MA417 Half Unit
Computational Methods in Finance
This information is for the 2025/26 session.
Course Convenor
Prof Luitgard Veraart
Availability
This course is compulsory on the MSc in Financial Mathematics. This course is available on the MSc in Quantitative Methods for Risk Management, MSc in Statistics (Financial Statistics) and MSc in Statistics (Financial Statistics) (Research). This course is available with permission as an outside option to students on other programmes where regulations permit. This course uses controlled access as part of the course selection process.
All MSc Financial Mathematics students are guaranteed a place. Additional places will be allocated based on a first come first served basis. Students should check that they meet the requisites in the course guide and that their degree programme is included in the availability section of the course guide before applying.
Deadline for application: Apply by Friday 3 October 2025, 5pm.
For queries contact: Maths.info@lse.ac.uk
The only programmes on which this course is available as an optional course are MSc in Statistics, MSc in Statistics (Financial Statistics), MSc in Statistics (Financial Statistics) (LSE and Fudan), MSc in Statistics (Financial Statistics) (Research) and MSc in Statistics (Research).
Requisites
Pre-requisites:
Students must have completed MA400 before taking this course.
Additional requisites:
Any students who are taking MA417 as an optional course and who have not completed MA400 need to obtain permission from the lecturer. They need to provide 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, 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
10 hours of seminars and 20 hours of lectures in the Autumn Term.
Formative assessment
Problem sets
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
Exam (80%), duration: 90 Minutes in the Spring exam period
Project (20%) in December
Key facts
Department: Mathematics
Course Study Period: Autumn Term
Unit value: Half unit
FHEQ Level: Level 7
CEFR Level: Null
Total students 2024/25: 71
Average class size 2024/25: 71
Controlled access 2024/25: NoCourse 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