Neuro-evolutionary system for FOREX trading

This paper proposes a neuro-genetic system for trading on Forex market. The main idea is to apply evolutionary methods for selection of the most suitable, in a given macro-economic context, set of variables, whose usefulness is subsequently validated based on a short and simplified training of several perceptron-type networks. Once the indicative training for this selected input data proves effective, the final, more sophisticated and more detailed training is performed on the ensemble of neural predictors. The proposed method was tested on 170 five-day investment periods (spanning over 3 years) with very promising results of both average and worst case performance. Furthermore, an investigation into the way the evolutionary component of the system selects input variables in subsequent trading periods has been performed, leading to interesting observation about the usefulness of particular data sources, as well as their repeatability across independent runs of the system.