units

AFF5380

Faculty of Business and Economics

Postgraduate - Unit

This unit entry is for students who completed this unit in 2014 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

print version

6 points, SCA Band 3, 0.125 EFTSL

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered, or view unit timetables.

LevelPostgraduate
FacultyFaculty of Business and Economics
Organisational UnitDepartment of Accounting and Finance
OfferedNot offered in 2014

Synopsis

This unit develops knowledge and improves skills in credit risk modelling by using market information to predict defaulted firms. The topics discussed will provide an understanding of their relative merits, the issues involved in their implementation and their use in the pricing and risk management of credit risk. This unit assists practitioners and students alike to understand better the use of credit risk models and moves them away from the proverbial Black Box scenario.

Outcomes

The learning goals associated with this unit are to:

  1. develop credit risk modelling using Altman and Ohlson models
  2. develop an understanding of credit risk modelling approaches
  3. analyse the Merton structural model and implications for credit analysis
  4. analyse the term structure of credit spreads and probabilities of default
  5. analyse implications of alternative ways to model recovery
  6. develop correlations between default rates and recovery
  7. develop copula based approach to modelling default dependence
  8. apply critical thinking, problem solving and presentation skills to individual and / or group activities dealing with credit risk modelling and demonstrate in an individual summative assessment task the acquisition of comprehensive understanding of the topics covered by AFF5380.

Assessment

Within semester assessment: 100%

Chief examiner(s)

Workload requirements

3 hours per week

Prerequisites

Students must have completed AFF9140 or ETF9300 and must be enrolled in one of the following courses 3818, 4412, 3850.