MA323 Half Unit
Computational Methods in Financial Mathematics
This information is for the 2019/20 session.
Teacher responsible
Dr Luitgard Veraart COL 4.11
Availability
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.
Pre-requisites
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.
Teaching
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).
Assessment
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
Personal development skills
- Self-management
- Problem solving
- Application of information skills
- Communication
- Application of numeracy skills
- Specialist skills