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Beyond the Classic Markov Chain Life Insurance Setting
Provider: Faculty of Science

Activity no.: 5544-18-07-31 
Enrollment deadline: 19/11/2018
Tilmelding : Beyond the Classic Markov Chain Life Insurance Setting
PlaceDepartment of Mathematical Sciences
Universitetsparken 5, 2100 København Ø
Date and time19.11.2018, at: 09:00 -
27.01.2019, at: 16:00
 
Tilmelding : Beyond the Classic Markov Chain Life Insurance Setting
ECTS credits7.50
PlaceDepartment of Mathematical Sciences
Universitetsparken 5, 2100 København Ø
Date and time19.11.2018, at: 08:00 -
27.01.2019, at: 00:00
Regular seats50
ECTS credits7.50
Contact personNina Weisse    E-mail address: weisse@math.ku.dk
Enrolment Handling/Course OrganiserChristian Furrer    E-mail address: furrer@math.ku.dk
Teaching languageEnglish partially in English
Semester/BlockBlock 2 ¤ Block 3
Scheme groupB
Exam formContinuous assessment
Exam formContinuous assessment
Exam detailsThe exam consists of three individual assignments. Each assignment counts 1/3 towards the total grade. 7-point grading scale. No external censorship.
Course workload
Course workload categoryHours
Exam60.00
Lectures32.00
Exercises16.00
Preparation98.00
Sum206.00
Learning outcome
At the end of the course the student is expected to have:

Knowledge:
Knowledge about parametric modeling and inference beyond the classic (semi-)Markov chain life insurance setting, including the relationship to frailty models in event history and survival analysis and knowledge about likelihoods for random counting measure distributions. Knowledge about credibility theory in life insurance.

Skills:
Skills to implement procedures related to estimation beyond the classic (semi-)Markov chain life insurance setting in R.

Competences:
The course will strengthen the student's competences in navigating inside the classic (semi-)Markov life insurance setting and develop the student's ability to formulate, handle, and interpret hierarchical (credibility) extensions of the setting.

Literature
See Absalon for a list of course literature.

Teaching and learning methods
4 hours of lectures and 2 hours of practical/exercise classes each week for 8 weeks. Active participation is expected.

Content
Parametric modelling and inference for the classic (semi-)Markov chain life insurance setting; credibility in life insurance using hierarchical (random effect, frailty) extensions of classic models; implementation of estimation procedures in R; practical issues related to valuation and pricing.

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