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 is based on the belief that analytical methods are best understood by implementing them. It does not only introduce students to the major concepts and instruments for the management of credit risk in both capital markets and banking institutions theoretically but also shows how to implement them employing Excel. Although not always the first choice for some problems, it is the major application used in financial institutions and accessible from almost everywhere. Nonetheless, students are not required to have an excessive prior knowledge in Excel! All applications will be demonstrated and described in class. Furthermore, it will be shown that other statistical packages (e.g. Stata) will provide helpful for an analysis of markets related to credit risk.
Students will become familiar with the products and models used in today’s credit markets such as internal and external ratings, credit default swaps (CDS) and collateralized debt obligations (CDO’s), structural asset value models, and also some concepts of the Basel capital accord. The application of these products and models will be discussed as well as pricing issues for credit risk trading. Additionally the interrelations of credit risk factors in security markets will be analyzed empirically.
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:
Perform simple regression analyses, also using forecasting methods
Evaluate single claim credit risk applying different methodologies such as structural models, ratings, 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)
Collateralized Debt Obligations (CDO)
Björn Imbierowicz is Economist in the Research Center of the Deutsche Bundesbank and Academic Director of the Financial Risk Management Program at Goethe Business School. Previously, he was Assistant Professor at the Department of Finance at Copenhagen Business School as well as Goethe University Frankfurt. He received his PhD from Goethe University Frankfurt and has been visiting professor at the University of Strasbourg and visiting scholar at NYU – Stern School of Business. His teaching specializes inter alia in corporate finance and risk management, his research on financial intermediation and risk management.
Course materials will be provided in electronic form.
Partially online via Zoom and Campus Westend of Goethe University Frankfurt.
A GBS certificate of participation is awarded upon completion of the course.
€ 1.900 (fee is exempt from VAT). The fee for GBS students or alumni amounts to € 800.
*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., Jun 4, 2021||15:30-17:30, 18:00-20:00|
|Sat., Jun 5, 2021||09:00-11:00 11:30-13:30|
|Fri., June 18, 2021||13:00-15:00 15:30-17:30|
|Sat., June 19, 2021||09:00-11:00 11:30-13:30|
|Fri., July 2, 2021||15:30-17:30 18:00-20:00|
|Sat., July 3, 2021||11:30-13:30 14:30-16:30|