emoen/Machine-Learning-for-Asset-Managers
Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.
This project provides practical code examples from the book "Machine Learning for Asset Managers" by Prof. Marcos López de Prado. It allows quantitative finance professionals to apply concepts like denoising covariance matrices, calculating various distance metrics, and performing optimal asset clustering. The output helps in building more stable portfolios and understanding asset relationships, particularly useful for portfolio managers or quantitative analysts.
614 stars.
Use this if you are a quantitative finance professional who wants to understand and apply specific machine learning techniques for asset management as described in López de Prado's book.
Not ideal if you are looking for a production-ready library; for that, consider dedicated frameworks like mlfinlab.
Stars
614
Forks
188
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 11, 2026
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