Mr Georgios Zouros

This course is compulsory on the BSc in Actuarial Science. This course is available on the BSc in Data Science and BSc in Mathematics, Statistics and Business. This course is available as an outside option to students on other programmes where regulations permit and to General Course students.

Students must have completed Mathematical Methods (MA100) and Elementary Statistical Theory (ST102).

“Students must have completed one of the following two combinations of courses: (a) ST102 and MA100, or (b) MA107 and ST109 and EC1C1. Equivalent combinations may be accepted at the lecturer’s discretion.”

An introduction to stochastic processes with emphasis on life history analysis and actuarial applications. Principles of modelling; model selection, calibration, and testing; Stochastic processes and their classification into different types by time space, state space, and distributional properties; construction of stochastic processes from finite-dimensional distributions, processes with independent increments, Poisson processes and renewal processes and their applications in general insurance and risk theory, Markov processes, Markov chains and their applications in life insurance and general insurance, extensions to more general intensity-driven processes, counting processes, semi-Markov processes, stationary distributions. Determining transition probabilities and other conditional probabilities and expected values; Integral expressions, Kolmogorov differential equations, numerical solutions, simulation techniques. Survival models - the random life length approach and the Markov chain approach; survival function, conditional survival function, mortality intensity, some commonly used mortality laws. Statistical inference for life history data; Maximum likelihood estimation for parametric models, non-parametric methods (Kaplan-Meier and Nelson-Aalen), regression models for intensities including the semi-parametric Cox model and partial likelihood estimation; Various forms of censoring; The technique of occurrence-exposure rates and analytic graduation; Impact of the censoring scheme on the distribution of the estimators; Confidence regions and hypothesis testing.

This course will be delivered through a combination of classes and lectures totalling a minimum of 30 hours across the Winter/Spring Terms, some of this teaching may be delivered as short online videos. This course includes a reading week in Week 6 of Winter Term.

Compulsory written answers to two sets of problems.

S Ross, Stochastic Processes; R Norberg, Risk and Stochastics in Life Insurance; The Institute of Actuaries, CS2: Risk Modelling and Survival Analysis. For full details of the syllabus of CT4, see https://www.actuaries.org.uk/curriculum_entity/curriculum_entity/8.

Exam (90%, duration: 3 hours) in the spring exam period.
Coursework (10%) in the ST.