#### Credit default risk

Ects : 3

Enseignant responsable :

- RAPHAEL DUPRAT

Description du contenu de l'enseignement :

- Idiosyncratic credit risk
- Credit portfolio risk
- Monte Carlo simulations for credit portfolios
- Risk contributions and portfolio management
- Collateralized debt obligations
- Advanced Monte Carlo simulation techniques

Pré-requis obligatoires :

- Java or Python programming and a development environment for that language
- Probabilities and statistics

Compétence à acquérir :

- Understand the definition of single name credit default risk and how it is measured
- Understand the risk aggregation problem and be able to program a Monte Carlo simulator for credit portfolios
- Understand the risk allocation problem and be able to calculate risk contributions to portfolio measures of risk
- Understand how CDS & CDOs can be used to manage credit portfolio risk and be able to calculate their impact by Monte Carlo simulation
- Understand the concept of Monte Carlo variance reduction and be able to implement importance sampling

Mode de contrôle des connaissances :

- Graded project
- Class participation

Bibliographie, lectures recommandées

- Introduction to Credit Risk Modeling (Chapman and Hall/CRC Financial Mathematics Series) 2nd Edition by Christian Bluhm, Ludger Overbeck and Christoph Wagner
- Monte Carlo Methods in Financial Engineering (Springer) by Paul Glasserman
- Quantitative Risk Management (Princeton Series in Finance) by Alexander McNeil, Rudiger Frey and Paul Embrechts