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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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2021
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/149917 |
| _version_ | 1826121858821390336 |
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| author | Tan, Nigel Jun Wen |
| author2 | Wang Lipo |
| author_facet | Wang Lipo Tan, Nigel Jun Wen |
| author_sort | Tan, Nigel Jun Wen |
| collection | NTU |
| 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. |
| first_indexed | 2024-10-01T05:39:02Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/149917 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:39:02Z |
| publishDate | 2021 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-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 |
| spellingShingle | Engineering::Electrical and electronic engineering Tan, Nigel Jun Wen Stock trading and prediction using weakly supervised learning |
| title | 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_short | Stock trading and prediction using weakly supervised learning |
| title_sort | stock trading and prediction using weakly supervised learning |
| topic | Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/149917 |
| work_keys_str_mv | AT tannigeljunwen stocktradingandpredictionusingweaklysupervisedlearning |