PyPortfolioOpt Extraction and Cleanup
Budget: $50 – $0 USD
I'm in need of a skilled Python developer, with particular expertise in numpy and cvxpy libraries.
The task? To extract and clean up the data preprocessing functions from the PyPortfolioOpt library. You've got complete freedom to remove classes and distill the features in question to simple, functions – using only Python and numpy. However, cvxpy can remain throughout the process.
A few important notes:
• Maintain the original functionality of the refactored code.
• Comments are not necessary during the cleanup process.
Your deep comprehension of numpy, Python, and cvxpy would be most advantageous in completing this project.
ef = EfficientFrontier(Flipped_Means, Cov_Matrix, weight_bounds=(0, 0.1))
weights = ef.max_sharpe()
This code above is the part i need extracted.
source codes:
https://pyportfolioopt.readthedocs.io/en/latest/_modules/pypfopt/efficient_frontier/efficient_frontier.html#EfficientFrontier.max_sharpe
https://pyportfolioopt.readthedocs.io/en/latest/_modules/pypfopt/base_optimizer.html
The task? To extract and clean up the data preprocessing functions from the PyPortfolioOpt library. You've got complete freedom to remove classes and distill the features in question to simple, functions – using only Python and numpy. However, cvxpy can remain throughout the process.
A few important notes:
• Maintain the original functionality of the refactored code.
• Comments are not necessary during the cleanup process.
Your deep comprehension of numpy, Python, and cvxpy would be most advantageous in completing this project.
ef = EfficientFrontier(Flipped_Means, Cov_Matrix, weight_bounds=(0, 0.1))
weights = ef.max_sharpe()
This code above is the part i need extracted.
source codes:
https://pyportfolioopt.readthedocs.io/en/latest/_modules/pypfopt/efficient_frontier/efficient_frontier.html#EfficientFrontier.max_sharpe
https://pyportfolioopt.readthedocs.io/en/latest/_modules/pypfopt/base_optimizer.html