NMAA05115U  Stochastic Processes in Life Insurance (LivStok)

Volume 2017/2018
Education

MSc Programme in Actuarial Mathematics
MSc Programme in Mathematics-Economy

Content
  • Finite variation 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 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.

Bacproj-akt. Vidsand1 no later than at the same time. Otherwise similar prerequisites.
5 hours of lectures per week for 7 weeks.
Credit
7,5 ECTS
Type of assessment
Oral examination, 30 minutes
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

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

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 the re-exam.

Criteria for exam assesment

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

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