Quantitative Risk Management: Tools and Examples

This lecture covers quantitative risk management tools and examples, starting with an overview of UBS and Cargill's risk management strategies. It delves into the challenges of estimating Historical Value-At-Risk, including the impact of missing data and the use of theoretical P&L. The instructor discusses CCAR scenarios and their market risk impact, emphasizing the need for accurate forecasting under different risk factor shocks. Additionally, the lecture explores processes to fit returns, such as iid, AR, and GARCH models, and highlights the importance of data analysis and machine learning techniques in risk management.