Postgraduate Course: Credit Risk Modelling (MATH11130)
Course Outline
| School | School of Mathematics |
College | College of Science and Engineering |
| Course type | Standard |
Availability | Not available to visiting students |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Credits | 15 |
| Home subject area | Mathematics |
Other subject area | None |
| Course website |
None |
Taught in Gaelic? | No |
| Course description | The aims of this module are:
- to introduce students to quantitative models for measuring and managing credit risks
- to provide students with a critical understanding of the credit risk methodology used in the financial industry
- to give students an appreciation of the regulatory framework in which the models operate |
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | MSc Financial Mathematics students only. Students must not have taken Credit Risk Management MATH11061 |
| Additional Costs | None |
Course Delivery Information
|
| Delivery period: 2013/14 Semester 2, Not available to visiting students (SS1)
|
Learn enabled: No |
Quota: None |
Web Timetable |
Web Timetable |
| Course Start Date |
15/01/2014 |
| Breakdown of Learning and Teaching activities (Further Info) |
Total Hours:
150
(
Lecture Hours 30,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 3,
Directed Learning and Independent Learning Hours
115 )
|
| Additional Notes |
Examination takes place at Heriot-Watt University.
|
| Breakdown of Assessment Methods (Further Info) |
Written Exam
100 %,
Coursework
0 %,
Practical Exam
0 %
|
| No Exam Information |
Summary of Intended Learning Outcomes
On completion of this module the student should be able to:
- Demonstrate an understanding of the nature of credit risk
- Describe the theoretical underpinnings of models used in the financial industry
- Show a knowledge of the regulatory framework and, in particular, the Basel II regulatory capital formula
- Describe how dependence is modelled in credit portfolios
- Describe mixture models of default and derive their mathematical properties
- Describe and use methods for calculating the portfolio loss distribution
- Describe and apply statistical approaches to calibrating credit risk models
- Explain the features and uses of the most common single-name products and basket derivatives
- Show an appreciation of the interface between academic theory and industrial practice
- Show an appreciation of the societal role of risk management in protecting the consumer and other stakeholders
- Demonstrate the ability to learn independently and as part of a group
- Manage time, work to deadlines and prioritise workloads
- Demonstrate skills in the understanding and processing of numerical information and interpretation of statistics
- Show knowledge of appropriate software for implementing solutions
|
Assessment Information
| See 'Breakdown of Assessment Methods' and 'Additional Notes', above. |
Special Arrangements
| MSc Financial Mathematics students only. |
Additional Information
| Academic description |
Not entered |
| Syllabus |
- Introduction to credit risk: credit-risky instruments, defaults, ratings
- Merton's model of the default of a firm
- Common industry models (KMV, CreditMetrics,CreditRisk+)
- Modelling dependence between defaults with factor models
- Latent variable and mixture models of default
- The Basel II regulatory capital formula
- Calculating the portfolio credit loss distribution
- Large portfolio behaviour of the credit loss distribution
- Calibration and statistical inference for credit risk models
- Overview of the more common single-name and portfolio/basket credit derivatives |
| Transferable skills |
Not entered |
| Reading list |
McNeil, A.J. and Frey, R. and Embrechts, P. (2005). Quantitative Risk Management: Concepts, Techniques and Tools. Princeton, New Jersey.
Bluhm, C. and Overbeck, L. and Wagner, C. (2002). An Introduction to Credit Risk Modeling. Chapman & Hall/CRC Financial Mathematics Series, London. |
| Study Abroad |
Not Applicable. |
| Study Pattern |
See 'Breakdown of Learning and Teaching activities' above. |
| Keywords | CRMo |
Contacts
| Course organiser | Dr Sotirios Sabanis
Tel: (0131 6)50 5084
Email: S.Sabanis@ed.ac.uk |
Course secretary | Mrs Kathryn Mcphail
Tel: (0131 6)50 4885
Email: k.mcphail@ed.ac.uk |
|
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