Wavelet neural networks for stock trading and prediction

The main aim of this report is to study the topic of Wavelet Neural Networks, and see how they are useful for stock market non-linear time series prediction. To do this, the theories of wavelet analysis, neuron network, and the combination of WNN have been studied. Following that, some key considera...

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Main Author: Xing, Xiaoyang.
Other Authors: Wang Lipo
Format: Final Year Project
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/54400
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-544002023-07-07T16:38:55Z Wavelet neural networks for stock trading and prediction Xing, Xiaoyang. Wang Lipo School of Electrical and Electronic Engineering DRNTU::Engineering The main aim of this report is to study the topic of Wavelet Neural Networks, and see how they are useful for stock market non-linear time series prediction. To do this, the theories of wavelet analysis, neuron network, and the combination of WNN have been studied. Following that, some key considerations in constructing the WNN found out during the project and literature reading are discussed. This provides sufficient background to implement a WNN model and conduct testing on S&P 500 index. The experiment result shows that thought the prediction ability of WNN is powerful, its performance is not stable. Bachelor of Engineering 2013-06-20T01:36:41Z 2013-06-20T01:36:41Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/54400 en Nanyang Technological University 67 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Xing, Xiaoyang.
Wavelet neural networks for stock trading and prediction
description The main aim of this report is to study the topic of Wavelet Neural Networks, and see how they are useful for stock market non-linear time series prediction. To do this, the theories of wavelet analysis, neuron network, and the combination of WNN have been studied. Following that, some key considerations in constructing the WNN found out during the project and literature reading are discussed. This provides sufficient background to implement a WNN model and conduct testing on S&P 500 index. The experiment result shows that thought the prediction ability of WNN is powerful, its performance is not stable.
author2 Wang Lipo
author_facet Wang Lipo
Xing, Xiaoyang.
format Final Year Project
author Xing, Xiaoyang.
author_sort Xing, Xiaoyang.
title Wavelet neural networks for stock trading and prediction
title_short Wavelet neural networks for stock trading and prediction
title_full Wavelet neural networks for stock trading and prediction
title_fullStr Wavelet neural networks for stock trading and prediction
title_full_unstemmed Wavelet neural networks for stock trading and prediction
title_sort wavelet neural networks for stock trading and prediction
publishDate 2013
url http://hdl.handle.net/10356/54400
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