Memoirs of an indifferent trader: Estimating forecast distributions from prediction markets

Published on Jul 1, 2010in Quantitative Economics
· DOI :10.3982/QE6
Joyce E. Berg16
Estimated H-index: 16
(UI: University of Iowa),
John Geweke68
Estimated H-index: 68
(UTS: University of Technology, Sydney),
Thomas A. Rietz21
Estimated H-index: 21
(UI: University of Iowa)
Prediction markets for future events are increasingly common and they often trade several contracts for the same event. This paper considers the distribution of a normative risk-neutral trader who, given any portfolio of contracts traded on the event, would choose not to reallocate that portfolio of contracts even if transactions costs were zero. Because common parametric distributions can conflict with observed prediction market prices, the distribution is given a nonparametric representation together with a prior distribution favoring smooth and concentrated distributions. Posterior modal distributions are found for popular vote shares of the U.S. presidential candidates in the 100 days leading up to the elections of 1992, 1996, 2000, and 2004, using bid and ask prices on multiple contracts from the Iowa Electronic Markets. On some days, the distributions are multimodal or substantially asymmetric. The derived distributions are more concentrated than the historical distribution of popular vote shares in presidential elections, but do not tend to become more concentrated as time to elections diminishes.
The basic idea of this note is simple. Fundamentally, opinion polls are estimates of the final vote shares of candidates. These estimates are characterised by uncertainty. This uncertainty is the link between prediction market prices and the opinion polls. The simple reason for this is that the price in a prediction market indicates the probability that a given candidate will win a share of the vote greater than a given threshold (usually 50%). As soon as one is able to estimate the distribution...
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Abstract We examine the impact of price trends on the accuracy of forecasts from prediction markets. In particular, we study an electronic betting exchange market and construct independent variables from market price (odds) time series from 6058 individual markets (a dataset consisting of over 8.4 million price points). Using a conditional logit model, we find that a systematic relationship exists between trends in odds and the accuracy of odds-implied event probabilities; the relationship is co...
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