Application of multi-agent games
to the prediction of financial time-series
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.
Click here to
download paper (130 kB)
