NSCPHD1082 Computational Finance (AAM)
PhD Programme in Actuarial Mathematics
PhD Programme in Mathematics-Economics
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See "Knowledge" below.
Knowledge (= a rough lecture plan)
- Rudimentary low-level programming.
- Data and computational resources at Copenhagen University and beyond.
- Monte Carlo simulation techniques in option pricing: Variance reduction, diffusion (and possibly Levy) process simulation, American options, adjoint techniques.
- Numerical transform methods for option pricing.
- Numerical optimization and model calibration.
- Numerical methods for solving parabolic partial differential equations.
Only a selection (based on lecturer and student interest) of the last three topics will be covered.
High- and low-level programming as fits the problem.
Extracting and handling financial data.
Effcient use computational resources, both wrt. hardware (distributed computing) and software (error order analysis).
Ability to implement Monte Carlo simulation techniques (to investigate pricing and hedging) for a large range of financial products and models.
Ability to implement a (limited) number of more specialized methods for more specific models and problems.
Proficieny in classical and modern numerical methods for quantitative finance problems. This is a question of having both a sizeable "toolbox" and the ability pick the appropriate one in a given situation.
Notes, articles and working papers
- Project work
- Theory exercises
- 7,5 ECTS
- Type of assessment
- Continuous assessment3 hand-ins over the course of the course.
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
20 minute oral exam without preparation.
Criteria for exam assesment
The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.