Keeping a weather eye on prediction markets: improving forecasts by accounting for environmental conditions

Abstract

Prediction markets are increasingly being embraced as a mechanism for eliciting and aggregating dispersed information and providing a means of deriving probabilistic forecasts of future uncertain events. The efficient market hypothesis postulates that prediction market prices should incorporate all information relevant to the performance of the contracts traded. This paper shows that this may not be the case in relation to information regarding environmental factors such as the weather and atmospheric conditions. In the context of horseracing betting markets, we demonstrate that even after the effects of these factors on the contestants (horses and jockeys) has been discounted, the accuracy of probabilities derived from market prices are systematically affected by the prevailing weather and atmospheric conditions. By correcting for this phenomenon, we show that significantly better forecasts can be derived from prediction markets, and that these have substantial economic value.

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ORCID for Ming-Chien Sung: orcid.org/0000-0002-2278-6185

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