Credit Risk Measurement and Management

BMAN71572 Credit Risk Measurement and Management 15 Semester 2 Postgraduate Taught Level 7 Chi-Yang Tsou Unit coordinator 1 FHEQ level (Framework for Higher Education Qualifications) ' Masters/Integrated Masters P4 ' European Credit Transfer & Accumulation System Rating : 7.5 <table align="left" cellpadding="0" cellspacing="0" hspace="0" vspace="0"> <tbody> <tr> <td align="left">  </td> </tr> </tbody></table><ul> <li> Capital Adequacy and the Basel II Regulatory Framework</li> <li> Credit Rating and Scoring Methods</li> <li> Structural Models for Credit Risk  (with the emphasis on the Merton’s model and its industrial application within the KMV framework)</li> <li> Intensity Models for Credit Risk</li> <li> Modelling default dependencies</li> <li> The Distribution of Loan Portfolio Value (Merton / Vasicek)</li> <li> Industry used Credit Risk Management products</li></ul> <ul> <li> Capital Adequacy and the Basel II Regulatory Framework</li> <li> Credit Rating and Scoring Methods</li> <li> Structural Models for Credit Risk  (with the emphasis on the Merton’s model and its industrial application within the KMV framework)</li> <li> Intensity Models for Credit Risk</li> <li> Modelling default dependencies</li> <li> The Distribution of Loan Portfolio Value (Merton / Vasicek)</li> <li> Industry used Credit Risk Management products</li></ul> This course unit provides students with a solid background in credit risk modeling methods and the empirical framework for their application. Topics are presented in relation to the regulatory framework of Basel II and III, as well as in the light of the financial crises 2007-2011. The most recent research being conducted in the area is presented and discussed while at the same time a pragmatic approach is also provided with reference to industry approaches and financial engineering applications. The course provides students with an opportunity to implement the advanced credit risk models in MatLab. This course provides a good overview of topics that students may want to pursue for their dissertation. <div style="clear:both;"> On completion of this unit successful students will have achieved the following learning outcomes: <ul> <li> Understand the importance of credit risk management in the regulatory environment and its significance in maintaining regulatory and economic capital.</li> <li> Understand the principles underlying the development of internal and external credit rating and scoring systems.</li> <li> Understand the theory and mathematics behind standard industry practises and products in defining and measuring default probability (PD) and loss given default (LGD). </li> <li> Understand how individual credit risks add up to the portfolio level and over time.</li> <li> Understand how and why credit derivatives are created and how they are used in credit risk management.</li> </ul> The methods of assessment for this unit allow students to demonstrate achievement of all intended learning outcomes</div>  0 Other 100% Written Examination (80%)Individual Project (20%) Informal advice and discussion during a lecture, seminar, workshop or lab.Online exercises and quizzes delivered through the Blackboard course space.Responses to student emails and questions from a member of staff including feedback provided to a group via an online discussion forum.Written and/or verbal comments on assessed or non-assessed coursework.Generic feedback posted on Blackboard regarding overall examination performance.   BMAN71572 Programme Req: BMAN71572 is only available as a core unit to students on MSc Quantitative FinanceStudents taking this unit must have a solid foundation in Mathematical Statistics, and at least intermediate knowledge in Finance N <table align="left" cellpadding="0" cellspacing="0" hspace="0" vspace="0"> <tbody> <tr> <td align="left">  </td> </tr> </tbody></table><div style="clear:both;"> Main Texts1.  Measuring and Managing Credit Risk by Arnaud de Servigny and Oliver Renault (S&R), McGraw-Hill, 2004.  ISBN 0-07-141755-92.  Credit Risk Modeling by David Lando, Princeton, 2004, ISBN: 978-0-691-08929-43.  Risk Management and Financial Institutions by John C. Hull, third edition, 2012, ISBN 9781118269039Supplementary Texts1.  Credit Risk Modeling using Excel and VBA by Loffler and Posch ISBN: 978-0-470-03157-52.  An Introduction to Credit Risk Modeling by Christian Bluhm, Ludger Overbeck and Christoph Wagner, Chapman and Hall/CRC, 2003, ISBN 1-58488-326-X3.  Value at Risk and Bank Capital Management by Francesco Saita, Academic Press, 2007, ISBN 0-12-369466-34.  Credit Risk Measurement by Anthony Saunders and Linda Allen, Wiley, 2002, ISBN 0-471-21910-X5.  Credit Risk: Pricing Measurement and Management by Darrell Daffie and Kenneth J. Singleton, Princeton University Press, 2003, ISBN 0-691-09046-76.  The Analytics of Risk Model Validation by George Christodoulakis and Stephen Satchell (eds.), Elsevier, 2008, ISBN 978-0-7506-8158-27.  Managing Risks in the European Periphery Debt Crisis by George Christodoulakis (ed.), Palgrave Macmillan, 2015, ISBN 978-1-137-30494-0Basic Econometrics Texts <ol> <li> Introductory Econometrics by Jeffrey M. Wooldridge, 2009, 4th edition, ISBN-13:978-0-324-58548-3</li> </ol></div>  Assessment written exam 2 Lectures 20 0 128 Informal Contact MethodsOffice HoursOnline Learning Activities (online discussions via Blackboard, self-assessment questions)E-mail