ST440      Half Unit
Recent Developments in Finance and Insurance

This information is for the 2019/20 session.

Teacher responsible

Dr Beatrice Acciaio COL 6.02 and Dr George Tzougas COL 5.11


This course is available on the MSc in Financial Mathematics, MSc in Quantitative Methods for Risk Management, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (LSE and Fudan) and MSc in Statistics (Financial Statistics) (Research). This course is available with permission as an outside option to students on other programmes where regulations permit.


Students must have completed Stochastic Processes (ST409).

Course content

Recent developments in the theory of stochastic processes and applications in finance and insurance and their interface. A variety of topics will be chosen, from robust evaluation; optimal hedging; evaluation via utility criteria; optimal risk sharing; minimal capital requirement according to the Basel Accords and the Solvency Directives; life and non-life insurance. The programming language R will be utilized for estimating advanced regression models for the number and the cost of claims in real insurance data, for a priori and a posteriori ratemaking, and for pricing reinsurance contracts.


20 hours of lectures and 10 hours of seminars in the MT.

Week 8 will be devoted to students' presentations, using material which will have been provided in week 1 or 2; as well as to discuss in groups solutions to problems that will have been set in class.

Week 6 will be used as a reading week.

Formative coursework

A set of coursework similar to the exercises that will appear in the exam will be assigned as well as a mock exam.

Indicative reading

H. Foellmer and A. Schied: Stochastic finance. An introduction in discrete time. (3rd ed.), de Gruyter.

Selected papers from scientific journals.


Exam (90%, duration: 2 hours) in the January exam period.
Presentation (10%) in the MT Week 9.

Student performance results

(2015/16 - 2017/18 combined)

Classification % of students
Distinction 28.4
Merit 24.5
Pass 27.5
Fail 19.6

Key facts

Department: Statistics

Total students 2018/19: 35

Average class size 2018/19: 35

Controlled access 2018/19: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Team working
  • Problem solving
  • Application of information skills
  • Communication
  • Specialist skills