
Proceedings Paper
Wavelet neural networks for stock tradingFormat | Member Price | Non-Member Price |
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Paper Abstract
This paper explores the application of a wavelet neural network (WNN), whose hidden layer is comprised of neurons
with adjustable wavelets as activation functions, to stock prediction. We discuss some basic rationales behind technical
analysis, and based on which, inputs of the prediction system are carefully selected. This system is tested on Istanbul
Stock Exchange National 100 Index and compared with traditional neural networks. The results show that the WNN can
achieve very good prediction accuracy.
Paper Details
Date Published: 29 May 2013
PDF: 10 pages
Proc. SPIE 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI, 87500A (29 May 2013); doi: 10.1117/12.2018040
Published in SPIE Proceedings Vol. 8750:
Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI
Harold H. Szu, Editor(s)
PDF: 10 pages
Proc. SPIE 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI, 87500A (29 May 2013); doi: 10.1117/12.2018040
Show Author Affiliations
Tianxing Zheng, Nanyang Technological Univ. (Singapore)
Kamaladdin Fataliyev, Nanyang Technological Univ. (Singapore)
Kamaladdin Fataliyev, Nanyang Technological Univ. (Singapore)
Lipo Wang, Nanyang Technological Univ. (Singapore)
Published in SPIE Proceedings Vol. 8750:
Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI
Harold H. Szu, Editor(s)
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