Quantitative risk management

Summary

This course is an introduction to quantitative risk management that covers standard statistical methods, multivariate risk factor models, non-linear dependence structures (copula models), as well as portfolio allocation and diversification.

Content

Keywords

risk management, copula, diversification, credit risk

Learning Prerequisites

Recommended courses

• Calculus and Linear Algebra (undergraduate level)
• Statistics and Probability (first university course)
• Some knowledge of financial derivatives
• Previous experience with Matlab is very useful

Learning Outcomes

By the end of the course, the student must be able to:

• Use the main statistical tools used to model financial risk
• Conduct important volatility and credit risk models
• Identify and apply appropriate tools to describe and quantify the risk of a portfolio

Transversal skills

• Use a work methodology appropriate to the task.

Teaching methods

• Lectures
• Exercises
• Homework

Expected student activities

active attendance at lectures, completing exercises

Assessment methods

• 40% midterm exam
• 60% final exam

Resources

Bibliography

• Quantitative Risk Management - McNeil, Frey, Embrechts (primary reference)
• An Introduction to Statistical Modeling of Extreme Values - Coles
• Analysis of Financial Times Series - Tsay
• Statistical Models - Davison

Ressources en bibliothèque

• Quantitative Risk Management / McNeil
• An Introduction to Statistical Modeling of Extreme Values / Coles
• Statistical Models / Davison
• Analysis of Financial Times Series / Tsay

Moodle Link

• https://go.epfl.ch/FIN-417