NMAA09045U Finance 2: Dynamic Portfolio Choice (Fin2)
Volume 2014/2015
Education
MSc Programme in
Mathematics-Economics
Content
See the "Knowledge" part of the learning outcome below.
Learning Outcome
Competencies
- Formulate and analyze decision problems (investment/consumption and optimal stopping) in a stochastic multi-period setting.
- Analyze model consequences “with numbers”; algorithmically, experimentally or empirically. (As well as understand why these three things are different concepts.)
- Acquire the confidence to read presentations of the same – or almost the same – problem in the literature. Know that notation, motivation, and rigour varies and that there is rarely a gospel.
Skills
- Rigorously prove optimality principles and conditions for stochastic control problems in (discrete time, finite space)-multi-period setting.
- Explicitly solve simple investment/consumption and optimal stopping problems.
- Derive (with pen and paper), analyze (with a computer) and explain (in plain English) model implications; be they quantitative or qualitative, be they regarding policy, equilibrium, or empirics.
Knowledge
- Maximization of expected utility and (partial and full) equilibrium in one-period models.
- Multi-period optimal portfolio choice. The martingale method vs. dynamic programming/the Bellman equation.
- Explicit solutions with HARA utility and binomial(‘ish) stock dynamics.
- Properties and consequences of solutions; myopia and constant weights, C-CAPM, the equity premium puzzle.
- Optimal stopping and the hedging and pricing of American options.
Academic qualifications
A bachelor degree in
Mathematics-Economics.
Teaching and learning methods
4 hours of lectures and 2
hours of tutorials per week for 7 weeks.
Workload
- Category
- Hours
- Exam
- 1
- Lectures
- 28
- Preparation
- 163
- Theory exercises
- 14
- Total
- 206
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Exam
- Credit
- 7,5 ECTS
- Type of assessment
- Oral examination, 20 min---
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
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
- NMAA09045U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 4
- Schedule
- C (Mon 13-17 + Wednes 8-17)
- Course capacity
- No limit
- Continuing and further education
- Study board
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Mathematical Sciences
Course responsibles
- Rolf Poulsen (4-7774716b457266796d33707a336970)
Phone: +45 35 32 06 85 office,
04.4.11
Saved on the
01-12-2014