We design this course to train participants to evaluate and measure financial risks. The course starts with a detailed analysis of matrix and risk profiles, the importance of financial risk factors, and hedging risk exposure techniques. Then the main points related to why and how firms should hedge are addressed. We discuss Basel capital accords. After ensuring that the participants know how to compute and backtest Value-at-risk (VaR) and Expected Shortfall (ES) for portfolios exposed to market risk. We discuss important market risk modeling technical aspects, such as copulas, micro correlations, and tail dependences. Next, the course turns to credit risks and their measurement (CVaR). We discuss how to manage credit risk using credit derivatives. The program ends with a review of operational risk measures (OVaR) and implementation issues.
The emphasis of the course is on modeling and measuring financial risk. The course deals with the interest rate, exchange rate, commodity price, equity, credit, and systemic and operational risks. The course draws heavily on mathematics, statistics, econometrics, and financial theory. The practice sessions require applying standard Econometric techniques such as GARCH modeling and Machine Learning and Deep Learning techniques such as Regression Trees and Long Short-Term Memory Networks (LSTM). The course involves a command of Matlab and, especially, LiveScripts.
