NSCPHD1016 Quantitative Risk Management (QRM)
MSc programme in Acturial Mathematics
MSc programme in Mathematics-Economics
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Risk measures; extreme value theory; multivariate distributions and dependence; copulas; credit modeling and operational risk modeling.
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.
- Practical exercises
- Theory exercises
Please register at: email@example.com
- 7,5 ECTS
- Type of assessment
- Oral examination, 30 min.No preparation time.
- Exam registration requirements
To participate in the exam, the two required homework sets must be passed.
- 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 handed in no later than two weeks before the beginning of the re-exam week. They must be approved before the re-exam.
Criteria for exam assesment
The student must, in a satisfactory way, demonstrate that he/she has mastered the learning outcome.