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

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

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Paper provided by Oxford Financial Research Centre in its series OFRC Working Papers Series with number 2001mf04.

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Date of creation: 2001
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Handle: RePEc:sbs:wpsefe:2001mf04

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Web page: http://www.finance.ox.ac.uk
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  1. Derveeuw, Julien, 2005. "Market dynamics and agents behaviors: a computational approach," MPRA Paper 4916, University Library of Munich, Germany. [Downloadable!]
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