Table of contents

The course is connected to the following study programs

Teaching language

English.

Prerequisites

ME-431 Quantitative Methods in Finance and BE-421 Investments or equivalent.

Learning outcomes

Upon completion of this course the student should be able to

  • Understand and critically evaluate the principles of mean-variance optimization and its limitations.
  • Incorporate practical constraints (e.g., restrictions on short-sale, leverage, and turnover) into portfolio construction.
  • Recognize and mitigate estimation errors when implementing optimization in practice.
  • Apply alternative portfolio construction methods beyond mean-variance optimization, as proposed in contemporary scientific papers.
  • Perform portfolio backtesting using real-world data and interpret results with proper statistical rigor.
  • Use bootstrap and resampling methods to assess inference and robustness in portfolio evaluation.
  • Conduct multiple testing inference to avoid spurious conclusions when comparing investment strategies.
  • Implement all techniques in R, gaining reproducible coding and data analysis skills relevant for portfolio management.

Contents

This course provides a hands-on introduction to modern portfolio management with a strong emphasis on practical implementation. While mean-variance theory serves as a starting point, we do not restrict ourselves to this classical framework. The course explores a range of contemporary approaches to portfolio construction proposed in the scientific literature, including methods designed to address estimation risk, constraints, transaction costs, and statistical inference challenges. The course is grounded in recent research and emphasizes techniques that bridge theory and practice, such as shrinkage, resampling, bootstrap inference, and robust backtesting procedures. Students will work extensively with real-world financial data and implement portfolio strategies in R, developing both technical and empirical skills directly applicable to professional investment practice.

Teaching and learning methods

The course consists of lectures, group-work sessions and assignment. Estimated workload is about 200 hours.

Examination requirements

Approved mandatory assignment. More information will be given in Canvas at the start of the semester.

Examinations

The examination consists of a term paper submitted either by an individual student or by a group of two students. In the case of group work, a single grade is awarded to the group as a whole. Assessment expression: letter grade, A-F. Further details will be available on Canvas.

Student evaluation

The person responsible for the course decides, in cooperation with the student representative, the form of student evaluation and whether the course is to have a midway or end of course evaluation in accordance with the quality system for education, chapter 4.1.

Offered as a free-standing course

No.

Reduction of Credits

This course’s contents overlap with the following courses. A reduction of credits will occur if one of these courses is taken in addition:

Course Reduction of Credits
BE-513 – Practical Portfolio Management . 5
Last updated from FS (Felles studentsystem) Oct. 15, 2026 7:42:26 AM