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Forecasting Uncertain Events with Small Groups

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  • Kay-Yut Chen
  • Leslie R. Fine
  • Bernardo A. Huberman

Abstract

We present a novel methodology for predicting future outcomes that uses small numbers of individuals participating in an imperfect information market. By determining their risk attitudes and performing a nonlinear aggregation of their predictions, we are able to assess the probability of the future outcome of an uncertain event and compare it to both the objective probability of its occurrence and the performance of the market as a whole. Experiments show that this nonlinear aggregation mechanism vastly outperforms both the imperfect market and the best of the participants.

Suggested Citation

  • Kay-Yut Chen & Leslie R. Fine & Bernardo A. Huberman, 2001. "Forecasting Uncertain Events with Small Groups," Papers cond-mat/0108028, arXiv.org.
    • Handle: RePEc:arx:papers:cond-mat/0108028
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    References listed on IDEAS

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    1. Plott, Charles R & Sunder, Shyam, 1982. "Efficiency of Experimental Security Markets with Insider Information: An Application of Rational-Expectations Models," Journal of Political Economy, University of Chicago Press, vol. 90(4), pages 663-698, August.
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    Cited by:

    1. 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.
    2. Kay-Yut Chen & Leslie R. Fine & Bernardo A. Huberman, 2004. "Eliminating Public Knowledge Biases in Information-Aggregation Mechanisms," Management Science, INFORMS, vol. 50(7), pages 983-994, July.

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