Predictive analysis of stock prices using gated recurrent neural network
Stock price prediction is a popular and prevalent field of study due the large potential profits involved. However, the stock market is difficult to predict due to the many unknown and unpredictable factors affecting the market as well as random noise. Machine learning has shown great promise in man...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/149820 |
| _version_ | 1824454422216835072 |
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| author | Chew, Athena Yee Jun |
| author2 | Wong Jia Yiing, Patricia |
| author_facet | Wong Jia Yiing, Patricia Chew, Athena Yee Jun |
| author_sort | Chew, Athena Yee Jun |
| collection | NTU |
| description | Stock price prediction is a popular and prevalent field of study due the large potential profits involved. However, the stock market is difficult to predict due to the many unknown and unpredictable factors affecting the market as well as random noise. Machine learning has shown great promise in many applications and in particular, recurrent neural networks (RNN) have shown promise in time series predictions. This project will focus on gated RNNs such as LSTMs and GRUs and the on the stock prices of the largest companies in the banking industry on the Singapore stock exchange. Daily trading data, technical indicators and macroeconomic variables would be mined, calculated fed to the machine learning models to predict stock prices. Different models of different types are evaluated for their suitability for stock price prediction of Singapore bank. The results show that a GRU model with auto-regression was the most successful in predicting stock price. |
| first_indexed | 2025-02-19T03:22:03Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/149820 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:22:03Z |
| publishDate | 2021 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1498202023-07-07T17:55:02Z Predictive analysis of stock prices using gated recurrent neural network Chew, Athena Yee Jun Wong Jia Yiing, Patricia School of Electrical and Electronic Engineering EJYWong@ntu.edu.sg Engineering::Electrical and electronic engineering Stock price prediction is a popular and prevalent field of study due the large potential profits involved. However, the stock market is difficult to predict due to the many unknown and unpredictable factors affecting the market as well as random noise. Machine learning has shown great promise in many applications and in particular, recurrent neural networks (RNN) have shown promise in time series predictions. This project will focus on gated RNNs such as LSTMs and GRUs and the on the stock prices of the largest companies in the banking industry on the Singapore stock exchange. Daily trading data, technical indicators and macroeconomic variables would be mined, calculated fed to the machine learning models to predict stock prices. Different models of different types are evaluated for their suitability for stock price prediction of Singapore bank. The results show that a GRU model with auto-regression was the most successful in predicting stock price. Bachelor of Engineering (Electrical and Electronic Engineering) 2021-06-09T06:07:05Z 2021-06-09T06:07:05Z 2021 Final Year Project (FYP) Chew, A. Y. J. (2021). Predictive analysis of stock prices using gated recurrent neural network. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/149820 https://hdl.handle.net/10356/149820 en A1176-201 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Electrical and electronic engineering Chew, Athena Yee Jun Predictive analysis of stock prices using gated recurrent neural network |
| title | Predictive analysis of stock prices using gated recurrent neural network |
| title_full | Predictive analysis of stock prices using gated recurrent neural network |
| title_fullStr | Predictive analysis of stock prices using gated recurrent neural network |
| title_full_unstemmed | Predictive analysis of stock prices using gated recurrent neural network |
| title_short | Predictive analysis of stock prices using gated recurrent neural network |
| title_sort | predictive analysis of stock prices using gated recurrent neural network |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/149820 |
| work_keys_str_mv | AT chewathenayeejun predictiveanalysisofstockpricesusinggatedrecurrentneuralnetwork |