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Predictive modeling of Tesla stock prices using AR, MA, ARIMA, and LSTM models. This project leverages Python for time series analysis, statistical forecasting, and deep learning techniques.

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SOSPETER03/tesla-stock-forecasting

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Contributing to Tesla Stock Forecasting Project

Thank you for considering contributing to this project! We welcome all kinds of contributions including bug reports, feature suggestions, improvements to documentation, and code contributions.

📌 How to Contribute

1. Fork the Repository

Click on the "Fork" button at the top right of the GitHub repository.

2. Clone Your Fork

git clone https://github.com/YOUR_USERNAME/tesla-stock-forecasting.git
cd tesla-stock-forecasting

3. Create a New Branch

git checkout -b feature/your-feature-name

4. Make Your Changes

5. Commit and Push

git add .
git commit -m "Your detailed commit message"
git push origin feature/your-feature-name

6. Submit a Pull Request

Go to your fork on GitHub and click “New Pull Request.”

🧪 Code Style and Testing

  • Follow PEP8 guidelines for Python code.
  • Use meaningful variable and function names.
  • If adding new models or methods, please include test cases or evaluation metrics.

💬 Questions or Suggestions?

Feel free to open an issue for any questions, bugs, or feature requests.


Let’s make financial forecasting smarter — together! 🚀

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Predictive modeling of Tesla stock prices using AR, MA, ARIMA, and LSTM models. This project leverages Python for time series analysis, statistical forecasting, and deep learning techniques.

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