NMAA05115U Stochastic Processes in Life Insurance (LivStok)

Volume 2015/2016
Education
MSc Programme in Actuarial Mathematics
MSc Programme in Mathematics-Economy
Content
  • Counting processes
  • Markov processes
  • Semi-Markov processes
  • Martingale methods in life insurance
  • Inference for models of counting processes
Learning Outcome

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 bounded 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.

Lecture notes

Bacproj-akt. Vidsand1 no later than at the same time. Otherwise similar preriquisites.
5 hours of lectures per week for 7 weeks.
  • Category
  • Hours
  • Exam
  • 1
  • Lectures
  • 35
  • Preparation
  • 170
  • Total
  • 206
Credit
7,5 ECTS
Type of assessment
Oral examination, 30min
30-minute 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
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 handed in no later than two weeks before the beginning of the re-exam week. The assignments must be aproved before thr re-exam.
Criteria for exam assesment

The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome.