Stochastic Processes in Life Insurance (LivStok)
Course content
- Finite variation processes
- Markov processes
- Semi-Markov processes
- Martingale methods in life insurance
- Inference for models of counting processes
MSc Programme in Actuarial Mathematics
MSc Programme in Mathematics-Economics
Knowledge:
Stochastic processs and methods applied in life insurance models.
Skills:
At the end of the course, the students are expected to be able
to
- Apply theorems on stochastic processes of finite variation, including theorems on counting processes,
- Markov chains, integral processes, martingales.
- Analyse Markov chain models and derive Thiele differential equation for reservs using martingale methods.
- Analyse extended models and derive differential equations for reservs.
- Analyse statistical parametric life history models.
- Analyse statistical nonparametric life history models.
Competences:
To make the student operational and to give the student knowledge
in application of stochastic processes in life
insurance.
5 hours of lectures per week for 7 weeks.
VidSand1 no later than at the same time. Otherwise similar
prerequisites.
Academic qualifications equivalent to a BSc degree is
recommended.
There is feedback on the two mandatory assignments.
- ECTS
- 7,5 ECTS
- Type of assessment
-
Oral examination, 30 minutes
- Type of assessment details
- 30-minutes oral exam without time for preparation.
- Exam registration requirements
-
Two mandatory assignments must be approved and valid before the student is allowed attending the exam
- Aid
- Only certain aids allowed
The student may bring notes to the oral exam, but they are only allowed to consult these in the first minute after they have drawn a question. After that, all notes must be put away.
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
- Re-exam
-
As the ordinary exam. If the two mandatory assignments have not been approved during the course the non-approved project(s) must be (re)submitted. The assignments must be 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
Kursusinformation
- Language
- English
- Course number
- NMAA05115U
- ECTS
- 7,5 ECTS
- Programme level
- Full Degree Master
- Duration
-
1 block
- Placement
- Block 1
- Schedulegroup
-
C
- Capacity
- No limit
The number of seats may be reduced in the late registration period - Studyboard
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Mathematical Sciences
Contracting faculty
- Faculty of Science
Course Coordinator
- Jesper Lund Pedersen (6-6d6876736875437064776b316e7831676e)
Er du BA- eller KA-studerende?
Kursusinformation for indskrevne studerende