Stock trading and prediction using weakly supervised learning

This project attempts to use both technical analysis and sentimental analysis to predict stock market prices. The method in this published paper, Deep Learning Approach for Short-Term Stock Trends Prediction Based on Two-Stream Gated Recurrent Unit Network, will be replicated. After which, modificat...

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Bibliographic Details
Main Author:	Tan, Nigel Jun Wen
Other Authors:	Wang Lipo
Format:	Final Year Project
Language:	English
Published:	Nanyang Technological University 2021
Subjects:	Engineering::Electrical and electronic engineering
Online Access:	https://hdl.handle.net/10356/149917
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Institution:	Nanyang Technological University
Language:	English

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spelling	sg-ntu-dr.10356-1499172023-07-07T18:29:30Z Stock trading and prediction using weakly supervised learning Tan, Nigel Jun Wen Wang Lipo School of Electrical and Electronic Engineering ELPWang@ntu.edu.sg Engineering::Electrical and electronic engineering This project attempts to use both technical analysis and sentimental analysis to predict stock market prices. The method in this published paper, Deep Learning Approach for Short-Term Stock Trends Prediction Based on Two-Stream Gated Recurrent Unit Network, will be replicated. After which, modifications will be made to try to improve on the results achieved in the published paper. Historical price of the S&P500 will be used along with news article from Bloomberg and Reuters. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-06-10T14:42:03Z 2021-06-10T14:42:03Z 2021 Final Year Project (FYP) Tan, N. J. W. (2021). Stock trading and prediction using weakly supervised learning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149917 https://hdl.handle.net/10356/149917 en application/pdf Nanyang Technological University
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	Engineering::Electrical and electronic engineering
spellingShingle	Engineering::Electrical and electronic engineering Tan, Nigel Jun Wen Stock trading and prediction using weakly supervised learning
description	This project attempts to use both technical analysis and sentimental analysis to predict stock market prices. The method in this published paper, Deep Learning Approach for Short-Term Stock Trends Prediction Based on Two-Stream Gated Recurrent Unit Network, will be replicated. After which, modifications will be made to try to improve on the results achieved in the published paper. Historical price of the S&P500 will be used along with news article from Bloomberg and Reuters.
author2	Wang Lipo
author_facet	Wang Lipo Tan, Nigel Jun Wen
format	Final Year Project
author	Tan, Nigel Jun Wen
author_sort	Tan, Nigel Jun Wen
title	Stock trading and prediction using weakly supervised learning
title_short	Stock trading and prediction using weakly supervised learning
title_full	Stock trading and prediction using weakly supervised learning
title_fullStr	Stock trading and prediction using weakly supervised learning
title_full_unstemmed	Stock trading and prediction using weakly supervised learning
title_sort	stock trading and prediction using weakly supervised learning
publisher	Nanyang Technological University
publishDate	2021
url	https://hdl.handle.net/10356/149917
_version_	1772827147818237952

Stock trading and prediction using weakly supervised learning

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