2012 | OriginalPaper | Chapter
A Hybrid Radial Basis Function and Particle Swarm Optimization Neural Network Approach in Forecasting the EUR/GBP Exchange Rates Returns
Authors : Georgios Sermpinis, Konstantinos Theofilatos, Andreas Karathanasopoulos, Efstratios Georgopoulos, Christian Dunis
Published in: Engineering Applications of Neural Networks
Publisher: Springer Berlin Heidelberg
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The motivation for this paper is to introduce in Finance a hybrid Neural Network architecture of Adaptive Particle Swarm Optimization and Radial Basis Function (ARBF-PSO) and a Neural Network fitness function for financial forecasting purposes. This is done by benchmarking the ARBF-PSO results with those of three different Neural Networks architectures and three statistical/technical models. As it turns out, the ARBF-PSO architecture outperforms all other models in terms of statistical accuracy and trading efficiency in the examined forecasting task.