Wavelet neural networks for stock trading

Tianxing Zheng; Kamaladdin Fataliyev; Lipo Wang

doi:10.1117/12.2018040

29 May 2013 Wavelet neural networks for stock trading

Tianxing Zheng, Kamaladdin Fataliyev, Lipo Wang

Proceedings Volume 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI; 87500A (2013) https://doi.org/10.1117/12.2018040
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

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.

Citation Download Citation

Tianxing Zheng, Kamaladdin Fataliyev, and Lipo Wang "Wavelet neural networks for stock trading", Proc. SPIE 8750, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XI, 87500A (29 May 2013); https://doi.org/10.1117/12.2018040

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