Seminar: Applied Computational Finance (3 ECTS)
Students work in pairs to identify and solve an investment-related problem with statistical tools. This seminar is ideally suited for students who want to deepen and apply their knowledge from classes like investments and statistics. Based on recommended literature, students will use financial data and software (written in R or Python) to answer a question along the investment management process. Topics which students solved in the past include the evaluation of a low volatility strategy for a pension fund, investigating the causes of the quant fund meltdown in 2007 and the implementation of a market neutral strategy for an endowment fund. Topics will arise from recommended literature and in collaboration with the supervisor.
Bachelor Thesis Seminar (0 ECTS)
Students who write a bachelor thesis at the Chair present their findings and state open questions on a regular basis. All Bachelor thesis writers are invited to participate to learn from the research of their fellow students and to benefit from the professor's and PhD student's feedback.
Lecture: Building Intelligent Robo-Adviced Portfolios (9.0 ECTS, 4/2)
This is a course on portfolio management. Already today, there is large fraction of wealth that is managed on an at least semi-automated basis. It is expected that this trend continues at an accelerated speed. Students in this course learn all the necessary financial economic know-how that is necessary to set-up their own robo-advisor. Industry experience is revealed via several real-world case studies that focus on topics like ethical investing, the global financial crisis of 2008, investing in illiquidity, the quant crash, the low risk anomaly and factor investing. The additional engineering-like skills that are essential for building intelligent and robo-adviced portfolios will be taught and trained throughout the course. Several (optional) problem sets provide opportunities to apply the concepts with real-world data and software.
Lecture/Project: Engineering FinTech Solutions (4.5 ECTS, 2/1)
This project invites students to either pursue their own FinTech innovation project or to contribute to the Chair's ongoing innovation projects. Students will also learn to connect innovative financial research with modern information technology to build a prototype that solves some daunting tasks for professional end-users in the field of modern asset and risk management. Depending on the topic, students work alone or in groups. Students are required to have obtained a grade of 1.7 or better in either "Computational Risk and Asset Management" and/or "Bayesian Risk Analytics and Machine Learning" or a grade of 1.3 or better in a Bachelor thesis with an above average amount of computational aspects (i.e. proofed affinity for computational modeling) at e.g. the AIFB, OR, Statistics, FBV or Informatics institute.
Seminar: Automated Financial Advisory (3 ECTS)
This seminar has to be taken together with the lecture/project "Engineering FinTech Solutions".
Programming Internship: Computational FinTech with Python and C++ (1.5 ECTS)
Thi programming internship has to be taken together with the semiar "Automated Financial Advisory".
Seminar: Applied Risk and Asset Management (3 ECTS)
see winter term.
Master and PhD Thesis Seminar (0 ECTS)
Students who write a master or PhD thesis at the Chair present their findings and open questions on a weekly basis. All thesis writers are invited to participate to learn from the research of their fellow students and to benefit from the professor's and PhD student's feedback.