26 June 2019
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.