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Forecasting uncertain events with small groups
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Source Electronic Commerce archive
Proceedings of the 3rd ACM conference on Electronic Commerce table of contents
Tampa, Florida, USA
Pages: 58 - 64  
Year of Publication: 2001
ISBN:1-58113-387-1
Authors
Kay-Yut Chen  HP Laboratories, Palo Alto, CA
Leslie R. Fine  HP Laboratories, Palo Alto, CA
Bernardo A. Huberman  HP Laboratories, Palo Alto, CA
Sponsor
SIGEcom: ACM Special Interest Group on Electronic Commerce
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 2,   Downloads (12 Months): 33,   Citation Count: 4
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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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Kay-Yut Chen: colleagues
Leslie R. Fine: colleagues
Bernardo A. Huberman: colleagues

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