Practical Financial Optimization
Course content
Week One
- Day 1: Introduction to GAMS using mean-variance/ mean-standard-deviation-optimization.
- Day 2: Continued introduction to GAMS. Adding practical constraints such as fixed costs, size limits, and gearing to the mean-variance model. Analysing results in Excel.
- Day 3: Continued introduction to GAMS. Scenario-based optimization models and scenario generation.
- Day 4: Value at Risk and Conditional Value at Risk. Introduction to Investment Funnel.
- Day 5: Feature selection in asset allocation. Introduction to the final project.
Week Two
- Students will work on their final project in class. By the end of the week, they must hand in a project report.
Knowledge:
See course contents above.
Skills:
Participants will be trained in quantitative evaluation of
risk-return trade-offs, and learn how to model, solve, and document
large, practical problems.
The course also introduces the programming language GAMS (General
Algebraic Modelling Systems), which will be used extensively
in all cases and examples.
Participants completing the course will acquire skills in:
- Measuring and managing return and risk trade-offs
- Adding practical constraints to financial optimization problems
- Scenario generation using bootstrapping
- Modelling Value at Risk, Conditional Value at Risk, and Index Tracking
- Feature selection in asset allocation using hierarchical clustering and minimum spanning tree
- Back-testing the results of optimization models
Competencies:
The course gives an introduction to the domain of practical financial risk and portfolio management. Participants will work with problem areas that can be attacked using optimization models.
3 hours of lectures and 3 hours of tutorials (work on
assignments) per day during week 1. The lectures and tutorials are
taught online.
During the 2nd week students work on a larger project and have to
hand in a written report by the end of the week.
Reading material will be sent out in July.
Example of course literature:
- A GAMS Tutorial
- Zenios, Stavros A. (2008), "Practical Financial Optimization: Decision Making for Financial Engineers", Blackwell.
An introductory course in finance, an introductory course in
operations research, and basic programming literacy. (The first two
years of the BSc Programme in Mathematics-Economics will do
nicely.)
Academic qualifications equivalent to a BSc degree is
recommended.
Continuous feedback during the course
- ECTS
- 7,5 ECTS
- Type of assessment
-
Oral exam on basis of previous submission, 15 minutes (no preparation time)
- Type of assessment details
- The report will be the focal point of the examination.
The grade will be given based on an overall evaluation. - Aid
- Only certain aids allowed (see description below)
The student can bring the report for the examination.
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Severel internal examiners
- Re-exam
-
20-minute oral examination (no preparation time), no aids allowed.
Criteria for exam assessment
See Learning Outcome
Single subject courses (day)
- Category
- Hours
- Lectures
- 30
- Class Instruction
- 10
- Theory exercises
- 10
- Practical exercises
- 10
- E-Learning
- 90
- Study Groups
- 40
- Exam
- 16
- English
- 206
Kursusinformation
- Language
- English
- Course number
- NMAK15000U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Placement
- Summer
- Schedulegroup
-
3-28 August 2026
Online summer course - Capacity
- 40
The number of places might be reduced if you register in the late-registration period (BSc and MSc) or as a credit or single subject student. - Studyboard
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Mathematical Sciences
Contracting faculty
- Faculty of Science
Course Coordinator
- Rolf Poulsen (4-74716e68426f63766a306d7730666d)
Teacher
Kourosh Marjani Rasmussen
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