ArbitrageLab is a python library that enables traders who want to exploit mean-reverting portfolios by providing a complete set of algorithms from the best academic journals.

This code accompanies the the paper Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture (https://arxiv.org/pdf/2112.08534.pdf).

Python API and command line interface for the numer.ai machine learning competition

Downloads data from Yahoo Finance, generates features, trains a model and submits the predictions to the tournament.

Python Code used in publications, for archival purposes only

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.

Portfolio Optimization and Quantitative Strategic Asset Allocation in Python

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

Tutorials on using encoder decoder architecture for time series forecasting

As described in Advances of Machine Learning by Marcos Prado.

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]

Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.

Implementation of code snippets and exercises in the book Machine Learning for Asset Managers written by Prof. Marcos López de Prado.

Predictive Lead Scoring does all the hard work for you by leveraging Machine Learning to provide your sales and marketing team with in-depth customer knowledge and ways to target the hottest and mo…

Reports for the Numerai machine learning competition

DataCamp data-science courses

Code, Notebooks and Examples from Practical Business Python