There are two main things which make returning for Open Programs such a valuable and worthwhile experience. The first is being back on campus – meeting the current students, returning to campus again, the whole experience was just so pleasant. The second is the level of quality in the courses – the faculty teaching are absolute experts.
This course introduces to some modern credit risk methodologies. It will not only introduce the theoretical concepts of default models that are used in banking practice, but will also use computer-based applications and software (Microsoft Excel) to implement the theoretical concepts into practice.
The course will cover different approaches to determine individual probabilities of default. Examples of these approaches comprise credit scoring models, rating transitions (credit migration approach), or the Merton model as an approach to default modeling based on option pricing theory. The course will also cover some concepts of the regulation of credit risk as outlined in the Basel accords, and will discuss portfolio credit risk. Finally, students will become familiar with the products used in today’s credit markets such as internal and external ratings or credit default swaps (CDS), an insurance contract against default.
The course will not only present the theoretical concepts but also deepen the knowledge of the different credit risk management tools by a hands-on implementation in Microsoft Excel. Any pre-knowledge in MS Excel is useful, but not necessarily required for this course.
This course is offered in the part-time Master in Finance program and may be attended on a “no credit” basis by individuals not enrolled in the program. Course participants are visitors who are not responsible for assignments and do not take an exam or earn academic credits. As the number of seats in the course is limited, we recommend to register online early.
Upon completion of this course, you will be able to:
Perform simple regression analyses of non-linear models to model default probabilities as a function of observable characteristics
Evaluate single claim credit risk applying different methodologies such as structural models, credit migration approach, or scoring models
Estimate the risk of a credit portfolio using default-mode models
Understand and estimate the price of credit risk
Understand structured portfolio credit risk and be aware of the implied risks
Structural Pricing Models
Ratings and Rating Transition Matrices
Prediction of Default Probabilities
Portfolio Risk (e.g. Value-at-Risk, Expected Shortfall)
Credit Default Swaps (CDS)
Andreas Barth is Assistant Professor of Digital Transformation in Finance and Accounting at Saarland University Saarbrücken. Before joining Saarland University, he was Assistant Professor at the Chair of Banking and Finance at Goethe University Frankfurt. He graduated with Prof. Dr. Isabel Schnabel at Gutenberg University Mainz. Andreas did various research stays at the European Systemic Risk Board and the European Central Bank. His teaching specializes inter alia in financial modeling and risk management and applied econometrics. His research focusses mainly on financial intermediation, banking regulation and financial markets.
Course materials will be provided in electronic form.
Campus Westend of Goethe University Frankfurt.
A GBS certificate of participation is awarded upon completion of the course.
€ 950 (fee is exempt from VAT). The fee for GBS students or alumni amounts to € 400.
*Withdrawal and fee refund
In case the course withdrawal request is received two weeks prior to the start of classes, GBS will retain a withdrawal fee of €50. In case the course withdrawal request is received less than two weeks prior to the start of classes, GBS will retain 50% of the payment made.
|Fri., May 12, 2023||18:00 - 20:00|
|Sat., May 27, 2023||11:30 - 13:30, 14:30 - 16:30|
|Fri., Jun 9, 2023||18:00 - 20:00|
|Fri., Jul 7, 2023||18:00 - 20:00|
|Fri., Jul 14, 2023||18:00 - 20:00|