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Published in:
2009 | OriginalPaper | Chapter
A Hybrid Neural Network-Based Trading System
Authors : Nikos S. Thomaidis, Georgios D. Dounias
Published in: Hybrid Artificial Intelligence Systems
Publisher: Springer Berlin Heidelberg
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We present a hybrid intelligent trading system that combines artificial neural networks (ANN) and particle swarm optimisation (PSO) to generate optimal trading decisions. A PSO algorithm is used to train ANNs using objective functions that are directly linked to the performance of the trading strategy rather than statistical measures of forecast error (e.g. mean squared error). We experiment with several objective measures that quantify the return/risk associated with the trading system. First results from the application of this methodology to real data show that the out-of-sample performance of trading models is fairly consistent with respect to the objective function they derive from.