NMAA09045U Finance 2: Dynamic Portfolio Choice (Fin2)
Volume 2024/2025
Education
MSc Programme in Mathematics-Economics
Content
See the "Knowledge" part of the learning outcome below.
Learning Outcome
Knowledge
- A closer look at arbitrages: No arbitrage-intervals in incomplete markets, cross-currency betting arbitrage, statistical arbitrage.
- Maximization of expected utility and (partial) equilibrium in one-period models, the state-price utility theorem and betting against beta.
- Multi-period optimal portfolio choice. The martingale method vs. dynamic programming/the Bellman equation.
- Explicit solutions in binomial(‘ish) models and in amodel with reurn preditability and transaction costs.
- Properties and consequences of solutions; myopia and constant weights, C-CAPM, the equity premium puzzle.
- The numeraire porttfolio.
- Optimal stopping and the hedging and pricing of American options including Longstaff and Schwartz' simulation technique.
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.
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.
Recommended Academic Qualifications
A bachelor degree in
Mathematics-Economics.
Academic qualifications equivalent to a BSc degree is recommended.
Academic qualifications equivalent to a BSc degree is recommended.
Teaching and learning methods
Blended teaching and
learning: 4 hours of video lectures per week for 7 weeks.
Worksheets with exercises/problem solving will be provided for the
students for in-depth engagement with the course material. There
will be regular meetings with the lecturer for discussions of the
course material and the exam.
Remarks
This course is only
available to students enrolled in the MSc Programme in
Mathematics-Economics in the study year 2023/24 and
earlier.
Workload
- Category
- Hours
- Lectures
- 28
- Preparation
- 177
- Exam
- 1
- Total
- 206
Feedback form
Oral
Collective
Feedback by final exam (In addition to the
grade)
Sign up
Self Service at KUnet
Exam
- Credit
- 7,5 ECTS
- Type of assessment
- Oral examination, 20 minutes (no prepartion)
- Type of assessment details
- Without preparation time, but "open book" (i.e. "all aids allowed").
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
- Re-exam
Same as ordinary
Criteria for exam assesment
The student should convincingly and accurately demonstrate the knowledge, skills and competences described under Intended learning outcome.
Course information
- Language
- English
- Course code
- NMAA09045U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 2
- Schedule
- C
- Course capacity
- No limitation – unless you register in the late-registration period (BSc and MSc) or as a credit or single subject student.
Study board
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Mathematical Sciences
Contracting faculty
- Faculty of Science
Course Coordinators
- Rolf Poulsen (4-83807d77517e7285793f7c863f757c)
Office, 04.4.11
Saved on the
14-02-2024