|Fees||Look up fees|
This subject aims to provide students with a grounding in mathematical and statistical modelling techniques that are of particular relevance to actuarial work, covering survival models concepts, estimation procedures for lifetime distributions, multiple state models, binomial and Poisson models of mortality, actuarial applications of discrete-time and continuous-time Markov chains. This subject focuses on modelling techniques in life insurance.
Intended learning outcomes
On successful completion of this subject, students should be able to:
- Explain the concept of survival model
- Summarise estimation procedures for lifetime distributions
- Analyse discrete-time Markov chains and interpret their actuarial applications
- Analyse continuous-time Markov processes and apply them in actuarial problems
- Construct models of transfer between multiple states, including processes with single or multiple decrements, and derive relationships between probabilities of transfer and transition intensities
- Derive maximum likelihood estimators for the transition intensities in models of transfers between states with piecewise constant transition intensities
- Analyse the binomial model of mortality, derive the maximum likelihood estimator for the probability of death and compare the binomial model with the multiple state models
- Apply prerequisite mathematical and statistical concepts to the solution of problems on the above topics
High level of development: written communication; problem solving; statistical reasoning; application of theory to practice; use of computer software.
Last updated: 5 December 2019