Credit default risk

Ects : 3

Enseignant responsable :

  • RAPHAEL DUPRAT

Volume horaire : 18

Description du contenu de l'enseignement :

  1. Idiosyncratic credit risk
  2. Credit portfolio risk
  3. Monte Carlo simulations for credit portfolios
  4. Risk contributions and portfolio management
  5. Collateralized debt obligations
  6. Advanced Monte Carlo simulation techniques

Pré-requis obligatoires :

  • Java or Python programming and a development environment for that language
  • Probabilities and statistics
Coefficient : 1

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