Stock market prediction using natural language processing
This project proposes a stock market prediction framework based on Natural Language Processing (NLP) to improve investment decision-making, deal with the information. overload and empower real-time decision-making. The proposed system aims to significantly enhance prediction accuracy by leveraging N...
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| Format: | Final Year Project / Dissertation / Thesis |
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2024
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| Online Access: | http://eprints.utar.edu.my/7030/ http://eprints.utar.edu.my/7030/1/fyp_IB_2024_LWH.pdf |
| _version_ | 1848886830199472128 |
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| author | Looi, Wei Hung |
| author_facet | Looi, Wei Hung |
| author_sort | Looi, Wei Hung |
| building | UTAR Institutional Repository |
| collection | Online Access |
| description | This project proposes a stock market prediction framework based on Natural Language Processing (NLP) to improve investment decision-making, deal with the information. overload and empower real-time decision-making. The proposed system aims to significantly enhance prediction accuracy by leveraging NLP tools to analyse unstructured textual data and extract hidden signals that might influence stock prices. Additionally, the project contributes to the evolution of Financial Technology (FinTech) and provides innovative methods and techniques to market participants to remain competitive. The report outlines the project's scope and objectives, methods and technologies involved, and makes significant contributions to the evolution of NLP research. The project's success offers significant benefits to a wide range of financial stakeholders, such as investors, financial institutions, and academicians. |
| first_indexed | 2025-11-15T19:44:43Z |
| format | Final Year Project / Dissertation / Thesis |
| id | utar-7030 |
| institution | Universiti Tunku Abdul Rahman |
| institution_category | Local University |
| last_indexed | 2025-11-15T19:44:43Z |
| publishDate | 2024 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utar-70302025-02-27T07:31:49Z Stock market prediction using natural language processing Looi, Wei Hung T Technology (General) This project proposes a stock market prediction framework based on Natural Language Processing (NLP) to improve investment decision-making, deal with the information. overload and empower real-time decision-making. The proposed system aims to significantly enhance prediction accuracy by leveraging NLP tools to analyse unstructured textual data and extract hidden signals that might influence stock prices. Additionally, the project contributes to the evolution of Financial Technology (FinTech) and provides innovative methods and techniques to market participants to remain competitive. The report outlines the project's scope and objectives, methods and technologies involved, and makes significant contributions to the evolution of NLP research. The project's success offers significant benefits to a wide range of financial stakeholders, such as investors, financial institutions, and academicians. 2024-06 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/7030/1/fyp_IB_2024_LWH.pdf Looi, Wei Hung (2024) Stock market prediction using natural language processing. Final Year Project, UTAR. http://eprints.utar.edu.my/7030/ |
| spellingShingle | T Technology (General) Looi, Wei Hung Stock market prediction using natural language processing |
| title | Stock market prediction using natural language processing |
| title_full | Stock market prediction using natural language processing |
| title_fullStr | Stock market prediction using natural language processing |
| title_full_unstemmed | Stock market prediction using natural language processing |
| title_short | Stock market prediction using natural language processing |
| title_sort | stock market prediction using natural language processing |
| topic | T Technology (General) |
| url | http://eprints.utar.edu.my/7030/ http://eprints.utar.edu.my/7030/1/fyp_IB_2024_LWH.pdf |