skfolio/skfolio

Health v2 · maintenance only

Adoption not part of the score

2256 stars · 233 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

skfolio is a Python library for portfolio optimization, factor model construction, and risk management built on top of scikit-learn. It provides a unified scikit-learn-compatible API to build, tune, cross-validate, and stress-test portfolio models.

Use cases

• optimize a stock portfolio with mean-variance optimization in python
• build an efficient frontier for asset allocation
• compute risk parity weights for a portfolio
• run cross-validation on portfolio optimization models
• minimize CVaR for an investment portfolio
• cluster assets hierarchically for portfolio construction
• stress-test and backtest portfolio strategies

When to choose

• you want scikit-learn-style estimators, pipelines, and hyperparameter tuning for portfolio optimization
• you need convex optimization-based allocation (MVO, CVaR, risk budgeting) with cvxpy solvers
• you want a maintained, well-documented open-source quant finance library with BSD licensing

When to avoid

• you need live market data feeds or broker execution - skfolio focuses on optimization, not data or trading infrastructure
• you need a no-code or GUI portfolio tool
• your project is not Python-based

Facets

library · maturity active

machine-learning data-science math fintech data-science machine-learning python portfolio-optimization quantitative-finance asset-allocation risk-management scikit-learn cvxpy efficient-frontier risk-parity cvar hierarchical-clustering optimization

Member repositories

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markdown · JSON · MCP: product_card(name="skfolio/skfolio")