Stock market prediction using artificial intelligence
This work is divided into two sections, the first of which is a natural language processing module that analyzes sentiment for corresponding financial news, and the second of which is a stock prediction module that uses the output of the first module and past stock data to forecast future stock pric...
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| Other Authors: | |
| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/156132 |
| _version_ | 1826121423604678656 |
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| author | Zhang, Yiran |
| author2 | Mohammed Yakoob Siyal |
| author_facet | Mohammed Yakoob Siyal Zhang, Yiran |
| author_sort | Zhang, Yiran |
| collection | NTU |
| description | This work is divided into two sections, the first of which is a natural language processing module that analyzes sentiment for corresponding financial news, and the second of which is a stock prediction module that uses the output of the first module and past stock data to forecast future stock prices. This structure can more precisely forecast the stock's future trajectory. The natural language portion is built based on a recurrent neural network, which helps understand the link between nearby inputs better and is more similar to how humans interpret language. To increase the accuracy of the system, the stock prediction module uses the support vector machine method and mixes several kernel functions.
This study builds a stock prediction network structure for a series of tests using the Python language on the Linux 16.4 environment. Although our experiment only employs a restricted number of stocks, it nevertheless yields competitive prediction results, which supports the conclusion analysis of this study. |
| first_indexed | 2024-10-01T05:32:24Z |
| format | Thesis-Master by Coursework |
| id | ntu-10356/156132 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:32:24Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1561322023-07-04T17:49:32Z Stock market prediction using artificial intelligence Zhang, Yiran Mohammed Yakoob Siyal School of Electrical and Electronic Engineering EYAKOOB@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence This work is divided into two sections, the first of which is a natural language processing module that analyzes sentiment for corresponding financial news, and the second of which is a stock prediction module that uses the output of the first module and past stock data to forecast future stock prices. This structure can more precisely forecast the stock's future trajectory. The natural language portion is built based on a recurrent neural network, which helps understand the link between nearby inputs better and is more similar to how humans interpret language. To increase the accuracy of the system, the stock prediction module uses the support vector machine method and mixes several kernel functions. This study builds a stock prediction network structure for a series of tests using the Python language on the Linux 16.4 environment. Although our experiment only employs a restricted number of stocks, it nevertheless yields competitive prediction results, which supports the conclusion analysis of this study. Master of Science (Signal Processing) 2022-04-05T05:11:19Z 2022-04-05T05:11:19Z 2022 Thesis-Master by Coursework Zhang, Y. (2022). Stock market prediction using artificial intelligence. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156132 https://hdl.handle.net/10356/156132 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Zhang, Yiran Stock market prediction using artificial intelligence |
| title | Stock market prediction using artificial intelligence |
| title_full | Stock market prediction using artificial intelligence |
| title_fullStr | Stock market prediction using artificial intelligence |
| title_full_unstemmed | Stock market prediction using artificial intelligence |
| title_short | Stock market prediction using artificial intelligence |
| title_sort | stock market prediction using artificial intelligence |
| topic | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence |
| url | https://hdl.handle.net/10356/156132 |
| work_keys_str_mv | AT zhangyiran stockmarketpredictionusingartificialintelligence |