Crypto Portfolio Management | Python, Matplotlib, Deap, Simanneal

Description:

This project proposes a cryptocurrency portfolio optimization simulation using the simulated annealing method. It was developed in Python and relies on the Matplotlib, Deap, and Simanneal libraries.

Features:

• Algorithm: The project implements a simulated annealing-based optimization algorithm to explore the search space and identify the optimal portfolio composition.
• Data analysis: Historical cryptocurrency price data is used to evaluate the performance and risk of different portfolio configurations.
• Visualization: Matplotlib is used to generate graphs and visualizations of performance and risk data.

Technologies:

• Python: Main programming language
• Matplotlib: Data visualization library
• Deap: Genetic algorithm library
• Simanneal: Simulated annealing implementation library

Usage:

• Installation: pip install -r requirements.txt
• Execution: python main.py Example:

python main.py

License:

This project is licensed under MIT.

Contributors:

• Lou-John GENTHON

Notes:

• This project is a basic example and can be extended in several ways.
• You can add new cryptocurrencies, implement technical indicators, and further optimize the algorithm.
• Feel free to contribute to the project by submitting pull requests.

I hope this is helpful!

Pdf end of project analysis: 56640_Loujohn_Genthon_Assignement_Documentation_195393_186812911.pdf