Postgraduate Course: Credit Risk Management (MATH11061)
Course Outline
| School | School of Mathematics |
College | College of Science and Engineering |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Credits | 15 |
| Home subject area | Mathematics |
Other subject area | Financial Mathematics |
| Course website |
None |
Taught in Gaelic? | No |
| Course description | This course will:
! introduce students to quantitative models for measuring and managing credit risks
! provide students with a critical understanding of the credit risk methodology used in the financial industry
! 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 | None |
| Additional Costs | None |
Information for Visiting Students
| Pre-requisites | None |
| Displayed in Visiting Students Prospectus? | No |
Course Delivery Information
| Not being delivered |
Summary of Intended Learning Outcomes
On completion of this course 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
| Examination 100%. Examination held at Heriot-Watt University. |
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
Mixture models of default
The Basel II regulatory capital formula
Calculating the portfolio credit loss distribution
Calibration and statistical inference for credit risk models
Credit derivative models and pricings (CDS and CDOs)
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| Transferable skills |
Not entered |
| Reading list |
McNeil, A. & Frey, R. & Embrechts, P. (2005). Quantitative Risk Management. Princeton University Press.
Blum, C. & Overbeck, L. & Wagner, C. (2003). An Introduction to Credit Risk Modeling. Chapman and Hall, London.
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| Study Abroad |
Not entered |
| Study Pattern |
Not entered |
| Keywords | CRM |
Contacts
| Course organiser | Dr Sotirios Sabanis
Tel: (0131 6)50 5084
Email: S.Sabanis@ed.ac.uk |
Course secretary | Dr Jenna Mann
Tel: (0131 6)50 4885
Email: Jenna.Mann@ed.ac.uk |
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