Finance 2: Dynamic Portfolio Choice (Fin2)
See the "Knowledge" part of the learning outcome below.
MSc Programme in Mathematics-Economics
- 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.
- 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.
- 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.
4 hours of lectures and 2 hours of tutorials per week for 7 weeks.
A bachelor degree in Mathematics-Economics.
Academic qualifications equivalent to a BSc degree is recommended.
- 7,5 ECTS
- Type of assessment
Oral examination, 20 minutes
- Type of assessment details
- Without preparation time, but "open book" (i.e. "all aids allowed").
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- External censorship
Criteria for exam assessment
The student should convincingly and accurately demonstrate the knowledge, skills and competences described under Intended learning outcome.
Single subject courses (day)
- Theory exercises
- Course number
- 7,5 ECTS
- Programme level
- Full Degree Master
- Block 4
- No limit
The number of seats may be reduced in the late registration period
- Study Board of Mathematics and Computer Science
- Department of Mathematical Sciences
- Faculty of Science
- Rolf Poulsen (4-7b78756f49766a7d7137747e376d74)
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Courseinformation of students