Deep GRU neural networks for Apple stock price prediction

The stock market's ever-evolving landscape is characterized by its capricious nature, rendering the task of stock price prediction highly intricate. The intertwining variables such as global political scenarios, company performance, and public sentiment contribute to the volatility of stock pri...

全面介紹

Saved in:
書目詳細資料
主要作者: Ji, YiJun
其他作者: Wang Lipo
格式: Final Year Project
語言:English
出版: Nanyang Technological University 2023
主題:
在線閱讀:https://hdl.handle.net/10356/172724
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
id sg-ntu-dr.10356-172724
record_format dspace
spelling sg-ntu-dr.10356-1727242023-12-22T15:41:58Z Deep GRU neural networks for Apple stock price prediction Ji, YiJun Wang Lipo School of Electrical and Electronic Engineering ELPWang@ntu.edu.sg Engineering::Electrical and electronic engineering::Computer hardware, software and systems The stock market's ever-evolving landscape is characterized by its capricious nature, rendering the task of stock price prediction highly intricate. The intertwining variables such as global political scenarios, company performance, and public sentiment contribute to the volatility of stock prices, making predictions even more sophisticated. However, the rapidly advancing realm of machine learning and deep learning like Gated Recurrent Unit (GRU) has begun to hold significant promise in tackling these challenges. This project aims to use GRU network to predict gold price using its historic value and evaluating its accuracy with other traditional neural networks. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-12-19T05:14:21Z 2023-12-19T05:14:21Z 2023 Final Year Project (FYP) Ji, Y. (2023). Deep GRU neural networks for Apple stock price prediction. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/172724 https://hdl.handle.net/10356/172724 en A3313-222 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::Computer hardware, software and systems
spellingShingle Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Ji, YiJun
Deep GRU neural networks for Apple stock price prediction
description The stock market's ever-evolving landscape is characterized by its capricious nature, rendering the task of stock price prediction highly intricate. The intertwining variables such as global political scenarios, company performance, and public sentiment contribute to the volatility of stock prices, making predictions even more sophisticated. However, the rapidly advancing realm of machine learning and deep learning like Gated Recurrent Unit (GRU) has begun to hold significant promise in tackling these challenges. This project aims to use GRU network to predict gold price using its historic value and evaluating its accuracy with other traditional neural networks.
author2 Wang Lipo
author_facet Wang Lipo
Ji, YiJun
format Final Year Project
author Ji, YiJun
author_sort Ji, YiJun
title Deep GRU neural networks for Apple stock price prediction
title_short Deep GRU neural networks for Apple stock price prediction
title_full Deep GRU neural networks for Apple stock price prediction
title_fullStr Deep GRU neural networks for Apple stock price prediction
title_full_unstemmed Deep GRU neural networks for Apple stock price prediction
title_sort deep gru neural networks for apple stock price prediction
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/172724
_version_ 1787136423043792896