Quantitative Risk Management (QRM)

Course content

  • Risk measures
  • Extreme value theory
  • Multivariate distributions and dependence
  • Copulas
  • Credit modeling and operational risk modeling

MSc Programme in Actuarial Mathematics

MSc Programme in Mathematics-Economics

Learning outcome


By the end of the course, the student should develop an understanding of risk measures, including VaR and expected shortfall, and of stastistical methods from extreme value theory (including the Hill estimator and the POT method).

Also, the student should develop a thorough understanding of the various means for analyzing dependence, including elliptical distributions and copulas.

Moreover, the student should develop a thorough knowledge of some of the standard models used for credit risk modeling and operational risk modeling and a basic knowledge of emerging risks.



The student should develop analytical and computational skills for computing VaR, expected shortfall, and for analyzing dependence and credit risk losses.



The student should be able to analyze risk in a variety financial settings and to compute VaR, expected shortfall, or other related risk measures in these contexts.

The student should also be able to apply basic methods from extreme value theory to analyze these risks.

Moreover, the student should develop proficiency in analyzing dependent risks using, in particular, elliptical distributions or copulas.

Finally, the student should develop a competence in analyzing credit risk losses.

4 hours of lectures and 2 hours exercises per week for 7 weeks.

Mathematical finance or equivalent.

Academic qualifications equivalent to a BSc degree is recommended.

7,5 ECTS
Type of assessment
On-site written exam, 3 hours under invigilation
Exam registration requirements

To participate in the exam, a required homework set must be approved.

Only certain aids allowed

Three A4-pages of handwritten notes.

Marking scale
7-point grading scale
Censorship form
No external censorship

Same as the ordinary exam.

If the required homework set is not approved before the ordinary exam, the non-approved set must be (re)submitted and approved no later than 3 weeks before the beginning of the re-exam week.

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)

  • Category
  • Hours
  • Lectures
  • 28
  • Preparation
  • 161
  • Theory exercises
  • 14
  • Exam
  • 3
  • English
  • 206


Course number
7,5 ECTS
Programme level
Full Degree Master

1 block

Block 3
No limitation – unless you register in the late-registration period (BSc and MSc) or as a credit or single subject student.
Study Board of Mathematics and Computer Science
Contracting department
  • Department of Mathematical Sciences
Contracting faculty
  • Faculty of Science
Course Coordinator
  • Jeffrey F. Collamore   (9-677370706571737669447165786c326f7932686f)
Phone +45 35 32 07 82, office: 04.3.08
Saved on the 14-02-2024

Are you BA- or KA-student?

Are you bachelor- or kandidat-student, then find the course in the course catalog for students:

Courseinformation of students