Master's Programme in Business Administration (5 years)
Language of instruction
ME-201-1 Business analytics 2 (7.5 ECTS credits) or equivalent course
Upon successful completion of this course the student should be able to
safely apply appropriate methods and concepts such as R-programming, portfolio theory, expected utility theory and measuring risk attitudes, in order to solve decision problems under uncertainty demonstrate advanced knowledge of and be able to safely carry out matrix/vector algebra, including, but not limited to, matrix/vector multiplication, determinants of matrices, and definiteness of matrices
demonstrate solid understanding of calculus and linear algebra in general, which the students should also be able to safely apply to solve problems in economics and finance
in particular, safely solve optimization problems using the Lagrange multiplier and Kuhn-Tucker methods
The objective of this course is to endow the students with quantitative methods and programming tools required for financial economics. The students are going to learn how to apply the methods by working through practical examples drawn from and relevant for subsequent courses in the Analytical Finance specialization. After having learned matrix and linear algebra, the students are going to use this knowledge to solve optimization problems using the Lagrange multiplier and Kuhn-Tucker methods in the second part of the course.
The course consists of lectures and group-work sessions. Estimated workload is about 200 hours.
Approved mandatory assignments. More information will be given in Canvas at the start of the semester.
Assessment methods and criteria
4-hour written examination counts for 100 % of the final grade. Grading by letters.
End of course evaluation in accordance with the quality system for education, chapter 4.1.