MA417 Half Unit
Computational Methods in Finance
This information is for the 2022/23 session.
Teacher responsible
Prof Luitgard Veraart
Availability
This course is compulsory on the MSc in Financial Mathematics. This course is not available as an outside option.
Pre-requisites
Students must have completed September Introductory Course (Financial Mathematics and Quantitative Methods for Risk Management) (MA400).
Course content
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 random number generation, the fundamentals of Monte Carlo simulation and a number of related issues. 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.
Teaching
This course is delivered through a combination of seminars and lectures totalling a minimum of 30 hours across Lent Term.
Formative coursework
Weekly exercises and practicals are set and form the basis of the seminars.
Indicative reading
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;
Assessment
Project (100%) in the ST.
Key facts
Department: Mathematics
Total students 2021/22: 31
Average class size 2021/22: 31
Controlled access 2021/22: Yes
Lecture capture used 2021/22: Yes (LT)
Value: Half Unit
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
- Self-management
- Problem solving
- Application of information skills
- Communication
- Application of numeracy skills
- Specialist skills
