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									Form 20                             Heriot-Watt University - Module Descriptor Template (RAY)                                                     Version 3.0 (2007/2008)

Module Title                                                               School    MACS                                                           On or Off-     On
                Credit Risk Modelling                                                                                                               Campus
Module          MSc QRM Course Director                                    SCQF      11        Module                         Semester   2          Credits        15
Co-ordinator                                                               Level               Code

1. Pre-requisites
                                None
2. Linked Modules
   (specify if synoptic)
3. Excluded Modules

4. Replacement Module           Code:                      New module replacing       5.   Availability as an           Yes              No
                                                           F71CR + F71CD from              Elective                                           X
                                Date Of Replacement:       Sep 09
6. Degrees for which this
   is a core module             MSc/PG Diploma/PG Certificate in Quantitative Risk Management; MSc/PG Diploma/PG Certificate in Financial Mathematics
7. Aims


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

8. Syllabus


The module covers the following topics:

               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


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Form 20                            Heriot-Watt University - Module Descriptor Template (RAY)                                                    Version 3.0 (2007/2008)

Module Title                                                            School     MACS                                                           On or Off-        On
               Credit Risk Modelling                                                                                                              Campus
Module         MSc QRM Course Director                                  SCQF       11      Module                       Semester      2           Credits           15
Co-ordinator                                                            Level              Code

9. Learning Outcomes (HWU Core Skills: Employability and Professional Career Readiness)

Subject Mastery       Understanding, Knowledge and Cognitive Skills             Scholarship, Enquiry and Research (Research-Informed Learning)

                      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


Personal Abilities    Industrial, Commercial & Professional Practice       Autonomy, Accountability & Working with Others          Communication, Numeracy & ICT

                            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

10. Assessment Methods                                                                                          11. Re-assessment Methods

                   Method                      Duration of Exam      Weighting (%)      Synoptic modules?                   Method                  Duration of Exam
                                                   (if applicable)                                                                                     (if applicable)
Examination                                    2 hours               At least 70%                               Examination                         2 hours
project                                                              Up to 30%



12. Date and Version

Date of Proposal     November 2008           Date of Approval by                                    Date of             September 2009              Version     1
                                             School Committee                                       Implementation                                  Number
                                                                                                                                                               2/2

								
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