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Public Information Bias and Prediction Market Accuracy

Thomas Gruca, Joyce E. Berg and Michael Cipriano
The Journal of Prediction Markets
Volume 1, Number 3, pages 219-231, 2007 (December)

  • Abstract
    How do prediction markets achieve high levels of accuracy? We propose that, in some situations, traders in prediction markets improve upon publicly available information. Specifically, when there is a known bias in publicly available information, markets provide an incentive for traders to "de-bias" this information. In such a situation, a prediction market will provide a more accurate forecast than the public information available to traders. We test our conjecture using real-money prediction markets for seven local elections in the United States. We find that the prediction market forecasts are significantly more accurate than those generated using the pre-election polls.
  • Published Paper