Streamline PyPortfolioOpt Library

• Status: Closed
• Prêmio: $150
• Inscrições Recebidas: 1
• Vencedor: ruiteixeira93

Winner

Síntese do concurso

The task? To extract and clean the PyPortfolioOpt library. You've got to remove classes and distill the features in question to simple, functions – using only Python and numpy. However, cvxpy can remain throughout the process.

What to deliver:
A colab notebook prooving how you code (as short as possible) results in the same answer as the following code:

ef = EfficientFrontier(Means, Cov_Matrix, weight_bounds=(0, 0.1))
weights = ef.max_sharpe()


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

Habilidades Recomendadas

• Object Oriented Programming (OOP)
• Python