Courses Summer Term 2026
Lectures
Corporate Finance is an introductory course that teaches the core concepts and analytical methods of corporate finance. Students acquire a foundational understanding of how financial decisions are made within companies and which tools are used in the process.
Learning Objectives
- Understand the concept of time value of money and applications in capital budgeting.
- Appreciate the features and valuation of marketable securities, including stocks and bonds.
- Evaluate the relationship between risk and return in financial investments.
- Analyze the capital structure of a firm and its impact on the valuation.
Taught by: Dr. Saswat Patra from Queen’s University Belfast.
ECTS: 4
Credit: M.Sc. Economics in the profile “Finance”, M.Sc. VWL in Finance, Accounting, and Taxation.
Language: English
Prerequisites: None
Examination: Take Home Exercise involving a case study
Schedule:
| Friday, June 5th | 12:00 – 02:00 p.m. | lecture hall 1009 KG I |
| Monday, June 8th | 12:00 – 02:00 p.m. | lecture hall 1015 KG I |
| Tuesday, June 9th | 12:00 – 02:00 p.m. | lecture hall 1009 KG I |
| Friday, June 12th | 12:00 – 02:00 p.m. | lecture hall 1009 KG I |
| Monday, June 15th | 12:00 – 02:00 p.m. | lecture hall 1015 KG I |
| Tuesday, June 16th | 12:00 – 02:00 p.m. | Postponed |
| Donnerstag, June 18th | 08:00 a.m. – 12:00 p.m. | Postponed |
| Friday, June 19th | 12:00 – 02:00 p.m. | Online BigBlueButton |
| Monday, June 22nd | 12:00 – 02:00 p.m. | Online BigBlueButton |
| Tuesday, June 23rd | 12:00 – 02:00 p.m. | Online BigBlueButton |
| Friday, June 26th | 12:00 – 02:00 p.m. | Online BigBlueButton |
| Monday, June 29th | 12:00 – 02:00 p.m. | Online BigBlueButton |
| Tuesday, June 30th | 12:00 – 02:00 p.m. | Online BigBlueButton |
| Monday, July 6th | 12:00 – 02:00 p.m. | Online BigBlueButton |
| Tuesday, July 7th | 12:00 – 02:00 p.m. | Online BigBlueButton |
This course introduces the fundamental process of statistical analytics and data science for finance to students interested in FinTech and financial modelling & forecasting. The course focuses on developing critical computational, statistical, and analytical skills essential for professionals conducting data-driven financial analytics in the FinTech area.
Learning Objectives
- Apply statistical and modern data science methods.
Evaluate financial data in a way that provides clear, actionable insights. - Understand machine learning in a financial context.
Learn about the most important algorithms and see how they are used in the financial industry. - Financial portfolio modeling and market risk analysis.
Understand methods for composing portfolios and assessing market and credit risks. - Use software tools for data analysis.
Solve real-world problems in the financial services sector using common analysis software (e.g., Python, R, Excel) and present the results in a comprehensible manner.
By the end of the course, you will be able to independently analyze financial data, draw meaningful insights, and use them to make well‑informed decisions.
Taught by: Dr. Saswat Patra from Queen’s University Belfast.
ECTS: 4
Credit: M.Sc. Economics in der Profillinie “Finance”, M.Sc. VWL in Finance, Accounting, and Taxation.
