Architecture of a prediction economy

A design and implementation of a Prediction Economy is presented and compared to alternative designs. A Prediction Economy is composed of prediction markets, market managers, information brokers and automated trading agents. Two important goals of a Prediction Economy are to improve liquidity and information dispersal. Market managers automatically open and close appropriate markets, quickly giving traders access to the latest claims. Information brokers deliver parsed data to the trading agents. The agents execute trades on markets that might not otherwise have much trading action. Some preliminary results from a running Prediction Economy are presented, with binary markets based on football plays during a college football game. The most accurate agent chose to enter 8 of 32 markets, and was able to predict 7 of the 8 football play attempts correctly. Source code for the newly implemented tools is available, as are references to the existing open source tools used.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2008

Author dc:creator

• Carver, Jason W

Advisor dc:contributor.advisor

• Thomas W. Malone.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/45807

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/45807