Application of multi-agent games to the prediction of financial time series

Neil F. Johnson, David Lamper, Paul Jefferies, Michael L. Hart, Sam Howison

Research output: Contribution to journalConference article

35 Scopus citations

Abstract

We report on a technique based on multi-agent games which has potential use in the prediction of 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. In addition to the possibility of identifying profit opportunities, the technique may prove useful in the development of improved risk management strategies.

Original languageEnglish (US)
Pages (from-to)222-227
Number of pages6
JournalPhysica A: Statistical Mechanics and its Applications
Volume299
Issue number1-2
DOIs
StatePublished - Oct 1 2001
EventApplication of Physics in Economic Modelling (NATO ARW) - Prague, Czech Republic
Duration: Feb 8 2001Feb 10 2001

ASJC Scopus subject areas

  • Statistics and Probability
  • Condensed Matter Physics

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