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EigenLedger
Python portfolio backtesting, optimization, and risk analysis
What it is
A Python open-source quantitative investment library for portfolio management, analysis, and optimization, built as a wrapper around financial analysis libraries such as Quantstats and PyPortfolioOpt. It lets users backtest and analyze individual securities or whole portfolios, producing performance and risk metrics in an accessible framework. The project is aimed at both financial institutions and retail investors, and recommends running it in a notebook environment such as Jupyter or Google Colab. As largely a wrapper over other libraries, its capabilities depend on those underlying tools, and macOS and Windows users need additional tooling installed before setup.
At a glance
Worth watchingOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Professional quants |
|---|---|
| Used for | Backtesting, Data analysis |
| Markets | Multi-market |
| Stack | Python |
| Learning curve | Moderate learning curve |
| Practical value | Medium 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): +4 over the period, now 1,085. Gaps mean no snapshot was taken that day.
Portfolio backtesting, optimization, and risk and performance analysis.
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