Financial Risk Management in Python, R and Excel

Course details

A financial portfolio is almost always modeled as the sum of correlated random variables. Measuring the risk of this portfolio accurately is important for all kinds of applications: the financial crisis of 2007, the failure of the famous hedge fund LTCM and many other mishaps are attributable to poor risk modeling.

In this course, we cover the theory and practice of robust risk modeling:

• Model risk using covariance matrices and historical returns
• Refine this approach using factor models for dimensionality reduction and robustness
• Generate realistic stress-test scenarios using these factor model
• Calculate Value-at-Risk and understand the implications, strengths and weaknesses of this approach
• Implement all of this in Python, Excel and R