Stochastic Processes in Non-Life Insurance (SkadeStok)
Stochastic processes in non-life insurance; ruin theory; claims reserving.
MSc Programme in Actuarial Mathematics
MSc Programme in Mathematics-Economics
Knowledge: At the end of the course, the student should
develop a thorough understanding of renewal theory, perturbation
techniques, and martingale techniques as they apply to problems in
risk theory. The student should develop a thorough
understanding of the theory behind the Cramér-Lundberg model in the
subexponential case. Moreover, the student should
develop a basic knowledge of claims reservation (chain ladder
method, Mack's formula, and some related methods).
Skills: The students should develop problem-solving skills for claims reservation and for estimating ruin probabilities in non-life insurance mathematics in various settings, including the cases of classical and subexponential claims and some of their standard generalizations.
Competencies: The student should develop a working knowledge of renewal theory, perturbation arguments, and martingale techniques in connection with the Cramér-Lundberg model and some of its extensions, and develop a working knowledge of claims reservation.
4 hours of lectures and 3 hours of exercises per week for 7 weeks.
VidSand 1 or similar.
Academic qualifications equivalent to a BSc degree is recommended.
- 7,5 ECTS
- Type of assessment
Written examination, 3 hours under invigilation
- Written aids allowed
Written aids allowed, but no electronic aids allowed.
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
One internal examiner
Criteria for exam assessment
Den studerende skal på tilfredsstillende måde godtgøre, at vedkommende lever op til fagets målbeskrivelse.
Single subject courses (day)
- Theory exercises
- Course number
- 7,5 ECTS
- Programme level
- Full Degree Master
- Block 1
- No limit
The number of seats may be reduced in the late registration period
- Study Board of Mathematics and Computer Science
- Department of Mathematical Sciences
- Faculty of Science
- Jeffrey F. Collamore (9-677370706571737669447165786c326f7932686f)
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