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alphalens-reloaded
Performance analysis of predictive stock factors
What it is
A community-maintained continuation of Quantopian's alphalens for analysing predictive stock factors. Given factor values and prices, it produces information coefficient analysis, returns by quantile and turnover statistics in a standard tear sheet. Quant researchers testing whether a factor actually predicts returns use it during factor discovery and validation. It analyses factors you have already computed; building the factors and handling data quality remain your job.
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 | US equities, Multi-market |
| Stack | Python |
| Learning curve | Moderate learning curve |
| Practical value | High practical value |
| Cost | Free and open source |
| Hardware | No GPU needed |
| Maintenance | Commits today |
GitHub stars, last 30 days
Daily snapshots since 2026-09-28 (up to 30 days): +20 over the period, now 677. Gaps mean no snapshot was taken that day.
Performance analysis of predictive (alpha) stock factors.
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