Modeling information incorporation in markets, with application to detecting and explaining events

Authors:
David M. Pennock;Sandip Debnath;Eric J. Glover;C. Lee Giles
Affiliations:
NEC Research Institute, Princeton, NJ;NEC Research Institute, Princeton, NJ and Department of Computer Science and Engineering, Pennsylvania State University, PA;NEC Research Institute, Princeton, NJ;NEC Research Institute, Princeton, NJ nd Department of Computer Science and Engineering and School of Information Sciences and Technology, Pennsylvania State University, PA
Venue:
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Year:
2002

Citing 2
Cited 11

Extracting collective probabilistic forecasts from web games

Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Improving Category Specific Web Search by Learning Query Modifications

SAINT '01 Proceedings of the 2001 Symposium on Applications and the Internet (SAINT 2001)

Computation in a distributed information market

Proceedings of the 4th ACM conference on Electronic commerce
Information incorporation in online in-Game sports betting markets

Proceedings of the 4th ACM conference on Electronic commerce
A learning based model for headline extraction of news articles to find explanatory sentences for events

Proceedings of the 3rd international conference on Knowledge capture
Computation in a distributed information market

Theoretical Computer Science - Game theory meets theoretical computer science
A strategic model for information markets

Proceedings of the 8th ACM conference on Electronic commerce
The imagination market

Information Systems Frontiers
Incentives for expressing opinions in online polls

Proceedings of the 9th ACM conference on Electronic commerce
Modeling volatility in prediction markets

Proceedings of the 10th ACM conference on Electronic commerce
Mechanisms for making crowds truthful

Journal of Artificial Intelligence Research
Prediction without markets

Proceedings of the 11th ACM conference on Electronic commerce
Using a case-based reasoning approach for trading in sports betting markets

Applied Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

We develop a model of how information flows into a market, and derive algorithms for automatically detecting and explaining relevant events. We analyze data from twenty-two "political stock markets" (i.e., betting markets on political outcomes) on the Iowa Electronic Market (IEM). We prove that, under certain efficiency assumptions, prices in such betting markets will on average approach the correct outcomes over time, and show that IEM data conforms closely to the theory. We present a simple model of a betting market where information is revealed over time, and show a qualitative correspondence between the model and real market data. We also present an algorithm for automatically detecting significant events and generating semantic explanations of their origin. The algorithm operates by discovering significant changes in vocabulary on online news sources (using expected entropy loss) that align with major price spikes in related betting markets.