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A comprehensive application that analyzes real-time market data to provide stock trend predictions, company insights, and risk assessments. It leverages advanced financial algorithms and machine learning models to deliver explainable, actionable investment suggestions, enabling users to make informed portfolio decisions with confidence.

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hreger/stockintel

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🚀 StockIntel - Your AI-Powered Stock Market Intelligence Platform

Python Version License Status

StockIntel is your all-in-one AI trading assistant, combining real-time market data, advanced analytics, and machine learning to empower smarter investment decisions. Whether you're a seasoned trader or just starting out, StockIntel delivers actionable insights and a seamless user experience.


🌟 Features

  • Real-time market data visualization
  • Technical analysis with indicators (RSI, MACD, Bollinger Bands)
  • Portfolio tracking and performance analysis
  • Market signals and alerts
  • News and announcements integration

Screenshots

Home Page

Home Page

Additional Features

Other Features

Installation

# Clone the repository
git clone https://github.com/hreger/stockintel.git
cd stockintel

# Install dependencies
pip install -r requirements.txt

# Set up environment variables
# Create a .env file with your API keys and database configuration

# Run the application
python flask_app.py

Technologies Used

  • Flask - Web framework
  • Matplotlib/Seaborn - Data visualization
  • Pandas - Data manipulation
  • Alpha Vantage API - Market data
  • PostgreSQL - Database
  • Docker - Containerization
  • Kafka - Data streaming (optional)
  • FastAPI - Prediction service
  • Dash - Web application
  • Scikit-learn - Machine learning
  • Requests - HTTP requests
  • BeautifulSoup - Web scraping

📁 Project Structure

stockintel/
├── data_ingestion/          # Data collection and processing
│   ├── kafka_producer.py    # Kafka producer for stock data (optional)
│   ├── kafka_consumer.py    # Kafka consumer for data processing (optional)
│   ├── init_db.py           # Database initialization
│   └── check_data.py        # Data verification
├── prediction_service/      # Machine learning predictions
│   ├── prediction_service.py # FastAPI service
│   ├── models/              # ML models
│   └── utils/               # Helper functions
├── dashboard/               # Web interface
│   ├── app.py               # Dash application
│   ├── components/          # UI components
│   └── layouts/             # Page layouts
├── portfolio/               # Portfolio management
│   └── portfolio_analyzer.py # Portfolio analysis
├── backtesting/             # Strategy testing
│   └── strategy_tester.py   # Backtesting engine
├── scanner/                 # Market scanning
│   └── market_scanner.py    # Opportunity scanner
├── requirements.txt         # Project dependencies
└── .env                     # Environment variables

🤝 Contributing

We love contributions! Here's how you can help:

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/AmazingFeature)
  3. Commit your changes (git commit -m 'Add some AmazingFeature')
  4. Push to the branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

💬 Support

Got questions? We're here to help!

🙏 Acknowledgments

A big thank you to:

  • Alpha Vantage for providing market data
  • PostgreSQL for reliable data storage
  • The amazing open-source community for their contributions

Made with ❤️ by the StockIntel Team

© 2024 StockIntel. All rights reserved.

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A comprehensive application that analyzes real-time market data to provide stock trend predictions, company insights, and risk assessments. It leverages advanced financial algorithms and machine learning models to deliver explainable, actionable investment suggestions, enabling users to make informed portfolio decisions with confidence.

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