A web application for option pricing using Physics-Informed Neural Networks (PINNs) implemented in PyTorch and Streamlit.

• Black-Scholes model pricing
• Heston model pricing
• Interactive UI with real-time calculations
• Visual representation of pricing equations

.
├── app.py              # Main Streamlit application
├── requirements.txt    # Python dependencies
├── Procfile           # Deployment configuration
├── src/
│   ├── models/        # Neural network model definitions
│   └── utils/         # Utility functions
├── saved_models/      # Trained model weights
└── results/           # Equation images and results

1. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

2. Install dependencies:

pip install -r requirements.txt

3. Run the app:

streamlit run app.py

This app can be deployed on various platforms:

1. Push your code to GitHub
2. Go to share.streamlit.io
3. Connect your GitHub repository
4. Deploy!

1. Create a Heroku account
2. Install Heroku CLI
3. Run:

heroku create your-app-name
git push heroku main

• Python 3.8+
• PyTorch
• Streamlit
• NumPy
• Matplotlib
• Pillow

MIT License