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Machine-Learning-for-Asset-Managers

Market & alternative data★ 674 GitHub starsPython⏱ No commits in over six months

Code for Machine Learning for Asset Managers by López de Prado

What it is

An implementation of the code snippets and exercises from Marcos López de Prado's Machine Learning for Asset Managers, part of the Elements in Quantitative Finance series. Beyond reproducing the book's examples, it applies the methods to real market data. Readers of the book and researchers who want to see these techniques run end to end will find it useful. It is one person's implementation of the book, so results should be read with the original text at hand.

At a glance

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

Best for	Professional quants
Used for	Strategy research, Data analysis
Markets	Multi-market
Stack	Python
Learning curve	Steep learning curve
Practical value	Medium practical value
Cost	Free and open source
Hardware	No GPU needed
Maintenance	No commits in over six months

GitHub stars, last 30 days

Daily snapshots since 2026-09-28 (up to 30 days): 0 over the period, now 674. Gaps mean no snapshot was taken that day.

In the author's words

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.

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