MLFinLab is an open-source* package based on the research of Dr. Marcos Lopez de Prado (QuantResearch.org) in his new books Advances in Financial Machine Learning, Machine Learning for Asset Managers, as well as various implementations from the Journal of Financial Data Science. This implementation started out as a spring board for a research project in the Masters in Financial Engineering programme at WorldQuant University and has grown into a mini research group called Hudson and Thames Quantitative Research (not affiliated with the university).

The following is the online documentation for the package: read-the-docs

A special thank you to our sponsors! It is because of your contributions that we are able to continue the development of academic research for open source. If you would like to become a sponsor and help support our research, please sign up on Patreon.

• Machine Factor Technologies

• E.P. Chan & Associates
• Markov Capital

• John B. Keown
• Roberto Spadim
• Zack Gow
• Jack Yu
• Егор Тарасенок
• Joseph Matthew
• Justin Gerard
• Jason
• Shaun McDonogh

Recommended versions:

• Anaconda 3
• Python 3.6

The package can be installed from the PyPi index via the console:

1. Launch the terminal and run: pip install mlfinlab

Clone the package repo to your local machine then follow the steps below.

1. Make sure you install the latest version of the Anaconda 3 distribution. To do this you can follow the install and update instructions found on this link: https://www.anaconda.com/download/#mac
2. Launch a terminal
3. Create a New Conda Environment. From terminal: conda create -n <env name> python=3.6 anaconda accept all the requests to install.
4. Now activate the environment with source activate <env name>.
5. From Terminal: go to the directory where you have saved the file, example: cd Desktop/mlfinlab/.
6. Install Python requirements, by running the command: pip install -r requirements.txt

1. Download and install the latest version of Anaconda 3
2. Launch Anaconda Navigator
3. Click Environments, choose an environment name, select Python 3.6, and click Create
4. Click Home, browse to your new environment, and click Install under Jupyter Notebook
5. Launch Anaconda Prompt and activate the environment: conda activate <env name>
6. From Anaconda Prompt: go to the directory where you have saved the file, example: cd Desktop/mlfinlab/.
7. Install Python requirements, by running the command: pip install -r requirements.txt

On your local machine open the terminal and cd into the working dir.

1. Code style checks: ./pylint
2. Unit tests: python -m unittest discover
3. Code coverage: bash coverage

We have recently opened access to our Slack channel to help form a community and encourage contributions.

Looking forward to hearing from you!

This project is licensed under an all rights reserved licence.

LICENSE.txt file for details.