Open-source project
Open-source project
Microsoft Qlib
An AI-oriented quantitative investment platform spanning data processing, model training, backtesting and research workflows.
- Provider
- Microsoft Research
- Access
- Open source
- Primary interface
- AI-oriented quant research platform
Microsoft Research
API / Skill
Research
Train machine-learning alpha models
Strong validation is essential to control leakage, overfitting and regime dependence.
Open source · AI-oriented quant research platform
Best used for
Train machine-learning alpha models
Run reproducible research pipelines
Evaluate signals and portfolios
Quick start
pip install pyqlib
import qlib
from qlib.constant import REG_US
qlib.init(provider_uri='~/.qlib/qlib_data/us_data', region=REG_US)
# Configure a dataset, model and workflow next.A practical workflow
- 1Confirm the source and license
- 2Run the smallest useful request
- 3Validate fields and missing values
- 4Cache responsibly and document assumptions
Before you build
Strong validation is essential to control leakage, overfitting and regime dependence.
Frequently asked questions
What can Microsoft Qlib do in a real workflow?
Train machine-learning alpha models Run reproducible research pipelines Evaluate signals and portfolios
What access and compatibility does Microsoft Qlib require?
Open source. AI-oriented quant research platform.
What is the main implementation risk with Microsoft Qlib?
Strong validation is essential to control leakage, overfitting and regime dependence.