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BSc Actuarial Science and Mathematics / Course details
Year of entry: 2021
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Course unit details:
|Unit level||Level 2|
|Teaching period(s)||Semester 2|
|Offered by||Department of Mathematics|
|Available as a free choice unit?||No|
This course unit provides a basic knowledge of some of the major notions and models of probability and statistics which are particularly relevant to non-life insurance. The course covers part of Subject CT6, one of the core technical modules from the educational program of the Actuarial Profession.
|Unit title||Unit code||Requirement type||Description|
|Financial Mathematics for Actuarial Science 1||MATH10951||Pre-Requisite||Compulsory|
For students on the Actuarial Science and Mathematics programme only.
The aim of this unit is to provide to students a further grounding in several stochastic and statistical techniques of particular relevance to the non-life insurance industry.
On completion of this unit, successful students will be able to:
- Analyse games and solve decision-making problems using game and decision theory.
- Model situations of the type arising in the insurance industry using probabilistic tools.
- Evaluate aspects of probabilistic models relevant for financial risk, and discuss the consequences in terms of risk and decision-making.
- Select and use approximation methods in probabilistic models, and describe their limitations.
- Compute reserves in an insurance context.
- Generate, describe and analyse simulation algorithms for random variables.
1.Decision Theory. Two person zero sum games, randomised strategies, saddle points, statistical games (with data), Bayes criterion, minimax criterion.
2.Loss Distributions. Properties of loss distributions, actuarial interpretation, effect of different types of reinsurance.
3.Run-off triangles. Several methods for computing required reserves in the context of run-off triangles.
4.Risk models. Aggregated claim amounts modeled by compound distributions in elementary and more advanced form, results about their moment generating functions/moments etc., several standard compound distributions, effect of different types of reinsurance.
5.Monte Carlo methods. The basics of the Monte Carlo simulation method: simulation using the cdf and acceptance-rejection, variance reduction techniques etc.
2.Examination at the end of the semester, 80%
Feedback tutorials will provide an opportunity for students' work to be discussed and provide feedback on their understanding. Coursework or in-class tests (where applicable) also provide an opportunity for students to receive feedback. Students can also get feedback on their understanding directly from the lecturer, for example during the lecturer's office hour.
- Core Reading: Subject CT6, Statistical Methods. Produced by the Actuarial Education Company (www.acted.co.uk).
- Loss models: from data to decisions (2008), third edition. Stuart A. Klugman, Harry H. Panjer and Gordon E. Willmot.
- Monte Carlo Methods in Financial Engineering (2004). Paul Glasserman.
- Non-life Insurance Mathematics. An Introduction with Stochastic Processes (2004),second edition. Thomas Mikosch.
|Scheduled activity hours|
|Independent study hours|
|Kees Van Schaik||Unit coordinator|
This course unit detail provides the framework for delivery in 20/21 and may be subject to change due to any additional Covid-19 impact.
Please see Blackboard / course unit related emails for any further updates