Implementing features from "Advances in Financial Machine Learning" by Marcos López del Prado in a financial algorithm using Enigma Catalyst.

For running the algorithm is used Enigma Catalyst, which is based in Zipline. This is useful because allow high compatibility with Quantopian and Zipline itself.

Before executing the algorithm you will need to install Catalyst in first place. You can use the Catalyst instalation instruccions.

The idea is to share the implementation of features exposed by Marco López del Prado in his book "Advances in Financial Machine Learning". You can use this as a base for working in your own algorithm. And you are welcome to help to implement the rest of the chapters. Until now I have programmed since chapter 1 to chapter 12. But in not just a copy paste form the book's scripts. In main.py file you will find a implementation of these scripts in a real algoritmic. So, you can use the code at live in Catalyst or with, few changes, use it in Zipline or Quantopian.