Stock index modeling using hierarchical radial basis function networks

Authors:
Yuehui Chen;Lizhi Peng;Ajith Abraham
Affiliations:
School of Information Science and Engineering, Jinan University, Jinan, P.R. China;School of Information Science and Engineering, Jinan University, Jinan, P.R. China;School of Information Science and Engineering, Jinan University, Jinan, P.R. China
Venue:
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Year:
2006

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Abstract

Forecasting exchange rates is an important financial problem that is receiving increasing attention especially because of its difficulty and practical applications. This paper proposes a Hierarchical Radial Basis Function Network (HiRBF) model for forecasting three major international currency exchange rates. Based on the pre-defined instruction sets, HRBF model can be created and evolved. The HRBF structure is developed using the Extended Compact Genetic Programming (ECGP) and the free parameters embedded in the tree are optimized by the Degraded Ceiling Algorithm (DCA). Empirical results indicate that the proposed method is better than the conventional neural network and RBF networks forecasting models.