PyPortfolioOpt

What it is

A Python library implementing financial portfolio optimization methods, spanning classical mean-variance optimization on the efficient frontier as well as Black-Litterman allocation, shrinkage estimators, and Hierarchical Risk Parity. Concretely, it estimates expected returns and covariance risk models, optimizes objective functions such as maximizing the Sharpe ratio, supports adding constraints or custom objectives, and can convert continuous weights into an actual allocation for a given portfolio size and recent prices. Inspired by scikit-learn, it is extensive yet easily extensible, making it a fit for casual investors as well as professionals seeking a prototyping tool for combining alpha sources in a risk-efficient way. Keep in mind that nothing in the project constitutes investment advice, and users remain responsible for their own investment decisions.