Stochastic Processes in Life Insurance (LivStok)

Course content

  • Counting processes
  • Markov processes
  • Semi-Markov processes
  • Martingale methods in life insurance
  • Inference for models of counting processes
Education

MSc Programme in Actuarial Mathematics
MSc Programme in Mathematics-Economy

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.

5 hours of lectures per week for 7 weeks.

Lecture notes

Bacproj-akt. Vidsand1 no later than at the same time. Otherwise similar prerequisites.

ECTS
7,5 ECTS
Type of assessment
Oral examination, 30min
30-minute oral exam without time for preparation.
Aid

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)

  • Category
  • Hours
  • Lectures
  • 35
  • Preparation
  • 170
  • Exam
  • 1
  • English
  • 206