MA323      Half Unit
Computational Methods in Financial Mathematics

This information is for the 2019/20 session.

Teacher responsible

Dr Luitgard Veraart COL 4.11


This course is compulsory on the BSc in Financial Mathematics and Statistics. This course is not available as an outside option. This course is available with permission to General Course students.


Students must have completed Introduction to Pricing, Hedging and Optimization (ST213) and Programming in C++ (MA332).

Course content

Random number generation; the fundamentals of Monte Carlo (MC) simulation; variance reduction techniques for MC simulation and related issues; numerical solutions to stochastic differential equations by means of MC simulation and their implementation; finite-difference schemes for the solution of partial differential equations arising in finance.


22 hours of lectures, 5 hours of classes and 10 hours of computer workshops in the LT.

Formative coursework

Students will be expected to produce 5 problem sets and 5 other pieces of coursework in the LT.

Indicative reading

P. Glasserman, Monte Carlo Methods in Financial Engineering, Springer;

R.U. Seydel, Tools for Computational Finance, Springer;

D.M. Capper, Introducing C++ for Scientists, Engineers and Mathematicians, Springer.

M. J. Capinski, T.  Zastawniak, Numerical Methods in Finance with C++, Cambridge University Press;

M. S. Joshi, C++ Design Patterns and Derivatives Pricing, Cambridge University Press;

S.M. Ross, Simulation, Academic Press (5th edition).


Exam (75%, duration: 2 hours).
Project (25%) in the ST.

The project will be a computational project. 

Key facts

Department: Mathematics

Total students 2018/19: Unavailable

Average class size 2018/19: Unavailable

Capped 2018/19: No

Value: Half Unit

Guidelines for interpreting course guide information

Personal development skills

  • Self-management
  • Problem solving
  • Application of information skills
  • Communication
  • Application of numeracy skills
  • Specialist skills