InvesTech

Welcome to the Real-Time Stock Price Prediction Web Application, InvesTech repository! This project hosts an intuitive web application that offers real-time stock price visualization and predictions using cutting-edge AI technologies. Built with React, Chart.js, and the integration of Machine Learning methods, this application provides a comprehensive platform for investors to make informed decisions and provide them with accurate forecasts.

💻 Live

Watch the live demo here: https://youtu.be/NRGSJnPG458

🚀 Highlights

• Live Price Tracking: Monitor live stock prices with real-time updates.
• ARIMA Model Integration: Utilize the power of the AutoRegressive Integrated Moving Average (ARIMA) model for precise stock price predictions.
• Enhanced Predictions: Our roadmap includes integrating sentiment analysis to further refine predictive accuracy.

⚡ Features

• Interactive chart visualization using Chart.js.
• Seamless integration of the ARIMA model for predictive insights.
• User-friendly interface designed for simplicity and efficiency.
• Ready for future sentiment analysis integration.

📂 Project Structure

• Investech-web/public: Static assets and HTML templates.
• Investech-web/src: React components and application logic.
• Investech-web/Components: Reusable UI components.
• Investech-web/Styles: Styling files for components.
• Investech-web/backend: API services for fetching data.
• Investech-Backend/mongoDbCli: Python scripts for web scraping and storing in MongoDB.
• Investech-Backend/model: Python scripts for Machine Learning and storing predictions in MongoDB.
• Investech-Backend/HistoricalData: CSV files for historical data of companies for predictions.

👷 Getting Started

1. Clone the repository: git clone https://github.com/zohairbadshah/InvesTech.git
2. Navigate to the project directory:
3. Install dependencies
4. Run the development server

💻 Tech Stack

• Frontend: React.js
• Backend: Node.js, Express
• Web Scraping(live data): Python (Selenium, WebDriver)
• MongoDB: Storing complex time series data and efficient querying

💡 Future Enhancements

• Sentiment Analysis Integration: Enhance prediction accuracy by integrating sentiment analysis. By analyzing news articles, social media trends, and financial reports, the application can take into account market sentiment to refine its predictions.
• Machine Learning Models: Experiment with other advanced machine learning models for stock price prediction, such as LSTM networks, hybrid models, or ensemble methods, to improve prediction accuracy.
• Provide advanced insights and analysis tools, such as moving averages, technical indicators, and pattern recognition, to help users make more sophisticated trading decisions.

💪 Contributions

Contributions are welcome! Feel free to open issues for discussions or submit pull requests to enhance the application's functionality and accuracy. Here is how you can contribute.

• Feature Enhancements: If you have ideas for new features, improved data visualization, or advanced prediction algorithms, open an issue to discuss your suggestions.

• Bug Fixes: If you encounter any bugs or unexpected behavior while using the application, submit detailed bug reports or pull requests to address the issues.

• Deployment Expertise: I am seeking help to streamline the deployment process. If you have experience with deploying web applications, your insights would be invaluable in making the application accessible to a wider audience.

To contribute, fork this repository, create a new branch for your work, make your changes, and submit a pull request. Let's collaborate to make this application even more powerful and user-friendly!

📄 License

This project is licensed under the MIT License.

Built with ❤️ by Zohair Badshah