Predicting the Future

Kay-Yut Chen, Leslie R. Fine and Bernardo A. Huberman
Additional contact information
Kay-Yut Chen: HP Laboratories
Leslie R. Fine: HP Laboratories
Bernardo A. Huberman: HP Laboratories

Information Systems Frontiers, 2003, vol. 5, issue 1, No 7, 47-61

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

Keywords: information aggregation; information markets; public information; experimental economics; mechanism design (search for similar items in EconPapers)
Date: 2003
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://link.springer.com/10.1023/A:1022041805438 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:infosf:v:5:y:2003:i:1:d:10.1023_a:1022041805438

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10796

DOI: 10.1023/A:1022041805438

Access Statistics for this article

Information Systems Frontiers is currently edited by Ram Ramesh and Raghav Rao

More articles in Information Systems Frontiers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().