skfolio is a portfolio optimization library built on top of scikit-learn, providing tools for mean-variance optimization, risk parity, black-litterman, hierarchical risk parity (HRP), and more. It integrates seamlessly with scikit-learn's API. Current version 0.20.1, released in 2025. Active development with frequent releases.
pip install skfolioNo compatibility data collected yet for this library.
Verified import paths — ran on the pinned version, not inferred.
Fits a minimum variance portfolio on S&P 500 daily returns. Prints optimized weights.
Change 'from skfolio.optimization import MeanVariance' to 'from skfolio import MeanVariance'.
Replace 'from skfolio.risk_parity import RiskParity' with 'from skfolio import RiskParity'.
Ensure input data is returns, e.g., df.pct_change().dropna() before calling fit().