NMAK14030U Practical Financial Optimization
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 constraints and gearing to the mean variance model. Analysing the results in Excel.
Day 3 Continued introduction to GAMS. Introducing classical concepts in fixed income modelling and management: yield curve generation, portfolio dedication and immunization.
Day 4 and 5 Project work. The participants will be asked to formulate, solve and analyse a GAMS model based on a given problem formulation. The results should be presented at the end of week 1.
Week Two
Day 1 Scenario generation and optimization. Case: index tracking and regret minimization.
Day 2 Scenario optimization continued. Case: Value at Risk and Conditional Value at Risk.
Day 3 Stochastic programming. Case: Mortgage loan refinancing.
Day 4 The final project will be introduced. We will work together on developing a back-testing framework for use in the final project.
Day 5 We will work on the final project in the class. By the end of this day the students should be able to perform independent work on the project.
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.
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 gives an introduction to the programming
language GAMS (General Algebraic Modelling Systems),
which will be used extensively in all the cases and
examples.
Participants who have followed the course will be able to formulate
and solve optimization problems in GAMS in particular within the
following areas:
- Measuring and managing return and risk trade offs
- Adding practical constraints to financial optimization problems
- Immunization and dedication of a bond portfolio
- Modelling Value at Risk and Conditional Value at Risk
- Back-testing results of ex-ante optimization
Knowledge
See course contents above.
“A GAMS Tutorial”: http://www.gams.com/dd/docs/gams/Tutorial.pdf
Zenios, Stavros A. (2008), "Practical Financial Optimization: Decision Making for Financial Engineers", Blackwell.
After that (or: during the 2nd week) students are given an assigment to which they must (before the regular teaching block begins) hand in written answers (a report).
- Category
- Hours
- Exam Preparation
- 6
- Exercises
- 30
- Lectures
- 30
- Preparation
- 70
- Project work
- 70
- Total
- 206
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- Credit
- 7,5 ECTS
- Type of assessment
- Oral examination, 15 min.Written assignment, One weekNo preparation time. 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
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
- 15 minutes oral exam (excl. grading) without preparation time. Here, the student will draw a question from a pre-specified list covering the full course contents.
Criteria for exam assesment
The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.
Course information
- Language
- English
- Course code
- NMAK14030U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- Two weeks in August 2014. Monday August 11 to Friday August 22. (Teaching only on weekdays.)
- Placement
- Summer
- Schedule
- Summer course; August 11 - 22, 2014 + exam (one week).
- Course capacity
- 40
- Continuing and further education
- Study board
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Mathematical Sciences
Course responsibles
- Rolf Poulsen (rolf@math.ku.dk)
Lecturers
Kourosh Marjani Rasmussen, DTU, mail: kmra@dtu.dk