Information Systems Frontiers

, Volume 5, Issue 1, pp 47–61 | Cite as

Predicting the Future

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


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. We then extend the mechanism to prove robust in the presence of public information.

information aggregation information markets public information experimental economics mechanism design 


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Copyright information

© Kluwer Academic Publishers 2003

Authors and Affiliations

  • Kay-Yut Chen
    • 1
  • Leslie R. Fine
    • 1
  • Bernardo A. Huberman
    • 1
  1. 1.HP LaboratoriesPalo AltoUSA

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