A comprehensive stock tracking and analysis platform built as a DBMS class project. We blend advanced machine learning with real-time stock data and news sentiment for insightful financial predictions.
StockTrack is designed to provide comprehensive financial information, news, and stock price data for various companies. Our platform integrates advanced machine learning with robust database management to deliver accurate predictions and real-time insights.
What sets us apart is our XGBoost prediction model achieving 93% accuracy in stock price predictions, combined with sentiment analysis from major financial news sources.
Implemented using XGBoost for stock price prediction, with feature engineering and real-time data processing capabilities.
Built on advanced DBMS principles with efficient query optimization and real-time data synchronization. The system supports robust stock data tracking and analysis.
Developed with React for a dynamic user interface, ensuring responsiveness and interactive experiences for users across all devices.
This project was developed as part of a DBMS class assignment, aiming to demonstrate practical application of database management principles while creating a useful tool for investors and financial analysts.
The integration of machine learning and sentiment analysis showcases how modern technologies can be combined with traditional database systems to create powerful, user-friendly applications. The goal is to enhance financial decision-making processes by providing actionable insights.