Stock trading and prediction using multi-layer perceptron neural networks

Stock price prediction has always been a choice problem to solve for stock enthusiast and investors alike. Everyone would like to remove the shade of uncertainty over the stock’s future prices and trends. Tackling this problem with neural networks has been done by many for decades. This project appl...

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Bibliographic Details
Main Author:	Yip, Jia Meng
Other Authors:	Wang Lipo
Format:	Final Year Project
Language:	English
Published:	2016
Subjects:	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Online Access:	http://hdl.handle.net/10356/67849
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-67849
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spelling	sg-ntu-dr.10356-678492023-07-07T16:09:10Z Stock trading and prediction using multi-layer perceptron neural networks Yip, Jia Meng Wang Lipo School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Stock price prediction has always been a choice problem to solve for stock enthusiast and investors alike. Everyone would like to remove the shade of uncertainty over the stock’s future prices and trends. Tackling this problem with neural networks has been done by many for decades. This project applies a multi-layer perceptron model with a moving window simulation to the stock price prediction problem, based on a paper written by Turchenko et al. Various experiments were carried out to determine the parameters of a better model with higher accuracy. Comparisons on the influence of each parameter over the results were done in later parts of the report. Bachelor of Engineering 2016-05-23T02:00:15Z 2016-05-23T02:00:15Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/67849 en Nanyang Technological University 116 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::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Yip, Jia Meng Stock trading and prediction using multi-layer perceptron neural networks
description	Stock price prediction has always been a choice problem to solve for stock enthusiast and investors alike. Everyone would like to remove the shade of uncertainty over the stock’s future prices and trends. Tackling this problem with neural networks has been done by many for decades. This project applies a multi-layer perceptron model with a moving window simulation to the stock price prediction problem, based on a paper written by Turchenko et al. Various experiments were carried out to determine the parameters of a better model with higher accuracy. Comparisons on the influence of each parameter over the results were done in later parts of the report.
author2	Wang Lipo
author_facet	Wang Lipo Yip, Jia Meng
format	Final Year Project
author	Yip, Jia Meng
author_sort	Yip, Jia Meng
title	Stock trading and prediction using multi-layer perceptron neural networks
title_short	Stock trading and prediction using multi-layer perceptron neural networks
title_full	Stock trading and prediction using multi-layer perceptron neural networks
title_fullStr	Stock trading and prediction using multi-layer perceptron neural networks
title_full_unstemmed	Stock trading and prediction using multi-layer perceptron neural networks
title_sort	stock trading and prediction using multi-layer perceptron neural networks
publishDate	2016
url	http://hdl.handle.net/10356/67849
_version_	1772825372687073280

Stock trading and prediction using multi-layer perceptron neural networks

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