Vector quantized radial basis function neural network with embedded multiple local linear models for financial prediction

Publication Type:
Conference Proceeding
Citation:
Proceedings of the International Joint Conference on Neural Networks, 2005, 4 pp. 2538 - 2543
Issue Date:
2005-12-01
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In this paper, a model is proposed which combines multiple local linear models with a novel modified probabilistic neural network (MPNN). The proposed model is developed to approximate multiple nonlinear model with reduced computational requirement The proposed model shows to provide both low bias and variance with reduced computations by utilizing semi parametric local linear approximation and efficient vector quantization of data space. The proposed model is shown to provide comparable performance to other state-of-the-art models in terms of bias, variance and computational requirement in short-term financial prediction. © 2005 IEEE.
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