Adaptive Selection Of KLSE Stocks Using Neural Networks

Stock is becoming a significant investment tools that contributes towards Malaysia economic growth. Thus it is vital to increase investor's confidence in the Malaysia stock market. In this era of Information Age, artificial intelligence is applied to develop sound investment analysis tools in s...

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Main Author:	Kok, Chee Foong
Format:	Thesis
Language:	eng eng
Published:	2002
Subjects:	QA76 Computer software
Online Access:	https://etd.uum.edu.my/566/1/KOK_CHEE_FOONG.pdf https://etd.uum.edu.my/566/2/KOK_CHEE_FOONG.pdf
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id	my-uum-etd.566
record_format	uketd_dc
spelling	my-uum-etd.5662013-07-24T12:07:53Z Adaptive Selection Of KLSE Stocks Using Neural Networks 2002 Kok, Chee Foong Sekolah Siswazah Sekolah Siswazah QA76 Computer software Stock is becoming a significant investment tools that contributes towards Malaysia economic growth. Thus it is vital to increase investor's confidence in the Malaysia stock market. In this era of Information Age, artificial intelligence is applied to develop sound investment analysis tools in selecting winning Malaysia stocks. Hence in this study, neural network technology is deployed to build an adaptive neural net trading system, specifically adopting the multilayer feedforward network with backpropagation learning algorithm. A 22-18-2-network architecture of a prediction model is derived from the developed network simulator to predict the following quarter stock price change, of twenty publicly traded Malaysian companies. A promising classification competency of 80 percent correctness is recorded after the network is iteratively trained for 6000 epochs. This study also indicates that the neural network generated forecasting model is capable of outperforming the statistical model, as recorded by 80 percent neural network accuracy versus 77.3 percent binary logistic regression accuracy. The findings conclude that the neural forecasting ability could be further enhanced. Future research could incorporate technical analyst approach for a comprehensive stock valuation and also integrates with fuzzy technology to handle imprecise data. 2002 Thesis https://etd.uum.edu.my/566/ https://etd.uum.edu.my/566/1/KOK_CHEE_FOONG.pdf application/pdf eng validuser https://etd.uum.edu.my/566/2/KOK_CHEE_FOONG.pdf application/pdf eng public masters masters Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
topic	QA76 Computer software
spellingShingle	QA76 Computer software Kok, Chee Foong Adaptive Selection Of KLSE Stocks Using Neural Networks
description	Stock is becoming a significant investment tools that contributes towards Malaysia economic growth. Thus it is vital to increase investor's confidence in the Malaysia stock market. In this era of Information Age, artificial intelligence is applied to develop sound investment analysis tools in selecting winning Malaysia stocks. Hence in this study, neural network technology is deployed to build an adaptive neural net trading system, specifically adopting the multilayer feedforward network with backpropagation learning algorithm. A 22-18-2-network architecture of a prediction model is derived from the developed network simulator to predict the following quarter stock price change, of twenty publicly traded Malaysian companies. A promising classification competency of 80 percent correctness is recorded after the network is iteratively trained for 6000 epochs. This study also indicates that the neural network generated forecasting model is capable of outperforming the statistical model, as recorded by 80 percent neural network accuracy versus 77.3 percent binary logistic regression accuracy. The findings conclude that the neural forecasting ability could be further enhanced. Future research could incorporate technical analyst approach for a comprehensive stock valuation and also integrates with fuzzy technology to handle imprecise data.
format	Thesis
qualification_name	masters
qualification_level	Master's degree
author	Kok, Chee Foong
author_facet	Kok, Chee Foong
author_sort	Kok, Chee Foong
title	Adaptive Selection Of KLSE Stocks Using Neural Networks
title_short	Adaptive Selection Of KLSE Stocks Using Neural Networks
title_full	Adaptive Selection Of KLSE Stocks Using Neural Networks
title_fullStr	Adaptive Selection Of KLSE Stocks Using Neural Networks
title_full_unstemmed	Adaptive Selection Of KLSE Stocks Using Neural Networks
title_sort	adaptive selection of klse stocks using neural networks
granting_institution	Universiti Utara Malaysia
granting_department	Sekolah Siswazah
publishDate	2002
url	https://etd.uum.edu.my/566/1/KOK_CHEE_FOONG.pdf https://etd.uum.edu.my/566/2/KOK_CHEE_FOONG.pdf
_version_	1747826945172701184

Adaptive Selection Of KLSE Stocks Using Neural Networks

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