott & Jorgen Wit & Winston C. Yang, 2003. "Parimutuel betting markets as information aggregation devices: experimental results," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 22(2), pages 311-351, September.
    4. Forsythe, Robert & Forrest Nelson & George R. Neumann & Jack Wright, 1992. "Anatomy of an Experimental Political Stock Market," American Economic Review, American Economic Association, vol. 82(5), pages 1142-1161, December.
    5. Yaw Nyarko & Andrew Schotter, 2002. "An Experimental Study of Belief Learning Using Elicited Beliefs," Econometrica, Econometric Society, vol. 70(3), pages 971-1005, May.
    6. Thaler, Richard H & Ziemba, William T, 1988. "Parimutuel Betting Markets: Racetracks and Lotteries," Journal of Economic Perspectives, American Economic Association, vol. 2(2), pages 161-174, Spring.
    7. Hansen, Lars Peter & Singleton, Kenneth J, 1982. "Generalized Instrumental Variables Estimation of Nonlinear Rational Expectations Models," Econometrica, Econometric Society, vol. 50(5), pages 1269-1286, September.
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    Citations

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    Cited by:

    1. Paul Rhode & Koleman Strumpf, 2006. "Manipulating political stock markets: A field experiment and a century of observational data," Natural Field Experiments 00325, The Field Experiments Website.
    2. Whelan, Karl, 2023. "How Do Prediction Market Fees Affect Prices and Participants?," MPRA Paper 116926, University Library of Munich, Germany.
    3. He, Xue-Zhong & Treich, Nicolas, 2012. "Heterogeneous Beliefs and Prediction Market Accuracy," TSE Working Papers 13-394, Toulouse School of Economics (TSE).
    4. Justin Wolfers & Eric Zitzewitz, 2006. "Interpreting prediction market prices as probabilities," Working Paper Series 2006-11, Federal Reserve Bank of San Francisco.
    5. Snowberg, Erik & Wolfers, Justin & Zitzewitz, Eric, 2013. "Prediction Markets for Economic Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 657-687, Elsevier.
    6. Stefan Palan & Jürgen Huber & Larissa Senninger, 2020. "Aggregation mechanisms for crowd predictions," Experimental Economics, Springer;Economic Science Association, vol. 23(3), pages 788-814, September.
    7. RYan Oprea & David Porter & Chris Hibbert & Robin Hanson & Dorina Tila, 2008. "Can Manipulators Mislead Prediction Market Observers?," Working Papers 08-01, Chapman University, Economic Science Institute.
    8. Manski, Charles F., 2006. "Interpreting the predictions of prediction markets," Economics Letters, Elsevier, vol. 91(3), pages 425-429, June.
    9. Mikuláš Gangur & Miroslav Plevný, 2014. "Tools for Consumer Rights Protection in the Prediction of Electronic Virtual Market and Technological Changes," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 16(36), pages 578-578, May.
    10. Coulomb, Renaud & Sangnier, Marc, 2014. "The impact of political majorities on firm value: Do electoral promises or friendship connections matter?," Journal of Public Economics, Elsevier, vol. 115(C), pages 158-170.
    11. Marco Ottaviani & Peter Norman Sørensen, 2009. "Aggregation of Information and Beliefs: Asset Pricing Lessons from Prediction Markets," Discussion Papers 09-14, University of Copenhagen. Department of Economics.
    12. Renaud Coulomb & Marc Sangnier, 2014. "The Impact of Political Majorities on Firm Value: Do Electoral Promises or Friendship Connections Matter?," PSE Working Papers halshs-00990241, HAL.
    13. Rajiv Sethi & Jennifer Wortman Vaughan, 2016. "Belief Aggregation with Automated Market Makers," Computational Economics, Springer;Society for Computational Economics, vol. 48(1), pages 155-178, June.
    14. repec:grz:wpsses:2019-01 is not listed on IDEAS
    15. Yu, Dian & Gao, Jianjun & Wang, Tongyao, 2022. "Betting market equilibrium with heterogeneous beliefs: A prospect theory-based model," European Journal of Operational Research, Elsevier, vol. 298(1), pages 137-151.
    16. Coulomb, Renaud & Sangnier, Marc, 2014. "The impact of political majorities on firm value: Do electoral promises or friendship connections matter?," Journal of Public Economics, Elsevier, vol. 115(C), pages 158-170.
    17. Deck, Cary & Hao, Li & Porter, David, 2015. "Do prediction markets aid defenders in a weak-link contest?," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 248-258.

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    More about this item

    Keywords

    Asset pricing; beliefs; competitive equilibrium; prediction markets; risk aversion;
    All these keywords.

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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