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

Learning outcome

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 prerequisites.

Academic qualifications equivalent to a BSc degree is recommended.

Continuous feedback during the course of the semester

There is feedback on the two mandatory assignments.

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

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

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


Course number
7,5 ECTS
Programme level
Full Degree Master

1 block

Block 1
No limit
The number of seats may be reduced in the late registration period
Study Board of Mathematics and Computer Science
Contracting department
  • Department of Mathematical Sciences
Contracting faculty
  • Faculty of Science
Course Coordinator
  • Jesper Lund Pedersen   (6-6c6775726774426f63766a306d7730666d)
Phone: +45 35 32 07 75, office: 04.3.11
Saved on the 28-02-2023

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