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Federal Reserve Bank of San Francisco
Working Paper Series
Interpreting prediction market prices as probabilities
Justin Wolfers
Eric Zitzewitz
Abstract

While most empirical analysis of prediction markets treats prices of binary options as predictions of the probability of future events, Manski (2004) has recently argued that there is little existing theory supporting this practice. We provide relevant analytic foundations, describing sufficient conditions under which prediction markets prices correspond with mean beliefs. Beyond these specific sufficient conditions, we show that for a broad class of models prediction market prices are usually close to the mean beliefs of traders. The key parameters driving trading behavior in prediction markets are the degree of risk aversion and the distribution on beliefs, and we provide some novel data on the distribution of beliefs in a couple of interesting contexts. We find that prediction markets prices typically provide useful (albeit sometimes biased) estimates of average beliefs about the probability an event occurs.


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Justin Wolfers & Eric Zitzewitz, Interpreting prediction market prices as probabilities, Federal Reserve Bank of San Francisco, Working Paper Series 2006-11, 2006.
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Keywords: Forecasting ; Financial markets ; Econometric models
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