Home / Backtesting & trading frameworks
QuantSoftware Toolkit
Python framework for portfolio construction and management
What it is
An open-source Python framework designed to support portfolio construction and management. It provides backtesting and portfolio analysis tools that researchers and students can use to set up their own strategy research environment. Learners following quantitative investing courses and developers studying portfolio tooling are the natural audience. Expect to check its dependencies against current Python and library versions before using it in a new project.
At a glance
Research onlyOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Professional quants |
|---|---|
| Used for | Backtesting, Strategy research |
| Markets | Multi-market |
| Stack | Python |
| Learning curve | Steep learning curve |
| Practical value | Low 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 2026-09-28 (up to 30 days): −1 over the period, now 479. Gaps mean no snapshot was taken that day.
Python-based open source software framework designed to support portfolio construction and management.
Similar tools
Vectorized Python backtesting and strategy research toolkit
Iterative trading strategy research framework with walk-forward testing
Research framework for RL-enhanced Avellaneda-Stoikov market making
Python library of quantitative finance building blocks
AI-oriented quantitative investment platform with full ML pipeline
Open-source reinforcement learning platform for quantitative trading