Document Type
Conference Proceeding
Publication Date
2011
Abstract
—Prediction markets have been shown to be a useful tool in forecasting the outcome of future events by aggregating public opinion about the events’ outcome. Previous research on prediction markets has mostly analyzed the prediction markets by building complex analytical models. In this paper, we posit that simpler yet powerful Boolean rules can be used to adequately describe the operations of a prediction market. We have used a multi-agent based prediction market where Boolean network based rules are used to capture the evolution of the beliefs of the market’s participants, as well as to aggregate the prices in the market. We show that despite the simplification of the traders’ beliefs in the prediction market into Boolean states, the aggregated market price calculated using our BN model is strongly correlated with the price calculated by a commonly used aggregation strategy in existing prediction markets called the Logarithmic Market Scoring Rule (LMSR). We also empirically show that our Boolean network-based prediction market can stabilize market prices under the presence of untruthful belief revelation by the traders.
Recommended Citation
Jumadinova, Janyl; Matache, Mihaela Teodora; and Dasgupta, Prithviraj, "A Multi-Agent Prediction Market Based on Boolean Network Evolution" (2011). Mathematics Faculty Proceedings & Presentations. 3.
https://digitalcommons.unomaha.edu/mathfacproc/3
Comments
© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.