Stock market prediction using natural language processing

Looi, Wei Hung (2024) Stock market prediction using natural language processing. Final Year Project, UTAR.

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Abstract

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.

Item Type:	Final Year Project / Dissertation / Thesis (Final Year Project)
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Information and Communication Technology > Bachelor of Information Systems (Honours) Business Information Systems
Depositing User:	ML Main Library
Date Deposited:	27 Feb 2025 15:31
Last Modified:	27 Feb 2025 15:31
URI:	http://eprints.utar.edu.my/id/eprint/7030

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