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

Knowledge:  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.

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

Competencies:  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.

5 hours of lectures per week for 7 weeks.

VidSand2 concurrently, or equivalent.

Academic qualifications equivalent to a BSc degree is recommended.

Feedback by final exam (In addition to the grade)
7,5 ECTS
Type of assessment
Oral examination, 30 minutes
Type of assessment details
No preparation time.
Exam registration requirements

To participate in the exam, the two required homework sets must be approved.

Without aids
Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners.

Same as the ordinary exam. If the required homework sets are not approved before the ordinary exam, the non-approved set(s) must be (re)submitted and approved no later than three 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
  • 35
  • Preparation
  • 170
  • Exam
  • 1
  • English
  • 206


Course number
7,5 ECTS
Programme level
Full Degree Master

1 block

Block 2
No limit
The number of seats may be reduced in the late registration period
Study Board of Mathematics and Computer Science
Contracting department
  • Department of Mathematical Sciences
Contracting faculty
  • Faculty of Science
Course Coordinator
  • Jeffrey F. Collamore   (9-65716e6e636f717467426f63766a306d7730666d)
Phone +45 35 32 07 82, office: 04.3.08
Saved on the 28-02-2023

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