TY - JOUR
T1 - Keeping a weather eye on prediction markets: improving forecasts by accounting for environmental conditions
AU - Costa Sperb, Luis Felipe
AU - Sung, Ming-Chien
AU - Johnson, Johnnie
AU - Ma, Tiejun
N1 - 24m embargo as author under Business School (and REF panel C) at other HEI of employment.
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
U2 - 10.1016/j.ijforecast.2018.04.005
DO - 10.1016/j.ijforecast.2018.04.005
M3 - Article
SN - 0169-2070
VL - 35
SP - 321
EP - 335
JO - International Journal of Forecasting
JF - International Journal of Forecasting
IS - 1
ER -