FinMLKit documentation¶
Welcome to FinMLKit’s documentation! This is a Python package for financial machine learning and more broadly quantitative finance.
The main goal of this library is to provide a solid foundation for financial machine learning, enabling users to process raw trades data, generate different types of bars, intra-bar features (eg. footprints), bar-level features (indicators), and labels for supervised learning.
⚒️ Quick Setup¶
pip install finmlkit
Or clone the repository and install it locally:
pip install .
For development (editable) installation:
pip install -e .
Documentation¶
Contents:
- finmlkit
- Tutorials
- Why FinMLKit?
- The problem we’re tackling
- What FinMLKit brings
- How this advances research
- What’s different from existing libraries
- Open source philosophy
- Call to action
- Processing Raw Trade Data
- Saving and Loading Data
- Building Intra-Bar Features
- Building Inter-Bar Features
- Feature pipelines: Compose, FeatureKit and the computation graph
- Building Labels