Calculating Value at Risk (VaR) with Python or R

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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. scenario-based possibilities
  • Calculate VaR as the worst case loss in a period for a particular probability
The modules:

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