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Designing Informative Securities

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  • Yiling Chen
  • Mike Ruberry
  • Jennifer Wortman Vaughan
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    Abstract

    We create a formal framework for the design of informative securities in prediction markets. These securities allow a market organizer to infer the likelihood of events of interest as well as if he knew all of the traders' private signals. We consider the design of markets that are always informative, markets that are informative for a particular signal structure of the participants, and informative markets constructed from a restricted selection of securities. We find that to achieve informativeness, it can be necessary to allow participants to express information that may not be directly of interest to the market organizer, and that understanding the participants' signal structure is important for designing informative prediction markets.

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    File URL: http://arxiv.org/pdf/1210.4837
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    Bibliographic Info

    Paper provided by arXiv.org in its series Papers with number 1210.4837.

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    Date of creation: Oct 2012
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    Handle: RePEc:arx:papers:1210.4837

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    Web page: http://arxiv.org/

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    1. Robin Hanson, 2007. "Logarithmic Market Scoring Rules for Modular Combinatorial Information Aggregation," Journal of Prediction Markets, University of Buckingham Press, vol. 1(1), pages 3-15, February.
    2. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-35, November.
    3. Grossman, Sanford J, 1981. "An Introduction to the Theory of Rational Expectations under Asymmetric Information," Review of Economic Studies, Wiley Blackwell, vol. 48(4), pages 541-59, October.
    4. Plott, Charles R. & Sunder, Shyam., . "Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets," Working Papers 463, California Institute of Technology, Division of the Humanities and Social Sciences.
    5. Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
    6. Ostrovsky, Michael, 2009. "Information Aggregation in Dynamic Markets with Strategic Traders," Research Papers 2053, Stanford University, Graduate School of Business.
    7. Martin Spann & Bernd Skiera, 2003. "Internet-Based Virtual Stock Markets for Business Forecasting," Management Science, INFORMS, vol. 49(10), pages 1310-1326, October.
    8. Nielsen, Lars Tyge, et al, 1990. "Common Knowledge of an Aggregate of Expectations," Econometrica, Econometric Society, vol. 58(5), pages 1235-39, September.
    9. Robert J Aumann, 1999. "Agreeing to Disagree," Levine's Working Paper Archive 512, David K. Levine.
    10. Radner, Roy, 1979. "Rational Expectations Equilibrium: Generic Existence and the Information Revealed by Prices," Econometrica, Econometric Society, vol. 47(3), pages 655-78, May.
    11. Garthwaite, Paul H. & Kadane, Joseph B. & O'Hagan, Anthony, 2005. "Statistical Methods for Eliciting Probability Distributions," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 680-701, June.
    12. Nielsen, Lars Tyge, 1984. "Common knowledge, communication, and convergence of beliefs," Mathematical Social Sciences, Elsevier, vol. 8(1), pages 1-14, August.
    13. McKelvey, Richard D & Page, Talbot, 1986. "Common Knowledge, Consensus, and Aggregate Information," Econometrica, Econometric Society, vol. 54(1), pages 109-27, January.
    14. Roy Radner, 1997. "Rational Expectations Equilibrium: Generic Existence and the Information Revealed by Prices," Levine's Working Paper Archive 1594, David K. Levine.
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