MA417 Half Unit
Computational Methods in Finance
This information is for the 2015/16 session.
Dr Luitgard Veraart and Dr Tugkan Batu
This course is compulsory on the MSc in Financial Mathematics. This course is available with permission as an outside option to students on other programmes where regulations permit.
Students must have completed September Introductory Course (Financial Mathematics) (MA400).
The purpose of this course is to (a) develop the students' computational skills, and (b) introduce a range of numerical techniques of importance to financial engineering. The course starts with the implementation of binomial and trinomial trees. Random number generation, the fundamentals of Monte Carlo simulation and a number of related issues follow. Numerical solutions to stochastic differential equations and their implementation are considered. The course then addresses finite-difference schemes for the solution of partial differential equations arising in finance.
8 hours of lectures and 12 hours of computer workshops in the MT. 20 hours of lectures, 4 hours of seminars and 10 hours of computer workshops in the LT.
Weekly exercises and practicals are set and form the basis of the seminars.
P.Glasserman, Monte Carlo Methods in Financial Engineering, Springer; R.U. Seydel, Tools for Computational Finance, Springer; P.E.Kloeden and E.Platen, Numerical Solution of Stochastic Differential Equations, Springer; D.M. Capper, Introducing C++ for Scientists, Engineers and Mathematicians, Springer. B. Stroustrup, The C++ Programming Language, Addison Wesley; 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;
Exam (50%, duration: 2 hours) in the main exam period.
Project (50%) in the ST.
Total students 2014/15: 24
Average class size 2014/15: 24
Controlled access 2014/15: No
Value: Half Unit
Personal development skills
- Problem solving
- Application of information skills
- Application of numeracy skills
- Specialist skills