Scientific word-processing and computing: Students are introduced to, and gain experience of, the main computing utilities currently used in the School and across campus which are relevant to the module. Scientific word-processing will be taught using LaTex. Students will also be introduced to the statistical software R, and refresh their knowledge of statistical methods relevant to actuarial research.
Topics in advanced topical actuarial research: Students will be introduced to areas of actuarial research which are topical and are of interest to the actuarial profession. This may include, but is not limited to, advanced topics on financial risk management, mortality models and adverse selection.
Total contact hours: 26
Private study hours 124
Total study hours: 150
Method of assessment
Porteous, B. and Tapadar, P. (2005). Economic Capital and Financial Risk Management for Financial Services Firms and Conglomerates. Palgrave Macmillan.
Sweeting, P. (2011). Financial Enterprise Risk Management. Cambridge University Press.
Thomas, R.G. (2017) Loss Coverage: Why Insurance Works Better with Some Adverse Selection. Cambridge University Press.
Cairns, A.J.G., Blake, D., Dowd, K., Coughlan, G.D., Epstein, D., Ong, A., and Balevich, I. (2009) A quantitative comparison of stochastic mortality models using data from England and Wales and the United States. North American Actuarial Journal 13(1): 1-35.
See the library reading list for this module (Canterbury)
The intended subject specific learning outcomes. On successfully completing the module students will be able to:
1. produce technical and scientific documentation and present reports on actuarial analysis using LaTex;
2. demonstrate skills in relevant computing utilities and the statistical package R;
3. select suitable techniques to analyse data, evaluate and develop models, and interpret the results appropriately;
4. demonstrate comprehensive knowledge and understanding of topical research areas in actuarial science which are not covered in detail in taught modules;
5. apply a range of mathematical, statistical and actuarial concepts and techniques in a particular topical area of actuarial research;
The intended generic learning outcomes. On successfully completing the module students will be able to:
1. demonstrate self-direction and originality in tackling and solving problems, and act autonomously in planning and implementing analysis of unfamiliar material at a
2. use and develop relevant computing skills at a high level, including use of appropriate document preparation and word-processing packages;
3. demonstrate the ability to communicate conclusions clearly to an appropriate audience;
4. demonstrate a capability for independent research and problem solving skills;
5. demonstrate intellectual independence through the exercise of initiative and personal responsibility, and an ability for independent learning and time management
required for continuing professional development;
6. demonstrate an ability to select material from source texts, either recommended to or found by the student, and show critical awareness of the relationship of the material
to background and to more advanced material.
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Credit level 7. Undergraduate or postgraduate masters level module.
- ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
- The named convenor is the convenor for the current academic session.
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