Language: English
Prerequisites: Basic Statistics and/or Econometrics courses
Examination: Take-Home Exercise involving real life problem with data
Schedule:
| Friday, June 5th | 08:00 – 10:00 a.m. | lecture hall 1009 KG I |
| Monday, June 8th | 04:00 – 06:00 p.m. | lecture hall 3044 KG III |
| Tuesday, June 9th | 06:00 – 08:00 p.m. | lecture hall 1009 KG I |
| Friday, June 12th | 08:00 – 10:00 a.m. | lecture hall 1009 KG I |
| Monday, June 15th | 04:00 – 06:00 p.m. | Postponed |
| Tuesday, June 16th | 06:00 – 08:00 p.m. | Postponed |
| Thursday, June 18th | 02:00 – 04:00 p.m. | Online BigBlueButton |
| Friday, June 19th | 08:00 – 10:00 a.m. | Online BigBlueButton |
| Monday, June 22nd | 04:00 – 06:00 p.m. | Online BigBlueButton |
| Tuesday, June 23rd | 02:00 – 04:00 p.m. | Online BigBlueButton |
| Thursday, June 25th | 08:00 a.m. – 12:00 p.m. | Postponed |
| Friday, June 26th | 08:00 – 10:00 a.m. | Online BigBlueButton |
| Monday, June 29th | 04:00 – 06:00 p.m. | Online BigBlueButton |
| Tuesday, June 30th | 06:00 – 08:00 p.m. | Online BigBlueButton |
| Monday, July 6th | 04:00 – 06:00 p.m. | Online BigBlueButton |
| Tuesday, July 7th | 02:00 – 04:00 p.m. | Online BigBlueButton |
The lecture introduces the basic principles of asset pricing and the valuation of contingent claims in both complete and incomplete market models.
Lecture
Taught by: Prof. Dr. Eva Lütkebohmert-Holtz
Schedule: Thursdays 12:00 – 02:00 p.m. in lecture hall 1098 KG I
First meeting: Thursday, April 23rd 2026
Tutorial
Taught by: Bartolomeo Fanciulli, M. Sc.
Schedule: Tuesdays 04:00 – 06:00 p.m. in lecture hall 1098 KG I
First meeting: Tuesday, April 28th 2026
Additional Tutorial in English
Taught by: Daniela Bencheva
Schedule: Tuesdays 08:00 – 10:00 a.m. in lecture hall 1098 KG I
Additional Tutorial in Mandarin
Taught by: Junru Liu
Schedule: Thursdays 08:00 – 10:00 a.m. in lecture hall 1016 KG I
ECTS: 6
Credit: M.Sc. Economics in the profile “Finance”; B.Sc. + M.Sc. Mathematik as an elective; M.Sc. VWL in “Accounting, Finance, and Taxation” and “VWL-Theorie”, M.Sc. BWL as an elective course Volkswirtschaftslehre.
Language: English
Prerequisites: Advanced Microeconomics I
Examination: 120 minutes written exam
In this lecture we present advanced models in discrete and continuous time for the valuation and hedging of various financial products. In addition to the standard European and American style put and call options, a range of more complex derivatives and exotic options are also introduced. Besides the pricing concepts, model calibration and simulation are covered as well.
Lecture
Taught by: Dr. Andrea Mazzoran
Schedule: Tuesdays 10:00 a.m. – 12:00 p.m. in lecture hall Max-Kade-Auditorium 2 (Alte Universität)
First meeting: Tuesday, April 21st 2026
Tutorial
Taught by: Dr. Andrea Mazzoran
Schedule: Thursdays 04:00 – 06:00 p.m. in lecture hall Max-Kade-Auditorium 2 (Alte Universität)
First meeting: Thursday, April 30th 2026
ECTS: 6
Credit: M.Sc. Economics in the profile “Finance”; B.Sc. + M.Sc. Mathematik as an elective; M.Sc. VWL in “Accounting, Finance, and Taxation” and “VWL-Theorie”, M.Sc. BWL as elective course Volkswirtschaftslehre.
Language: English
Prerequisites: Principles of Finance, Futures and Options, R-Vorkurs (recommended)
Examination: 120 minutes written exam
Literature:
- Hull, J.C.: Options, Futures, and other Derivatives, 7. ed., Prentice Hall, 2009.
- Materials supplied during the course
Seminars
Please note that the number of participants is limited – see below for registration!
This course provides an introduction to credit risk management with Python programming. Students will learn basic data processing techniques in Python, and how to analyze credit risk through factor models, including parameter calibrations and simulations. The course covers practical applications such as risk quantification, simulations, and data analysis in the context of credit risk management.
