A multi-agent system for analyzing the effect of information on prediction markets

Prediction markets have been shown to be a useful tool for forecasting the outcome of future events by aggregating public opinion about the event's outcome. In this paper, we investigate an important aspect of prediction markets-the effect of different information-related parameters on the behavior of the traders in the market. We have developed a multi-agent based system that incorporates different information-related aspects including the arrival rate of information, the reliability of information, the penetration or accessibility of information among the different traders, and the perception or impact of information by the traders. We have performed extensive simulations of our agent-based prediction market for analyzing the effect of information-related parameters on the traders' behaviors expressed through their trading prices, and compared our agents' strategies with another agent-based pricing strategy used in prediction markets called the zero intelligence strategy. Our results show that information-related parameters have a significant impact on traders' beliefs about event outcomes, and, frequent, reliable information about events improves the utilities that the traders receive. Overall, our work provides a better understanding of the effect of information on the operation of prediction markets and on the strategies used by the traders in the market.