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Computational Finance (AAM)
Provider: Faculty of Science

Activity no.: 5559-21-07-31 
Enrollment deadline: 06/09/2021
PlaceDepartment of Mathematical Sciences
Universitetsparken 5, 2100 København Ø
Date and time06.09.2021, at: 08:00 - 12.11.2021, at: 16:00
Regular seats50
ECTS credits7.50
Contact personNina Weisse    E-mail address: weisse@math.ku.dk
Enrolment Handling/Course OrganiserDavid Glavind Skovmand    E-mail address: skovmand@math.ku.dk
Written languageEnglish
Teaching languageEnglish
Semester/BlockBlock 1
Scheme groupA (Tues 8-12 + Thurs 8-17)
Exam requirementsThe student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course
Exam formContinuous assessment
Exam details2 hand-ins over the course of the course
Exam aidsAll aids allowed
Grading scale7 point grading scale. For PhD students: Passed / Not Passed
Exam re-examination20 minute oral exam without preparation
Course workload
Course workload categoryHours
Theory exercises18.00
Project work76.00


See "Knowledge" below.

Learning outcome
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 computaional 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 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. 

Notes, articles and working papers. See Absalon for a list of course literature.

Teaching and learning methods
4 hours of lectures and and 2 hours of exercises per week for 9 weeks.


PhD Programme in Actuarial Mathematics
PhD Programme in Mathematics-Economics

Academic qualifications:

A bachelor degree from the Departments of Mathematical Sciences (or something suitably close to that; computer science, polit, engineering, ...) plus (at least) working knowledge of continuous-time finance.

As an exchange, guest and credit student - please see: http://www.science.ku.dk/english/courses-and-programmes/

Continuing Education - please see: http://www.science.ku.dk/english/courses-and-programmes/continuing-education/bsc-msc-courses/

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