Dr Arne Lokka

This course is compulsory on the MSc in Financial Mathematics. This course is available on the MSc in Financial Statistics, MSc in Financial Statistics (Research) and MSc in Quantitative Methods for Risk Management. This course is not available as an outside option to students on other programmes. This course uses controlled access as part of the course selection process. For information on controlled access courses, including eligibility, application processes, deadlines, and departmental contact details, please refer to the Controlled Access Courses webpage.

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 2 October 2026, 5pm.

For queries contact: Maths.info@lse.ac.uk

The only programmes to which this course is available as an optional course are MSc in Quantitative Methods for Risk Management, MSc in Statistics, MSc in Statistics (Research). MSc in Financial Statistics, MSc in Financial Statistics (Research).  

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.

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.

10 hours of seminars and 20 hours of lectures in the Autumn Term.

Problem sets.

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; 

Exam (80%), duration: 90 Minutes in the Spring exam period.

Project (20%) in December.