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Distilling the Wisdom of Crowds: Prediction Markets versus Prediction PollsPavel D. AtanasovPolly Portfolio; University of Pennsylvania Phillip RescoberIndependent Eric StoneIndependent Samuel A. SwiftUniversity of California, Berkeley - Institute of Business and Economic Research (IBER); Tepper School of Business Emile Servan-SchreiberLUMENOGIC Philip E. TetlockUniversity of Pennsylvania Lyle UngarUniversity of Pennsylvania Barbara MellersUniversity of California, Berkeley - Marketing Group; University of Pennsylvania - Marketing Department October 8, 2015 Management Science, Early View, Forthcoming Abstract: We report the results of the first large-scale, long-term, experimental test between two crowd sourcing methods – prediction markets and prediction polls. More than 2,400 participants made forecasts on 261 events over two seasons of a geopolitical prediction tournament. Some forecasters traded in a continuous double auction market and were ranked based on earnings. Others submitted probability judgments, independently or in teams, and were ranked based on Brier scores. In both seasons of the tournament, last day prices from the prediction market were more accurate than the simple mean of forecasts from prediction polls. However, team prediction polls outperformed prediction markets when poll forecasts were aggregated with algorithms using temporal decay, performance weighting and recalibration. The biggest advantage of prediction polls occurred at the start of long-duration questions. Prediction polls with proper scoring, algorithmic aggregation and teaming offer an attractive alternative to prediction markets for distilling the wisdom of crowds.
Number of Pages in PDF File: 37 Keywords: Prediction, Forecasting, Prediction Markets, Crowdsourcing JEL Classification: C82, C93, D84 Date posted: September 15, 2015 ; Last revised: June 17, 2016Suggested CitationContact Information
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