Information Exchange in Prediction Markets: How Social Networks Promote Forecast Efficiency

Abstract

This paper studies the effects of information exchange and social networks on the performance of prediction markets with endogenous information acquisition. We provide a game-theoretic framework to resolve the question: Can social networks and information exchange promote the forecast efficiency in prediction markets? Our study shows that a social network is not a panacea in terms of improving forecast efficiency. The use of social networks could be detrimental to forecast performance when the cost of information acquisition is high. Although social networks can provide internal communications among participants, they reduce the incentive to acquire information because of free riding. We also study the effects of social networks on information acquisition in prediction markets. In the symmetric Bayes-Nash Equilibrium, all participants use a threshold strategy, and the equilibrium action of information acquisition is decreasing in the number of participant's friends and increasing in the network density. The aforementioned results are robust to two commonly used mechanisms of prediction markets: a forecast-report mechanism and a security-trading mechanism.

Keywords: Information Exchange, Prediction Markets, Social Networks

JEL Classification: D83, D85, C72