# DEGREE REGULATIONS & PROGRAMMES OF STUDY 2013/2014 -- ARCHIVE as at 1 September 2013 for reference onlyTHIS PAGE IS OUT OF DATE

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# Postgraduate Course: Credit Risk Modelling (MATH11130)

 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
 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
 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
 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
 See 'Breakdown of Assessment Methods' and 'Additional Notes', above.
 MSc Financial Mathematics students only.
 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
 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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