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Qlib

Backtesting & trading frameworks★ 49,265 GitHub starsPython⏱ Last commit 3 days ago

AI-oriented quantitative investment platform with full ML pipeline

What it is

An open-source, AI-oriented quantitative investment platform from Microsoft, written in Python. It provides a complete machine learning pipeline covering data processing, model training, and back-testing, and addresses the full chain of quantitative investment, including alpha research. Researchers and practitioners building ML-driven trading strategies will find it useful, and it pairs with the related RD-Agent project for automated factor mining and model optimization. It is a research-oriented framework rather than an out-of-the-box trading product, so users should expect to write code and configure data pipelines themselves.

At a glance

RecommendedOur rating, based on popularity, maintenance and how ready it is for real use.

Best forProfessional quants
Used forBacktesting, Strategy research
MarketsChina A-shares, Multi-market
StackPython
Learning curveSteep learning curve
Practical valueHigh practical value
CostFree and open source
HardwareGPU optional
MaintenanceLast commit 3 days ago

GitHub stars, last 30 days

Daily snapshots since 2026-09-12 (up to 30 days): +779 over the period, now 49,265. Gaps mean no snapshot was taken that day.

In the author's words

An AI-oriented Quantitative Investment Platform by Microsoft. Full ML pipeline of data processing, model training, back-testing; and covers the entire chain of quantitative investment: alph

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