By the end of the seminar, students will be able to use Python for basic credit risk analysis, including data processing, risk quantification, and the application of factor models in credit risk management.
Taught by: Prof. Dr. Eva Lütkebohmert-Holtz, Hongyi Shen, M. Sc.
ECTS: 6
Credit: M.Sc. Economics (Finance); M.Sc. VWL (Accounting, Finance, and Taxation / Empirical Economics)
Language: English
Prerequisites: Principles of Finance, Futures and Options, Python Course
Examination: Seminar presentation and written paper.
Schedule: Always in room 01.012 (1st floor), Rempartstraße 16
| April | |
| Monday, April 20th | 04:00 – 06:00 p.m. |
| Thursday, April 23rd | 02:00 – 04:00 p.m. |
| Monday, April 27th | 04:00 – 06:00 p.m. |
| Thursday, April 30th | 02:00 – 04:00 p.m. |
| May | |
| Monday, May 4th | 04:00 – 06:00 p.m. |
| Thursday, May 7th | 02:00 – 04:00 p.m. |
| Monday, May 11th | 04:00 – 08:00 p.m. |
| Monday, May 18th | 04:00 – 06:00 p.m. |
| Thursday, May 21st | 02:00 – 04:00 p.m. |
| June | |
| Thursday, June 11th | 08:00 a.m. – 12:00 p.m. AND 02:00 – 04:00 p.m. |
Registration:
Please note the changed mandatory procedure for seminar registration. Starting in the summer semester 2026, seminar registration and deregistration will only be possible via a standardized registration procedure in HISinOne (similar to lectures or exercises). Please note the following periods:
Seminar registration (immediate admission)
Period: March 1, 2026 – April 12, 2026
You must register for seminars yourself in HISinOne. Places will be allocated according to the principle of immediate admission with an automatic waiting list.
Allocation of remaining places
Period: April 13, 2026 – April 24, 2026
Any seminar places that are not filled will be made available again for registration via HISinOne in a second phase.
Please adhere to the specified periods and register for your seminars in a timely manner.
Literature:
- Bielecki, T., & Rutkowski, M. (2002). Credit Risk: Modeling, Valuation and Hedging. Springer.
- Bluhm, C., Overbeck, L., & Wagner, C. (2010). Introduction to Credit Risk Modeling (2nd ed.). Chaman & Hall/CRC.
- Frey, R., McNeil, A. J., & Embrechts, P. (2015) Quantitative Risk Management – Concepts, Techniques and Tools (revised edition)
- Gordy (1998), A Comparative Anatomy of Credit Risk Models
- Gundlach, M., & Lehrbass, F. (2003). CreditRisk+ in the Banking Industry. Springer.
- Lando, D. (2004) Credit Risk Modeling. Princeton University Press.
- Lütkebohmert, E. (2009) Concentration Risk in Credit Portfolios. Springer.
- Perraudin, W. (2004) Structured Credit Products: Pricing, Rating, Risk Management and Basel II. Risk Books.
- Pykhtin, M. (2004). Multi-factor Adjustment. Risk Magazine.
Further literature will be announced in the course
Please note that the number of participants is limited – see below for application & registration!
This seminar is intended for Master’s students of the Chair of Quantitative Finance. It is intended as a forum in which students can present their research at various stages of preparing their master’s thesis. Students can discuss their progress, as well as any potential challenges or problems that have arisen and need to be resolved, with the members of the department.
Taught by: Prof. Dr. E. Lütkebohmert-Holtz
ECTS: 4
Credit: M.Sc. Economics (Finance); M.Sc. VWL (Accounting, Finance, and Taxation / Empirical Economics)
Language: English
Prerequisites: Master’s and PhD students of the Chair of Quantitative Finance
Examination: Seminar presentation
Schedule: Mondays 02:00 – 04:00 p.m. in room 01.012 Rempartstraße 16
First meeting: Monday, April 27th, 2026
Registration: Please register on HISinOne within the specified time frame.
Literature: Will be discussed individually