Practical, hands-on risk modeling, risk assessment and verifications of risk models across major risk classes and understanding risk regulation as well. Implementing risk models in Python, R and Excel.

In the Market Risk/ directory you may find Jupyter Notebooks containing models and calculations for:

• VAR (Value at Risk)
• ES (Expected Shortfall, cVAR)
• Archegos Capital Management case study

In the Reporting in Commercial Banks directory you may find R netebook for applying Capital buffer framework on Serbian banking sector and calculating CCyB (Countercyclical Capital Buffer).

You may find the analysis on the website: CCyB rate for Serbia for 2021 Q3 - 2022 Q2

In the Convertable Bonds/ directory you may find Jupyter Notebooks containing models and calculations for:

• Analysing correlation between Credit and Equity indices to understand the systemic risk
• Convertible Bond pricing and risks
• Mandatory Convertible Bonds (PERCS and DECS) pricing
• Convertible Bond structuring and greeks

We recommend viewing and running notebook files with Google Collab, so you won't have to manage any of the python requirements compared with running them locally.

This repository represents group project work for course in Quantitative Risk Management for advanced degree Masters in Computational Finance, Union University.