The courses Asset/Risk Management I and II deal with modern investment theory and its application to portfolio and risk management.
Topics of Asset/Risk Management I include:

• Institutional background.
  We will discuss assets (liquid and illiquid asset classes) and asset owners (major investor types)
• Market efficiency and active versus passive investment
  Concepts of market efficiency and limitations, noise trader risk, liquidity spirals. 
• Stocks
  Historical return distributions, time varying market risk premium, predictabilty. Factor premia: portfolio sorts, quantification of factor premia using regression analysis. Parametric portfolio choice for equities.
• Government bonds
  Key concepts and empirical facts; time varying bond risk premia, predictability.
• Measurement and management of portfolio risks
  Hedging of foreign exchange risk; minimum variance portfolios; Value-at-Risk.
• Performance measurement
  Returns-based performance evaluation; portfolio holdings based evaluation.

Students who have successfully completed this course will have acquired the following skills:

• understand concepts of active portfolio management
• form expectations on risk premia for the major asset classes equities and government bonds
• applying techniques to measure portfolio performance and risk

In addition, students will have learned to

• analyze portfolio problems based on real-world data using R
• summarize and professionally present solutions to complex portfolio problems individually and as a member of a group

Full attendance is compulsory. This means that students have to attend at least 80% of all lectures.

The course will consist of a mix of regular lectures, class room discussions, and analyes of assignments. The lectures will be largely based on the instructor's lecture notes. A textbook is suggested for background reading and to help students refresh basic investments knowledge which is a prerequisite. Additional readings are assigned before classes. There will be assignments to practice the concepts developed during the lectures. These will involve quantitative analyses using R, to be solved in small groups. Students will present and discuss solutions in class.

Components:

• 20% individual assignment. The points will be based on the quality of the solution (deadline June 14) and a brief individual examination (online meeting slots will be scheduled on June 26 and June 27 from 15:00-17:30).
• 30% mid-term exam
• 10% in-class participation: 0-2 points per class are assigned for answering questions by the instructor and contributions to in-class discussion and/or short closed-book online quizzes taken in the classroom
• 40% final exam

Grading:

1. [90 - 100]
2. [80 - 90)
3. [65 - 80)
4. [50 - 65)
5. < 50%

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