This class exists in these courses :
• IÉSEG > IESEG Degree - Programme Grande École > Semester 2 > 2,00 ECTS

Prerequisites

- Introduction to Financial Data Services (Bloomberg)

Learning outcomes

- Critically describe the characteristics of the basic techniques for measuring market risk
- Determine the exposure of financial positions to market risk and estimate their Value-at-Risk and Expected Tail Loss
- Backtest market risk models
- Stress-test market risk estimates

Course description

This course develops a framework for the identification and management of market risks. The first part of the course surveys the estimation of the Value-at-Risk (VaR) and of the Expected Tail Loss (ETL) of positions in single securities or portfolios. After a detailed introduction to nonparametric methods such as historical simulation, age-weighted and volatility-weighted historical simulations, the focus of the course moves to parametric estimation of market risk measures. An examination of Monte Carlo simulation techniques concludes this survey. The second part of the course assesses the validity of VaR models through backtesting and stress-testing. A significant part of the course is devoted to empirical issues in the estimation of the VaR or of the ETL and the use of Bloomberg data and analytics to monitor market risk is carefully considered.

Class type

Class structure

Teaching methods

• E-learning
• Interactive class
• Project work

Assessment

The assessment for this course consists of one project to assess your understanding of the concepts presented during the lecture.