Skip to content

Bitcoin Prevision using Machine Learning and allocation strategy

Notifications You must be signed in to change notification settings

Quacox/Bitcoin-Prevision

Repository files navigation

Bitcoin-Prevision

Overview

Welcome to our latest research project, conducted by Mathieu Laruelle and Maxime Le Floch as part of our Master 1 studies at GINJER AM and ESILV - Ecole Supérieure d'Ingénieurs Léonard de Vinci. This project aims to uncover the behavior of Bitcoin, the king of cryptocurrency.

Research Objective

Our primary goal was to understand the underlying mechanisms driving Bitcoin's returns. We analyzed over 60 datasets from Bloomberg and Coin Metrics, using advanced machine learning algorithms to predict Bitcoin's returns from September 2014 to December 2023.

Key Findings

Our analysis revealed crucial performance indicators that informed the development of a dynamic investment strategy. By confirming causal relationships similar to Granger causality between significant features and Bitcoin's returns, we provide investors with tools to reduce volatility and seize market opportunities through three distinct investment strategies.

Conclusion

We hope our research paper enhances your understanding of Bitcoin's behavior and assists in making more informed investment decisions.

Thank you for your interest in our work!

Contact

For any questions or further information, please feel free to reach out to us.

About

Bitcoin Prevision using Machine Learning and allocation strategy

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published