Computational Finance
Course content
See "Knowledge" below.
MSc Programme in Actuarial Mathematics
MSc Programme in Mathematics-Economics
Knowledge (= a rough lecture plan)
Topics may include but are not limited to:
- High-level programming
- Data and computational resources
- Monte Carlo 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
- Machine learning approaches in quantitative finance
Only a selection (based on lecturer and student interest) of the topics will be covered.
Skills
High- and low-level programming as fits the problem.
Extracting and handling financial data.
Ability to implement numerical techniques (to investigate pricing and hedging) for a range of financial products and models.
Ability to implement a (limited) number of more specialized methods for more specific models and problems.
Competencies
Proficieny 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 on in a given situation.
4 hours of lectures and and 2 hours of exercises per week for 9 weeks.
See Absalon for a list of course literature.
A bachelor degree from the Departments of Mathematical Sciences
(or something suitably close to that; plus (at least) working
knowledge of continuous-time finance, and some experience with
programming.
Academic qualifications equivalent to a BSc degree is
recommended.
Individual feedback given on the basis of assignments.
- ECTS
- 7,5 ECTS
- Type of assessment
-
Continuous assessment
- Type of assessment details
- 2 equally weighted hand-ins over the course of the course.
- Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
One internal examiner.
Criteria for exam assessment
The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.
Single subject courses (day)
- Category
- Hours
- Lectures
- 36
- Preparation
- 76
- Theory exercises
- 18
- Project work
- 76
- English
- 206
Kursusinformation
- Language
- English
- Course number
- NMAK16004U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 block
- Placement
- Block 4
- Schedulegroup
-
A
- Capacity
- No limit
The number of seats may be reduced in the late registration period - Studyboard
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Mathematical Sciences
Contracting faculty
- Faculty of Science
Course Coordinator
- Nils Martin Anders Tegnér (6-78696b726976447165786c326f7932686f)
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Courseinformation of students