Trading Strategies and Performance

Updated on 1st May 2019

I’m excited to announce our first guest speaker to the London Python for Trading group, Jacques Joubert.

Jacques has prior experience working as a quantitative trader, quantitative analyst and a data scientist. He is currently a Masters in Financial Engineering candidate at World Quant University.

The event will be focused on a tutorial based, jupyter notebook (python), walk through of transforming raw tick data into financial data structures that are more amenable to financial machine learning. The notebook will be focused on the techniques described in the textbook Advances in Financial Machine Learning by Marcos Lopez de Prado.

# Who is the tutorial for (Intermediate to Advanced)?

The work we will be covering is based on some very technical material, however, it is the starting point. We will be using numpy, pandas, and our new package mlfinlab in a python environment - to create the new financial data structures described in the book. We will also take the time to analyze the statistical properties and explain why they are better when compared to fixed time interval sampling.

To get the most out of the lecture, it would be advised to read chapter 2 of the book. Please bring your laptop with the Anaconda3 distribution.

Notes:
A laptop is not a requirement but advised.

An entry level understanding of machine learning would be helpful.

# Resources

Advances in Financial Machine Learning: https://www.amazon.co.uk/Advances-Financial-Machine-Learning-Marcos/dp/1119482089

Python & Anaconda Distributions: https://www.anaconda.com/distribution/#download-section

Github Repo: https://github.com/hudson-and-thames

We look forward to seeing you there!

Jacques Joubert and Riyad Jaunoo.