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Agent-Based Modeling of the Prediction Markets

  • Tongkui Yu
  • Shu-Heng Chen

We propose a simple agent-based model of the political election prediction market which reflects the intrinsic feature of the prediction market as an information aggregation mechanism. Each agent has a vote, and all agents’ votes determine the election result. Some of the agents participate in the prediction market. Agents form their beliefs by observing their neighbors’ voting disposition, and trade with these beliefs by following some forms of the zero-intelligence strategy. In this model, the mean price of the market is used as a forecast of the election result. We study the effect of the radius of agents’ neighborhood and the geographical distribution of information on the prediction accuracy. In addition, we also identify one of the mechanisms which can replicate the favorite-longshot bias, a stylized fact in the prediction market. This model can then provide a framework for further analysis on the prediction market when market participants have more sophisticated trading behavior.

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Paper provided by ASSRU - Algorithmic Social Science Research Unit in its series ASSRU Discussion Papers with number 1119.

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Date of creation: 2011
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Handle: RePEc:trn:utwpas:1119
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  1. Gode, Dhananjay K & Sunder, Shyam, 1993. "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 119-37, February.
  2. Justin Wolfers & Eric Zitzewitz, 2006. "Interpreting prediction market prices as probabilities," Working Paper Series 2006-11, Federal Reserve Bank of San Francisco.
  3. Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 107-126, Spring.
  4. Snowberg, Erik & Wolfers, Justin, 2010. "Explaining the Favorite-Longshot Bias: Is it Risk-Love or Misperceptions?," IZA Discussion Papers 4884, Institute for the Study of Labor (IZA).
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