ME-431 Quantitative Methods in Finance. BE-421 Investments or equivalent
Learning outcomes
Upon successful completion of this course the student should be able to
Use the open-source R-programming language to retrieve, process and plot data.
Compute and analyze financial asset return and covariance matrices.
Design various portfolio optimization problems such as mean-variance and use the Black-Litterman model.
Design various constraints that portfolio managers meet in practice.
Solve the portfolio optimization problem using R to find the optimal portfolio for a given optimization problem and given constraints.
Solve portfolio optimization problems both theoretically/mathematically and practically using R.
Understand some numerical techniques needed to solve arising problems.
Contents
The aim of this course is to provide understanding about how investment portfolios should be diversified to control risk. This is in accordance with SDG # 8 (Decent work and economic growth). Portfolio managers who try to diversify their portfolio and simultaneously incorporate their market views, will often experience that this task is far from trivial. In this course we will study the various constraints portfolio managers typically meet. We will study how we can make R-programs that find the optimal portfolios where both the market views from analysts, the chosen diversification and the constraints are fulfilled.
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
Term paper (100%). Group examination. Groups of 2-3 students. The group as a whole is graded. Letter grades. More details will be available in Canvas.
Student evaluation
Course evaluation in accordance with the quality system for education, chapter 4.1.