1671 Course IV - Risk Management
Anna Zsofia Csiky, MSc (WU), Univ.Prof. Dr. Stefan Pichler
Contact details (interactive part), (admin questions). Please indicate your course number!
Weekly hours
Language of instruction
09/13/23 to 09/24/23
Registration via LPIS
Notes to the course
Day Date Time Room
Wednesday 12/06/23 01:00 PM - 03:15 PM TC.0.03 WIENER STÄDTISCHE
Wednesday 12/13/23 10:15 AM - 12:30 PM TC.4.02
Wednesday 12/13/23 01:00 PM - 03:15 PM TC.0.03 WIENER STÄDTISCHE
Wednesday 12/20/23 10:15 AM - 12:30 PM TC.4.02
Wednesday 12/20/23 01:00 PM - 03:15 PM TC.0.03 WIENER STÄDTISCHE
Wednesday 01/10/24 10:15 AM - 12:30 PM TC.4.02
Wednesday 01/10/24 01:00 PM - 03:15 PM TC.0.03 WIENER STÄDTISCHE
Wednesday 01/17/24 10:15 AM - 12:30 PM TC.4.02
Friday 01/19/24 02:00 PM - 04:15 PM TC.0.03 WIENER STÄDTISCHE
Wednesday 01/24/24 10:15 AM - 12:30 PM TC.4.02
Friday 02/02/24 01:00 PM - 02:30 PM Präsenz-Prüfung

Unit 1: Statistical foundations (Ch 22.1, lecture notes)

o General concepts of risk and uncertainty

o Risk measures (dispersion based vs. quantile based) and their properties

o Methods to compute VaR under normality or using the empirical sample distribution

o Extension to the multivariate case


Unit 2: Economic foundations (Ch. 21-22, lecture notes)

o Why is hedging relevant? How does hedging compare to the MM-world?

o Main focus on financial distress costs

o Managing systematic vs. unsystematic risk

o Valuation of corporate debt considering total risk: concept of credit ratings and PDs

o Maintaining locally optimal costs of capital: ROEC and RORAC


Unit 3: Credit risk (lecture notes)

o Probabilistic credit risk models: univariate case

o Probabilistic credit risk models: multivariate case

o Single-factor model and connection to CAPM/market model

o Credit VaR: simulation with given parameters, calibration to observable data


Unit 4: Interest rate risk (Ch. 23, lecture notes)

o Measures of interest rate risk (duration, PV01)

o Basics of asset-liability-management

o Debt financing decision: fixed or floating?


Unit 5: FX risk (Ch 22.2, lecture notes)

o Foundations of FX markets (institutions, structure, instruments, quotation)

o Economic determinants of FX rates

o Measuring FX risk

o Hedging FX risk with forwards and options

Learning outcomes

After completing the course, students will understand

· The statistical properties and economic foundations of important risk measures

· How to compute important risk measures based on market data

· How to connect risk management and hedging to the Modigliani-Miller model

· The concept of credit ratings and default probabilities to measure credit risk

· How to compute and how to apply measures of interest rate risk

· How to compute and how to apply measures of FX risk

Attendance requirements

Participation is compulsory in the interactive part. There are grade related performance assessments in each interactive unit. It is not possible to get points for those assessments if you are not present. Note that students may still pass the course if they are absent in the interactive sessions once only. However, students will fail the course if they are absent in the interactive sessions twice or more.

Teaching/learning method(s)

The course is composed of two parts, a lecture part (5 units) and an interactive part (5 units). The lecture part is organized in one big class for all students of the specialization. The interactive part is organized in small groups (max. 30 students). The five lecture units take place once a week. The five interactive units also take place once a week, but start one week after the first lecture unit.

The teaching approach of the lecture part is the traditional class room teaching. In the interactive part a mix of methods is applied that includes student presentations of numerical examples (“mini-cases”), class discussions, presentations by the lecturer and real-life case studies. There will be a final exam which covers the content of the lecture part, the interactive part, as well as the specified textbook chapters.

Based on the introduction to the underlying concepts in the lecture part, students will have to prepare small numerical problems ("mini-cases") for the interactive part. The concepts of the first lecture unit are applied and deepened in the first interactive unit, and so on. The mini-cases are presented by students and solutions are discussed with the lecturer. In addition, more involved case studies are discussed to provide additional insight into industry applications.

The courses are held on campus. The final exam will take place on campus and will be conducted on Learn. You need to bring your own device and access the online exam environment from the exam room.

Please note the following policy regarding the hybrid mode of this course:
Streaming of the lecture units will only take place if the number of students in the room exceeds the room capacity. Seats in the lecture room are available on a first come  - first serve basis. The interactive classes will never be streamed.


The components for the grades are weighted as follows:

  • 40% final exam
  • 60% interactive part

Interactive part: Students have to prepare mini-cases for the weekly sessions. Before a specific deadline for each interactive unit, students have to complete an assignment by answering true-false questions that indicate which problems they have solved and by uploading their solutions. Each example will be presented by a randomly selected student who checked this problem. Students need to solve a minimum number of mini-cases to pass the course. The baseline number of mini-cases and the minimum number to pass will be communicated before the start of the interactive part, e.g., a baseline of 27 mini-cases with a minimum of 19 mini-cases to pass. Note, the baseline number serves as a reference, there can be more but never less mini-cases than indicated by this number.

The presentation of mini-cases will be evaluated. Students need to be able to solve the mini-cases they present and explain their reasoning. A negative assessment of a student's presentation reduces the number of checked mini-cases by 6. The same deduction applies if a student indicates mini-cases he/she did not solve.

Note that two failed presentations will always lead to a number of checked mini-cases that is below the necessary minimum number and, thus, the student fails the course.

Grading: Formally, the evaluation is based on the percentage of credits earned (minimum of 50% of credits needed to pass). This percentage of credits C will be computed by C = 0.4*Clecture + 0.6*CinteractiveClecture denotes the percentage of credits earned at the final exam (between 0% and 100%). Cinteractive denotes the percentage of credits earned for the interactive part. The interactive part credits are calculated by dividing the checked mini-cases (after potential reductions for fails) by the baseline number of mini-cases, e.g., 21 checked mini-cases / 27 = 77.78%. If the checked number of mini-cases is below the minimum number, the resulting credit for the interactive part is 0% and the student fails the course. If the checked number of mini-cases is above the baseline number of mini-cases, the resulting credit for the interactive part is 100%, i.e., Cinteractive is capped at 100%.

For example: The student scores 90% in the final exam and 77.78% in the interactive part, then C = 0.4 * 90% + 0.6 * 77.78% = 82.8%.

The following grading scheme based on C is applied:

Percentage Grade
[87.5%;100%]: 1 1
[75%;87.5%): 2 2
[62.5%;75%): 3 3
[50%;62.5%): 4 4
<50%: 5 5

square bracket [ ] = percentage is still included in the quantity
round bracket ( ) = percentage is no longer included in the quantity

Please note that you will receive a grade for this course as soon as you upload and indicate exercises for an interactive unit.

Prerequisites for participation and waiting lists

Students need to be admitted to the specialization Finance: Markets, Institutions & Instruments and need to have completed Course I and Course II successfully to register for the course.


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Recommended previous knowledge and skills

Basic knowledge of Excel or R, basics in Statistics

Availability of lecturer(s)

Last edited: 2023-10-04