The Chair of Sustainable Banking and Finance offers the following modules for masters students committing to the focus “Banking and Insurance”. Students committing to a different focus or attending a different study program are also welcome

The password for documents and Moodle courses is displayed in the showcase of the chair on the 3rd floor of the building of the Faculty of Economics and Management Science, across from the elevator. Additionally, it will be announced in each introductory session.

Mandatory Modules

Credit Points: 10 LP
Examination: project
Language: English
Semester: Winter semester

The module provides an overview of the fundamentals of financial market regulation. To this end, reasons for state interventions in the financial sector, instruments used in these interventions, and their advantages as well as disadvantages are presented. Moreover, students deal with selected regulatory authorities and proposals to reform financial market regulation.

Moodle course

Credit Pointrs: 10 LP
Examination: project
Language: German
Semester: Summer semester

In this module, current questions from both research and practical application in the areas of financial markets, investment management, and insurance business are discussed. The Chair of Sustainable Finance is responsible for the part dealing with financial markets. The part about investment management is offered by the Institute for Finance, Accounting, Controlling, and Taxation. The part about insurance business is offered by the Chair of Insurance Economics. After the successful completion of the module, students know about the most important current issues in finance and are able to name the challenges companies face in practice. Moreover, students can analyze and solve current questions from both research and practical application in finance independently with scientific methods. Additionally, they are able to present their results.

MOODLE COURSE

Elective Modules

Credit Points: 10 LP
Examination: Exam
Language: English
Semester: Summer semester

This lecture focuses on different methods and models from risk management and asset pricing against the background of a fast and efficient numerical calculation. In the course of the lecture, a special focus lies on different algorithms to price options (and other derivatives). All algorithms are illustrated using applications from risk management in banks, insurance companies, and energy companies. They are implemented in MATLAB.

MOODLE COURSE

Credit Pointrs: 5 LP
Examination: Exam
Language: German
Semester: Winter semester

In this module, students’ knowledge of the risk type “operational risk” is deepened by considering significant events of damage and threat potentials in the financial sector. Contents of the module are the role of operational risk in supervisory law, the regulation of banks’ equity capital (current regulations according to Basel II and new regulations according to Basel III), the requirements of managing operational risk and capital adequacy within banks, further possibilities of managing operational risk (e.g. stress testing and plans for emergencies/restructuring), and the special features of regulating operational risk in non-banks.

Moodle course

Credit Points: 5 LP
Examination: Exam
Language: English
Semester: Summer semester

After actively participating in this module, students are able to explain both the legislative and the institutional characteristics of EU and US bank law and financial law and state key differences between both systems. Students are able to describe the most important features of European law. These include equity capital requirements, bank supervision, primary and secondary financial markets, financial instruments (focusing on derivatives), and market infrastructure. Moreover, students can explain the lawmaking process of financial regulations as well as new pan-European supervision systems. Furthermore students are able to reflect on the reforms of the US financial system and the German supervisory system following the financial crisis. As a consequence, students can derive the key differences between both systems.


MOODLE COURSE

Credit Points: 10 LP
Examination: project
Language: English
Semester: Summer semester

In this module, advanced academic works in selected areas of corporate governance and executive compensation are considered. Students learn about different structures of governance and theories of executive compensation and are able to critically examine them. Moreover, students can apply theories and methods from the areas of corporate governance and executive compensation to analyze important problems, derive solutions to current challenges, and perform empirical studies to this end.

Moodle course

Credit Points: 10 LP
Examination: Exam
Language: English
Semester: Winter semester

This module focuses on agency problems, which influence companies on different levels. During the course, comprehensive theoretical models, which investigate how companies facing information asymmetry and conflicts of interest can obtain necessary debt financing, are presented. The problems of credit rationing, the optimal maturity structure of liabilities, the determinants of companies’ borrowing capacity, theories of the pecking order, and the optimal distribution of control rights within a company are considered.

Moodle course

Credit Points: 5 LP
Examination: project
Language: English
Semester: Winter semester

Within the scope of the module, methods of quantitative risk management are deepened. The students learn to independently analyse real financial market data sets and to examine investments compiled from these with regard to their risk profile. The students are introduced to the most important tools of multivariate statistics and time series analysis and learn to apply them using statistical software. After completing the module, the students will be able to autonomously evaluate and solve real problems of financial risk management.

Moodle-COurSe
 

Credit Points: 5 LP
Examination: Exam
Language: English
Semester: Summer semester

In this module, students learn to independently structure and analyse large, unstructured data sets from the financial sector. The students learn to handle common programming languages and programme packages (Python, TensorFlow, R, etc.) and to independently master the tasks set in the course. The aim is to independently evaluate and solve real-life problems in finance arising from large amounts of data in the area of risk management, asset allocation or derivatives valuation using modern machine and deep learning tools.

MOODLE-CouRse

Information about working scientifically as well as layout templates for the term papers can be found in the download section on the Theses subpage.

This may also be interesting to you ...

Student Advisor of the Faculty

Read more

Student Council of the Faculty

Read more

Academic Calendar

Read more