37281 - Credit Derivatives

Academic Year 2021/2022

  • Teaching Mode: Traditional lectures
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Quantitative Finance (cod. 8854)

Learning outcomes

At the end of the course the student knows how to transfer credit risk by means of swap arrangements (asset swaps and TRORS), and with credit derivatives. The student knows the analysis developed both on a single name basis (CDS) and on a multiname basis (CDO, CDX, iTraxx). The analysis is extended to large CDO, ABS and ABX.

Course contents

1. The basics of credit derivatives. Defaultable bonds. Risk-adjusted vs actual default probabilities. The term structure of default probabilities.

2. Single name credit derivatives: ASW and CDS. The CDS-bond basis.

3. Single name credit models: structural and intensity-based models

4. Multi-name credit derivatives: credit indexes, first to default swaps. CDS index: Itaxx and CDX. Securitization: CDOs and ABS.

5. Multi-name credit models: copula functions.

6. JLT model for dynamic credit ratings.

7. Introduction to Counterparty Risk

Readings/Bibliography

  1. D. Duffie and K. Singleton: Credit Risk: Pricing, Measurement and Management, Princeton University Press, 2003
  2. D. Lando: Credit Rsik Modeling: Theory and Applications. Princeton Series in Finance
  3. C. Bluhm, L. Overbeck and C. Wagner: An introduction to Credit Risk Modeling, Chapman & Hall/CRC, 2003
  4. M. Morini, "Understanding and Managing Model Risk. A practical guide for quants, traders and validators", Wiley, 2011

Teaching methods

Classroom lectures.

Theoretical lessons are accompanied and completed by interactive Lab sessions with real market data, examples and exercises.

Lessons are based on slides and Excel exercises.

Assessment methods

The student will be required to write a term paper, either theoretical or empirical, on a topic connected to the course.

The assessment will consist of an oral defense of the term paper and of the main concepts developed in the course.

Teaching tools

Case studies analyses with real market data. Computer exercises.

Office hours

See the website of Marco Di Francesco