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Toward an Understanding of Financial Markets using Multi-agent Games

  • Neil F. Johnson
  • David Lamper
  • Paul Jefferies
  • Michael L. Hart
Chapter

Abstract

We report on our use of multi-agent games to understand financial market behavior. In addition to discussing the background to the multi-agent games themselves, we report a technique which may prove useful for forecasting future movements of financial time-series. A third-party game is trained on a black-box time-series, and is then run into the future to extract next-step and multi-step predictions. Such predictions have potential use as the basis for improved risk management and portfolio optimization strategies.

Keywords

Transaction Cost Financial Market Strategy Space Real Market Hedging Strategy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Neil F. Johnson
  • David Lamper
  • Paul Jefferies
  • Michael L. Hart

There are no affiliations available

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