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alphalens
Performance analysis of predictive alpha stock factors
What it is
A Python library for evaluating predictive (alpha) stock factors. It produces factor 'tear sheets' covering returns analysis, information coefficient analysis, turnover analysis, and grouped analysis, and integrates with Zipline for backtesting and Pyfolio for portfolio and risk analysis. Quants researching and testing alpha ideas, especially those working in Jupyter notebooks, will find it useful. The library originated with Quantopian, and its examples and notebooks assume familiarity with that research ecosystem, so some referenced services may not be fully available to outside users.
At a glance
RecommendedOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Professional quants |
|---|---|
| Used for | Data analysis, Strategy research |
| Markets | Multi-market |
| Stack | Python |
| Learning curve | Moderate learning curve |
| Practical value | High practical value |
| Cost | Free and open source |
| Hardware | No GPU needed |
| Maintenance | No commits in over six months |
GitHub stars, last 30 days
Daily snapshots since 2026-09-12 (up to 30 days): +27 over the period, now 4,470. Gaps mean no snapshot was taken that day.
Performance analysis of predictive alpha factors.
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