Credit risk is the possibility that a counterparty defaults on a payment. This course covers the main concepts and techniques required to manage the risk of portfolios of credit-sensitive assets, such as corporate bonds or loans. We will also learn how to use credit derivatives to manage credit risk, focusing particularly on Credit Default Swaps. Finally, we will study more complex structures, such as Collateralized Debt Obligations, which were at the forefront of the financial crisis of 2008. The materials covered in this course are relevant to commercial and investment banks and to any large firm with credit-sensitive assets.
João Pedro Pereira
Weekly - Available soon
Total - Available soon
A set of handouts will be distributed in class.
The following additional references may be helpful:
1. Lando, 2004, Credit Risk Modeling, Princeton University Press.
2. Smithson, C., 2003, Credit Portfolio Management, Wiley.
3. CreditMetrics - Technical Document, JP Morgan, 1997.
4. Chaplin, 2010, Credit Derivatives, Wiley.
5. Schönbucher, P.J., 2003, Credit Derivatives Pricing Models: Model, Pricing and Implementation, John Wiley & Sons.
The following websites may be helpful:
https://www.moodysanalytics.com/ - for Moody’s-KMV docs.
https://www.msci.com/documents/10199/242721/RiskMetrics_CreditManager.pdf/189bff0e-4c58-4ea7-a824-da2334ddeb34 - for CreditMetrics docs.
https://www.bis.org/ - for Basel docs.
'The Big Short' movie (2016), based upon the book by Michael Lewis on the 2007-2008 financial crisis.
T. Teaching Methods. The course will follow a standard lecture mode, where we will:
1. Discuss the theory of each topic.
2. Solve small applied problems.
The final grade is computed as follows:
Final exam: 50%
The exam is closed-book and closed-notes. However, you may use a two-sided A4 formula sheet and a pocket calculator.
Group projects: 50%
There will be around 6 or 7 take-home project assignments. The projects should be done in groups of one, two (recommended), or three people. Most projects will be small (requiring only a couple of hours of work), but a few will be more demanding. Some of the projects will require the simulation of stochastic models. The use of Matlab is encouraged, though not required.
Class participation: rounding of the final grade.
In accordance with the school’s norms, there is no procedure for grade improvement after passing a course (no re-sit or second course enrolment).
1. Foundations for credit risk modelling: Default loss; exposure; loss given default; probability of default; portfolio default loss.
2. Estimation of default probabilities: Agency credit ratings; credit scoring and internal rating models.
3. Structural approach to credit risk: Merton’s model; Moody’s-KMV EDF.
4. Portfolio models: Credit migration approach (CreditMetrics).
5. Valuing defaultable bonds: Credit spreads (G, I, Z); Risk-neutral pricing.
6. Credit derivatives: Credit default swaps (CDS); credit spread options; total return swaps; credit-linked notes.
7. Collateralized Debt Obligations.
|[Review/slack or guest speaker].|
Programs where the course is taught: