Calculating Value at Risk (VaR) with Python or R
The following modules linked below are based on a Pluralsight course,
Understanding and Applying Financial Risk Modeling Techniques, and while the code itself is nearly verbatim, this is mostly for my own development, working through the peculiarities of Value at Risk (VaR) in both R and Python, and adding commentary as needed.
The general outline of this process is as follows:

Load and clean Data

Calculate returns

Calculate historical variance

Calculate systemic, idiosyncratic, and total variance

Develop a range of stress variants, e.g. scenariobased possibilities

Calculate VaR as the worst case loss in a period for a particular probability
The modules: