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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Bibliographic Details
Main Author: Looi, Wei Hung
Format: Final Year Project / Dissertation / Thesis
Published: 2024
Subjects:
Online Access:http://eprints.utar.edu.my/7030/
http://eprints.utar.edu.my/7030/1/fyp_IB_2024_LWH.pdf
Description
Summary: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.