Abstract
This research presents the ongoing results of trading experiments that have been performed on the DAGGRE prediction market. DAGGRE is a research project that aims to improve the forecasting methods of world events using prediction markets, crowdsourcing and Delphi groups. The DAGGRE prediction market aggregates estimates from hundreds of participants to forecast the outcome of these events. On the prediction market that involves a few thousand human traders, during a time period of a year and a half, we introduced 3 trading algorithms that have been trading live on the market, based on different rules and trading policies. While all the Autotraders improved the overall market participation and activity and outperform most of the human traders, one of them is adaptive to the new information that continuously comes from the market. This paper presents the comparative analysis of the forecasting accuracy and market performance of these 3 Autotraders and discusses the preliminary results of these experiments.
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Berea, A., Twardy, C. (2013). Automated Trading in Prediction Markets. In: Greenberg, A.M., Kennedy, W.G., Bos, N.D. (eds) Social Computing, Behavioral-Cultural Modeling and Prediction. SBP 2013. Lecture Notes in Computer Science, vol 7812. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37210-0_13
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DOI: https://doi.org/10.1007/978-3-642-37210-0_13
Publisher Name: Springer, Berlin, Heidelberg
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