Not available in 2023/24
ST433      Half Unit
Computational Methods in Finance and Insurance

This information is for the 2023/24 session.

Teacher responsible

Dr Yufei Zhang

Availability

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

Pre-requisites

Students must have completed September Introductory Course (Financial Mathematics and Quantitative Methods for Risk Management) (MA400).

Any students who are taking ST433 as an optional course and who have not completed MA400 need to obtain permission from the lecturer by providing a statement explaining why and how they know the material covered in MA400.

Course content

The purpose of this course is to (a) develop the students' computational skills, (b) introduce a range of numerical techniques of importance in actuarial and financial engineering, and (c) develop the ability of the students to apply the theory from the taught courses to practical problems, work out solutions including numerical work, and to present the results in a written report.

Binomial and trinomial trees. Random number generation, the fundamentals of Monte Carlo simulation and a number of related issues. Finite difference schemes for the solution of ordinary and partial differential equations arising in insurance and finance. Numerical solutions to stochastic differential equations and their implementation. The course ends with an introduction to guidelines for writing a scholarly report/thesis.

Teaching

This course will be delivered through a combination of classes, lectures and Q&A sessions totalling a minimum of 32 hours across Lent Term.

Formative coursework

Weekly exercises and practicals are set and form the basis of the classes.

Indicative reading

N E Steenrod, P Halmos, M M Schiffer & J A Dieudonne, How to write mathematics (1973); D.J. Duffy, Finite Difference Methods in Financial Engineering: A Partial Differential Equation Approach, Wiley; P. Glasserman, MonteCarlo Methods in Financial Engineering, Springer; P.E. Kloden and E. Platen, Numerical Solution of Stochastic Differential Equations, Springer. Further material will be specified during the course.

Assessment

Project (100%) in the ST.

Student performance results

(2019/20 - 2021/22 combined)

Classification % of students
Distinction 62
Merit 18
Pass 16
Fail 4

Key facts

Department: Statistics

Total students 2022/23: 42

Average class size 2022/23: 42

Controlled access 2022/23: Yes

Lecture capture used 2022/23: Yes (LT)

Value: Half Unit

Guidelines for interpreting course guide information

Course selection videos

Some departments have produced short videos to introduce their courses. Please refer to the course selection videos index page for further information.

Personal development skills

  • Team working
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Commercial awareness
  • Specialist skills