Bursa stock recommender using technical analysis

Jee, Jia Bin (2025) Bursa stock recommender using technical analysis. Final Year Project, UTAR.

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Abstract

Investing in the stock market can be an effective strategy for wealth creation and financial security. However, current stock recommendation systems often lack user-centric features such as personalized insights and effective communication channels for investors. These limitations become challenges for novice investors in navigating financial data and making informed decisions. This project introduces Bursa Stock Recommender, a stock recommendation application that is designed to simplify the process of selecting a stock through financial performance analysis and technical indicators. This application tailored investment recommendations by leveraging historical financial data and other important metrics such as cash flow, price-to-earnings ratio, and dividend yield. It also incorporates advance charting tools for expert investors while maintaining the simplicity of this application for beginners through a user-friendly interface and predefined screens. A key feature of this application is the inclusion of a collaborative communication platform, which enables investors to share insights, discuss strategies, and exchange ideas. Additional functions such as risk management tools, customizable watchlists, and alert systems are also provided to enhance decision-making capabilities. In short, the core value of this project is to promote broader participation in the stock market and empower investors to reach their financial goals.

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