Language of instruction
|Monday||11/29/21||10:00 AM - 01:30 PM||Online-Einheit|
|Monday||12/06/21||10:00 AM - 01:30 PM||Online-Einheit|
|Monday||12/13/21||10:00 AM - 01:30 PM||Online-Einheit|
|Tuesday||12/14/21||02:30 PM - 06:00 PM||Online-Einheit|
|Monday||12/20/21||10:00 AM - 01:30 PM||Online-Einheit|
|Monday||01/10/22||10:00 AM - 01:30 PM||D4.0.136|
|Monday||01/17/22||10:00 AM - 01:30 PM||Online-Einheit|
|Wednesday||01/26/22||10:00 AM - 12:00 PM||Online-Einheit|
Students who have successfully completed this course will have acquired the following skills:
- understand the role and possibility of active portfolio management within the framework of modern capital market theory
After completing this class the student will have the ability to:
- distinguish between asset allocation and security selection in active portfolio management
- know about return and risk from historical records and its implications for forecasts
- appreciate the interplay between risk aversion and optimal capital allocation
- know-how to construct optimal risky portfolios
- understand how active portfolio managers can select individual equity and fixed income securities based on their forecasts
- evaluate a portfolio’s performance and to attribute ex-post portfolio performance to skill, luck, security selection, market timing, asset allocation etc.
Moreover, the class will contribute to the students’ ability to:
- analyze and solve complex portfolio problems individually and as a member of a group and to develop solutions by functioning as a valuable and cooperative team member
- summarize and professionally present solutions in class
- adequately communicate and participate in in-class discussions
- solve and present a case study in small groups
After completing this class the student will also have the ability to:
- find the necessary literature and data to solve complex portfolio problems using (e.g., the Internet, Reuters, Bloomberg)
- master reasonably complex problems in MS Excel: Use matrix formulas to solve linear programming and regression tasks. Employ the Solver tool to implement optimization constraints
- develop an Excel-based model to attribute performance to the different dimensions of active portfolio management or to implement a scoring model
Attendance is mandatory! Students may miss no more than 2 classes.
- Final exam (35%): There will be a 90-minute, closed-book final exam.
- Case study (30%): Students have to hand in solution to a case study and prepare a presentation in groups
- Computational assignment (35%): Students have to solve a portfolio problem with Microsoft Excel
- In-class participation (5% extra): Students can earn up to 5% in bonus points by actively participating in the class discussion by, for example, raising good questions, or giving a good answer to questions raised by the instructor or other students in class.
- Students need at least 50 points in total (exams + case study + assignment + in-class participation) to pass the course.
Please contact the lecturer if you have further questions about the assessment.
- Completion of the assessment phase
- Successful completion of 8 courses within the subject "GrundlagenFinanzwirtschaft, Rechnungswesen und Steuern" ("Basics in Finance,Accounting and Taxes")
- Allocation to the elective