Akshat111111 / Hedging-of-Financial-Derivatives

This strategy works for every market condition irrespective of the movement
BSD 3-Clause "New" or "Revised" License
77 stars 100 forks source link
collaborate communityexchange data finance financial-analysis git github hedging monte-carlo-simulation

Hedging of Financial Derivative πŸ’Ό

Welcome to Hedging of Financial Derivative! πŸ“ˆ

This project focuses on implementing a robust trading strategy using statistical arbitrage and convergence techniques for hedging financial derivatives.

Video Description of the Project and Repository Overview

https://github.com/JagjeetChauhan/Hedging-of-Financial-Derivatives/assets/98844703/52dd14f7-be7f-4684-a148-3c6192a735b7

Overview πŸ“Š

The project utilizes:

Getting Started πŸš€

To contribute to this project, follow these steps:

  1. Fork the repository on GitHub.
  2. Clone the forked project to your local machine: git clone <forked_repo_url>
  3. Create a new branch for your work: git checkout -b your-branch-name
  4. Make changes and improvements in your branch.
  5. Commit your changes: git commit -m 'Add your descriptive commit message'
  6. Push your changes to your forked repository: git push origin your-branch-name
  7. Submit a Pull Request (PR) to the main repository for review.

Ways to Contribute πŸ› οΈ

We welcome contributions in various forms, such as:

Our Contributors

Thanks to These Amazing People :grinning:

Code Guidelines πŸ“

Please adhere to proper coding standards and conventions:

Issue Tracking πŸ”

We use GitHub issues to manage tasks. Feel free to open an issue for bugs, suggestions, or discussions related to the project.

Code of Conduct 🀝

We maintain a Code of Conduct to ensure a welcoming environment for all contributors. Please review and follow our Code of Conduct.

Thank you for your interest in contributing to the Financial Derivative Hedging Project! πŸ™Œ

Example Strategy πŸ“Š

Hedging is a market-neutral trading strategy that enables traders to profit from virtually any market conditions: uptrend, downtrend, or sideways movement. This strategy is categorized as a statistical arbitrage and convergence trading strategy.

How It Works:

  1. Cointegration Analysis: Identify cointegrated pairs of stocks within a specified time interval.
  2. Spread Calculation: Calculate the spread of the cointegrated pairs using linear regression.
  3. Signal Generation: Generate trading signals based on Z-score normalization.
    • Go "Long" the spread whenever the Z-score is below -1.0
    • Go "Short" the spread when the Z-score is above 1.0
    • Exit positions when the Z-score approaches zero
  4. Backtesting: Test the strategy on historical data to evaluate performance.
  5. Portfolio Returns: Calculate and analyze the returns of the portfolio based on the strategy.

πŸ’ͺ Thanks to all Contributors

Thanks to all the contributors for helping this project grow! 🍻

πŸ™ Support

Don't forget to leave a star ⭐ for this project!

Crafted with β™₯ by @Akshat111111

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