The course is connected to the following study programs

Teaching language

English

Recommended prerequisites

Knowledge of math calculus and basics of optimization, statistics, and R programming. Builds upon parallel courses: ME-431-1 Quantitative Methods in Finance and SE-419-1 Financial Econometrics

Course contents

The aim of this course is to provide a detailed treatment of the main theoretical foundations of modern investment theory and give students necessary skills in applying theoretical models using real-life data. On the theoretical side, the course presents in-depth coverage of the relationship between the risk and return, mean-variance portfolio theory, Capital Asset Pricing Model (CAPM), Arbitrage Pricing Theory (APT), and portfolio performance evaluation. A particular emphasis is placed on the derivation of the theoretical asset pricing models and a rigorous mathematical argumentation. On the practical side, using the open source R statistical programming language, the students learn how to retrieve and analyse financial data, implement all theoretical models considered in the course, and evaluate the performance of financial portfolios.

Learning outcomes

Upon successful completion of this course the students should be able to

  • Discuss the trade-off between the risk and reward

  • Explain the optimal capital allocation between the risky and risk-free assets

  • Master the mathematics of mean-variance portfolio theory and construction of efficient portfolios

  • Compute and analyze financial asset returns

  • Construct mean-variance efficient portfolios using real financial data

  • Fully understand the mathematics of the capital market equilibrium including the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT)

  • Estimate the single index and multifactor models using ordinary least squares

  • Evaluate and compare performances of financial portfolios

Examination requirements

Approved mandatory assignments. More information is available in Canvas.

Teaching methods

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

Evaluation

End of course evaluation in accordance with the quality system for education, chapter 4.1.

Assessment methods and criteria

Individual written assignment (home exam) counts for 40 %, and 3-hour written examination counts for 60 % of the final grade. Grading by letters.

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-419 – Finance Theory 2.5
BE-506 – Computational Finance and Portfolio Mangement 2.5
Last updated from FS (Common Student System) June 30, 2024 3:34:46 PM