Following an introduction and overview, we continue with the Markowitz mean-variance optimization technique and its application in portfolio construction and asset allocation.We show how to identify the minimum-variance set and explore several important properties of the portfolio frontier, including the two-fund separation theorem and the linear beta/return relation. Next, we review the Capital Asset Pricing Model. We derive the main results of these models and examine their empirical relevance and implications for portfolio management. We then discuss the concept of market efficiency and relate it to various documented stock return "anomalies".
In the second half of the course, we discuss in detail the Arbitrage Pricing Model. We look at empirical cross-sectional asset pricing studies, e.g., several papers by Fama and French. Finally, the course deals with performance measurement. We will cover relative performance, tracking error and information ratio, as well as risk adjusted performance measures such as the Sharpe Ratio, the Jensen Alpha and the Treynor Index. Furthermore the method of style analysis will be introduced.
On succesful completion of this course, students will have acquired the following competencies:
- Knowledge about return and risk from historical records
- An understanding of the interplay between risk aversion and optimal capital allocation
- Know how to construct optimal risky portfolios
- An understanding of the major equilibrium asset pricing models such as the CAPM and the APT
- The ability to evaluate a portfolio’s performance
Furthermore, the classes contribute to the students’ ability to:
- Work effectively in groups, by working on complex portfolio problems
- Deliver professional presentations
- Adequately communicate and participate in in-class discussions
- Find, read and understand relevant academic literature
- Find and use relevant data to solve portfolio optimization problems
A maximum of four sessions (including the exam sessions) may be missed.
The course consists of a mix of mandatory regular lectures, class room discussions of readings, calculation, and data analysis assignments. The lectures will be largely based on the instructors’ lecture notes, on the main textbook and additional readings. There will be a hands-on assignments to practice the concepts developed during the lectures. The assignment will involve quantitative analyses using MS Excel. Students will have to work in groups of three students. Solutions to these assignments must be uploaded to learn@wu.
The evaluation will be based on:
- Mid-term exam (35%): There will be a 90-minute, closed-book mid-term exam.
- Final exam (40%): There will be a 90-minute, closed-book final exam. All course material is relevant to the final exam.
- Assignment (15%): The assignment has to be solved in groups of 3 students.
- Class participation (10%). We will regularly give short reading assignments which will be discussed in class. Students will earn participation points from summarizing and critically discussing the readings in class, guided by questions raised by the instructors.
Students need at least 50% of the total points to pass this course. The remaining cut-off points are 65, 77.5, 90.
Since the evaluation is an immanent aspect of the class (PI), there is no right to any retake exam.
Voluntary Enrichment Course
There may also be a companion voluntary enrichment course that facilitates understanding of the material covered in the course „Asset Management“, by allowing for Q&A in small groups, solving jointly with the instructor textbook exercises and exam like exercises. There will be no new concepts covered, but there is time to recapitulate the conceptionally and practically difficult topics from asset management.
The voluntary enrichment course is purely voluntary. No credits are earned, there will be no grading.
Instructors are current PhD students of finance to ensure that they are able to explain thoroughly even the more advanced topics covered.
At this point, it is not clear if the voluntary enrichment course will take place.