Home / Risk & portfolio
FinQuant
Python portfolio management, analysis and optimisation library
What it is
A Python library for financial portfolio management, analysis and optimisation. It builds a Portfolio object from stock prices, automatically computes common quantities such as cumulative returns, and can plot returns, moving averages with buy/sell signals, and Bollinger Bands. Optimisation is available via the Efficient Frontier or a Monte Carlo run, and portfolios can be built with data pulled from the web. The tool suits Python users who want quick portfolio analysis and optimisation in a few lines of code, though it is a research-oriented library rather than a finished trading product.
At a glance
Worth watchingOur 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 | 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): +11 over the period, now 1,831. Gaps mean no snapshot was taken that day.
A program for financial portfolio management, analysis and optimization.
Similar tools
Jupyter notebooks companion to Machine Learning for Trading
Goldman Sachs Python toolkit for derivatives and risk
scikit-learn compatible Python library for portfolio optimization
CVXPY-based portfolio optimization and strategic asset allocation
Python financial econometrics with ARCH, GARCH and volatility models
C++ financial research terminal with embedded Python analytics