Information markets vs. opinion pools: An empirical comparison

Yiling Chen, Chao Hsien Chu, Tracy Mullen, David M. Pennock

Research output: Chapter in Book/Report/Conference proceedingConference contribution

49 Scopus citations


In this paper, we examine the relative forecast accuracy of information markets versus expert aggregation. We leverage a unique data source of almost 2000 people's subjective probability judgments on 2003 US National Football League games and compare with the "market probabilities" given by two different information markets on exactly the same events, We combine assessments of multiple experts via linear and logarithmic aggregation functions to form pooled predictions. Prices in information markets are used to derive market predictions. Our results show that, at the same time point ahead of the game, information markets provide as accurate predictions as pooled expert assessments. In screening pooled expert predictions, we find that arithmetic average is a robust and efficient pooling function; weighting expert assessments according to their past performance does not improve accuracy of pooled predictions; and logarithmic aggregation functions offer bolder predictions than linear aggregation functions. The results provide insights into the predictive performance of information markets, and the relative merits of selecting among various opinion pooling methods.

Original languageEnglish (US)
Title of host publicationEC'05: Proceedings of the 6th ACM Conference on Electronic Commerce
Number of pages10
StatePublished - 2005
EventEC'05: 6th ACM Conference on Electronic Commerce - Vancouver, Canada
Duration: Jun 5 2005Jun 8 2005


OtherEC'05: 6th ACM Conference on Electronic Commerce

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Business, Management and Accounting (miscellaneous)


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