Syllabus

Title
0628 Y2E Portfolio Management - Foundations
Instructors
em.o.Univ.Prof. Dr. Josef Zechner
Contact details
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
09/03/19 to 09/22/19
Registration via LPIS
Notes to the course
Subject(s) Master Programs
Dates
Day Date Time Room
Tuesday 11/19/19 09:00 AM - 12:30 PM D4.0.127
Tuesday 11/26/19 09:00 AM - 12:30 PM D4.0.127
Wednesday 12/04/19 01:30 PM - 05:00 PM D4.0.127
Tuesday 12/10/19 09:00 AM - 12:30 PM D4.0.127
Tuesday 12/17/19 09:00 AM - 12:30 PM D4.0.127
Tuesday 01/07/20 09:00 AM - 12:30 PM D4.0.127
Tuesday 01/14/20 09:00 AM - 12:30 PM D4.0.127
Wednesday 01/22/20 01:30 PM - 03:30 PM TC.2.02
Contents

This course deals with modern investment theory and its application to portfolio management. Topics include asset allocation, security selection, and performance evaluation. The course should be taken concurrently with the course “Portfolio
Management: Applications”. In the applications course the concepts introduced in the foundations course will be used in a number of case studies and examples.


We will first review the basic concepts of portfolio theory, such as identifying the minimum variance portfolio and the tangency portfolio as well as factor models and the APT. Active portfolio management requires return predictability. Thus, the next part of the course will deal with the question whether return predictability exists and how it may be related to market efficiency. Thus, we will explore return predictability with a particular emphasis on the most important asset classes, namely stocks, bonds and commodities.


In the next part of the course we will develop concepts to utilize return forecasts as a basis for active asset allocation. In particular we will cover the Black‐Litterman Model as well as the model by Brandt Santa‐Clara and Valkanov.


Evaluating the success of portfolio management requires a concept for measuring the contribution of active asset allocation and security selection towards overall portfolio performance. Thus, we will introduce concepts of performance evaluation and performance attribution. Finally, we will discuss agency problems associated with delegated portfolio management.

Learning outcomes

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

  • Understand the role and possibility of portfolio management within the framework of modern capital market theoryAfter completing this class the student will have the ability to:
  • distinguish between asset allocation and security selection in passive and active portfolio management
  • appreciate the interplay between risk aversion and optimal capital allocation
  • construct passive and active optimal risky portfolios
  • master the Black-Litterman method to view-based optimal asset class allocation
  • evaluate the performance of portfoliosAfter completing this class the student will also have the 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
  • 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 incorporate consensus and individual forecasts into a mean-variance optimal portfolio
Attendance requirements

Attendance is mandatory! Students may miss no more than 2 classes.

Teaching/learning method(s)
The course will be taught in eight units of three hours each. It will consist of a mix of regular lectures, class room discussions and analyses of assignments. The lectures will be largely based on the instructor’s lecture notes, on the main textbook and additional readings and aim to communicate students the theoretical framework. There will be assignments to practice the concepts developed during the lectures. The assignments will involve quantitative analyses using Excel. Students will be allowed to work in small groups, consisting of a maximum of 3 students per group. Solutions to these assignments must be sent to the instructor electronically. The solution will be presented and discussed in class by the students.
Assessment
  • Final exam (45%): There will be a 90‐minute, closed‐book final exam.
  • Assignments (15% for Assignment 1, 20% for Assignment 2): Students have to hand in solutions to case studies and/or problem sets.
  • Presentation of Assignment 1 (10%): Students present the solutions to Assignment 1 in class
  • In‐class participation (10%): Students can earn up to 10% by participating actively in the class discussion by, for example, raising good questions, or giving good answers to questions raised by the instructor or other students in class.
  • Students need at least 50% of the total marks (exam + assignment +presentation + inclass participation) to pass the course.
Availability of lecturer(s)
josef.zechner@wu.ac.at
Other

Readings:

  • Bodie, Z., Kane, A., & Marcus, A. (2014). Investments (10th global edition). McGraw-Hill
  • Ang, Andrew, Asset Management (2014). A Systematic Approach to Factor Investing (1st edition). Oxford University Press

Additional readings:

  • Cochrane, John, H., (2005). Asset Pricing (revised edition). Princeton University Press
  • Grinold, R., & Kahn, R. (2000). Active Portfolio Management (2nd edtion). McGraw-Hill
  • Solnik, B., & McLeavey, D. (2005). International Investments (5th edtion). Pearson, Addison-Wesley

Additional material and papers will be uploaded to Learn@WU.

Last edited: 2019-11-19



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