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quantstats
Portfolio analytics and performance tear sheets for quants
What it is
A Python library for portfolio profiling that gives quants and portfolio managers in-depth performance and risk metrics. It provides three modules: stats for metrics such as Sharpe ratio, volatility and win rate; plots for visualizing performance, drawdowns and rolling statistics; and reports for generating metrics tear sheets, batch plots and full HTML reports, plus built-in Monte Carlo simulations. It works well for systematic and algorithmic strategies with regular rebalancing, since it analyzes return series rather than discrete trades. Metrics like win rate and payoff ratio are period-based, so they may differ from trade-level statistics for discretionary traders with multi-day trades.
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 | Easy to start |
| Practical value | High practical value |
| Cost | Free and open source |
| Hardware | No GPU needed |
| Maintenance | Last commit 14 days ago |
GitHub stars, last 30 days
Daily snapshots since 2026-09-12 (up to 30 days): +67 over the period, now 7,693. Gaps mean no snapshot was taken that day.
Portfolio analytics for quants, written in Python.
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