NDLI: Financial Prediction of Major Indices using Computational Efficient Artificial Neural Networks

Content Provider	IEEE Xplore Digital Library
Author	Patra, J.C. Weineng Lim Meher, P.K. Ee Luang Ang
Copyright Year	2006
Description	Author affiliation: Nanyang Technol. Univ., Singapore (Patra, J.C.; Weineng Lim; Meher, P.K.; Ee Luang Ang)
Abstract	Two computational efficient artificial neural networks (ANNs) for the prediction of major financial indices are proposed. First, we propose a single layer functional link artificial neural network (FLANN) for this purpose. FLANN has a simple structure in which the nonlinearity is introduced by the functional expansion of the input pattern using trigonometric polynomials. The second ANN proposed is a Chebyshev neural network (chNN) in which the functional expansion is carried out using Chebyshev polynomials. Performance comparison of the two ANNs with regards to a multilayer perceptron (MLP) were carried out through extensive computer simulations. It is shown that the proposed ANNs outperform the MLP for the prediction of the three financial indices.
Starting Page	2114
Ending Page	2120
File Size	891946
Page Count	7
File Format	PDF
ISBN	0780394909
DOI	10.1109/IJCNN.2006.246982
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-07-16
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computational efficiency Artificial neural networks Chebyshev approximation Autoregressive processes Polynomials Multilayer perceptrons Application software Predictive models Computer simulation Linear regression
Content Type	Text
Resource Type	Article

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