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An experimental analysis of information acquisition in prediction markets

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  • Page, Lionel
  • Siemroth, Christoph

Abstract

We study which factors in terms of trading environment and trader characteristics determine individual information acquisition in experimental asset markets. Traders with larger endowments, existing inconclusive information, lower risk aversion, and less experience in financial markets tend to acquire more information. Overall, we find that traders overacquire information, so that informed traders on average obtain negative profits net of information costs. Information acquisition and the associated losses do not diminish over time. This overacquisition phenomenon is inconsistent with predictions of rational expectations equilibrium, and we argue it resembles the overdissipation results from the contest literature. We find that more acquired information in the market leads to smaller differences between fundamental asset values and prices. Thus, the overacquisition phenomenon is a novel explanation for the high forecasting accuracy of prediction markets.

Suggested Citation

  • Page, Lionel & Siemroth, Christoph, 2017. "An experimental analysis of information acquisition in prediction markets," Games and Economic Behavior, Elsevier, vol. 101(C), pages 354-378.
    • Handle: RePEc:eee:gamebe:v:101:y:2017:i:c:p:354-378
    DOI: 10.1016/j.geb.2015.11.002
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    1. Sunder, Shyam, 1992. "Market for Information: Experimental Evidence," Econometrica, Econometric Society, vol. 60(3), pages 667-695, May.
    2. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    3. Sheremeta, Roman M., 2010. "Experimental comparison of multi-stage and one-stage contests," Games and Economic Behavior, Elsevier, vol. 68(2), pages 731-747, March.
    4. Thomas Dohmen & Armin Falk & David Huffman & Uwe Sunde & Jürgen Schupp & Gert G. Wagner, 2011. "Individual Risk Attitudes: Measurement, Determinants, And Behavioral Consequences," Journal of the European Economic Association, European Economic Association, vol. 9(3), pages 522-550, June.
    5. Angrisani Marco & Guarino Antonio & Huck Steffen & Larson Nathan C, 2011. "No-Trade in the Laboratory," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 11(1), pages 1-58, April.
    6. Carrillo, Juan D. & Palfrey, Thomas R., 2011. "No trade," Games and Economic Behavior, Elsevier, vol. 71(1), pages 66-87, January.
    7. Milgrom, Paul & Stokey, Nancy, 1982. "Information, trade and common knowledge," Journal of Economic Theory, Elsevier, vol. 26(1), pages 17-27, February.
    8. Andrea Frazzini, 2006. "The Disposition Effect and Underreaction to News," Journal of Finance, American Finance Association, vol. 61(4), pages 2017-2046, August.
    9. Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 107-126, Spring.
    10. Roman M. Sheremeta, 2013. "Overbidding And Heterogeneous Behavior In Contest Experiments," Journal of Economic Surveys, Wiley Blackwell, vol. 27(3), pages 491-514, July.
    11. Joël Peress, 2004. "Wealth, Information Acquisition, and Portfolio Choice," The Review of Financial Studies, Society for Financial Studies, vol. 17(3), pages 879-914.
    12. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    13. Paul J. Healy & Sera Linardi & J. Richard Lowery & John O. Ledyard, 2010. "Prediction Markets: Alternative Mechanisms for Complex Environments with Few Traders," Management Science, INFORMS, vol. 56(11), pages 1977-1996, November.
    14. Matthews,R. C. O., 2011. "A Study in Trade-Cycle History," Cambridge Books, Cambridge University Press, number 9781107600119, November.
    15. Simon P. Anderson & Jacob K. Goeree & Charles A. Holt, 1998. "Rent Seeking with Bounded Rationality: An Analysis of the All-Pay Auction," Springer Books, in: Roger D. Congleton & Arye L. Hillman & Kai A. Konrad (ed.), 40 Years of Research on Rent Seeking 1, pages 225-250, Springer.
    16. Jürgen Huber & Martin Angerer & Michael Kirchler, 2011. "Experimental asset markets with endogenous choice of costly asymmetric information," Experimental Economics, Springer;Economic Science Association, vol. 14(2), pages 223-240, May.
    17. Copeland, Thomas E & Friedman, Daniel, 1992. "The Market Value of Information: Some Experimental Results," The Journal of Business, University of Chicago Press, vol. 65(2), pages 241-266, April.
    18. Cary Deck & David Porter, 2013. "Prediction Markets In The Laboratory," Journal of Economic Surveys, Wiley Blackwell, vol. 27(3), pages 589-603, July.
    19. Ledyard, John & Hanson, Robin & Ishikida, Takashi, 2009. "An experimental test of combinatorial information markets," Journal of Economic Behavior & Organization, Elsevier, vol. 69(2), pages 182-189, February.
    20. 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.
    21. Stefan Palan, 2013. "A Review Of Bubbles And Crashes In Experimental Asset Markets," Journal of Economic Surveys, Wiley Blackwell, vol. 27(3), pages 570-588, July.
    22. Konrad, Kai A., 2009. "Strategy and Dynamics in Contests," OUP Catalogue, Oxford University Press, number 9780199549603.
    23. Plott, Charles R & Sunder, Shyam, 1988. "Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets," Econometrica, Econometric Society, vol. 56(5), pages 1085-1118, September.
    24. Charles N. Noussair & Steven Tucker, 2013. "Experimental Research On Asset Pricing," Journal of Economic Surveys, Wiley Blackwell, vol. 27(3), pages 554-569, July.
    25. N/A, 2011. "World Trade Report 2011: Executive Summary," Foreign Trade Review, , vol. 46(2), pages 108-132, July.
    26. Siemroth, Christoph, 2014. "Why prediction markets work : the role of information acquisition and endogenous weighting," Working Papers 14-29, University of Mannheim, Department of Economics.
    27. Brad M. Barber & Terrance Odean, 2001. "Boys will be Boys: Gender, Overconfidence, and Common Stock Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(1), pages 261-292.
    28. Ackert, Lucy F. & Church, Bryan K. & Shehata, Mohamed, 1997. "Market behavior in the presence of costly, imperfect information: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 33(1), pages 61-74, May.
    29. Grossman, Sanford J, 1976. "On the Efficiency of Competitive Stock Markets Where Trades Have Diverse Information," Journal of Finance, American Finance Association, vol. 31(2), pages 573-585, May.
    30. repec:reg:rpubli:460 is not listed on IDEAS
    31. repec:elg:eechap:15325_10 is not listed on IDEAS
    32. Huber, Jurgen, 2007. "`J'-shaped returns to timing advantage in access to information - Experimental evidence and a tentative explanation," Journal of Economic Dynamics and Control, Elsevier, vol. 31(8), pages 2536-2572, August.
    33. Berg, Joyce E. & Nelson, Forrest D. & Rietz, Thomas A., 2008. "Prediction market accuracy in the long run," International Journal of Forecasting, Elsevier, vol. 24(2), pages 285-300.
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    More about this item

    Keywords

    Asymmetric information; Experimental asset markets; Information acquisition; Prediction markets;
    All these keywords.

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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