NMAA05115U Stochastic Processes in Life Insurance (LivStok)
MSc Programme in Actuarial Mathematics
- Finite variation processes
- Markov processes
- Semi-Markov processes
- Martingale methods in life insurance
- Inference for models of counting processes
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.
Academic qualifications equivalent to a BSc degree is recommended.
- Category
- Hours
- Lectures
- 28
- Preparation
- 170
- Theory exercises
- 7
- Exam
- 1
- Total
- 206
Upon active participation in meetings for discussions of the course material.
- Credit
- 7,5 ECTS
- Type of assessment
- Oral examination, 30 minutes (no preparation time)
- 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
Same as the ordinary exam
Criteria for exam assesment
The student should convincingly and accurately demonstrate the knowledge, skills and competences described under Intended learning outcome.
Course information
- Language
- English
- Course code
- NMAA05115U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 1
- Schedule
- C
- Course capacity
- No limitation – unless you register in the late-registration period (BSc and MSc) or as a credit or single subject student.
Study board
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Mathematical Sciences
Contracting faculty
- Faculty of Science
Course Coordinators
- Jesper Lund Pedersen (jesper@math.ku.dk)