Stochastic Processes in Life Insurance (LivStok)
- 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
Stochastic processs and methods applied in life insurance models.
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.
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
Academic qualifications equivalent to a BSc degree is recommended.
There is feedback on the two mandatory assignments.
- 7,5 ECTS
- Type of assessment
Oral examination, 30 minutes30-minutes oral exam without time for preparation.
- 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
Criteria for exam assessment
The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome.
Single subject courses (day)
- Course number
- 7,5 ECTS
- Programme level
- Full Degree Master
- Block 1
- No limit
- Study Board of Mathematics and Computer Science
- Department of Mathematical Sciences
- Faculty of Science
- Jesper Lund Pedersen (6-6d6876736875437064776b316e7831676e)
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