MA323 Half Unit
Computational Methods in Financial Mathematics
This information is for the 2025/26 session.
Course Convenor
Dr Ofelia Bonesini
Availability
This course is compulsory on the BSc in Financial Mathematics and Statistics. This course is available on the Erasmus Reciprocal Programme of Study and Exchange Programme for Students from University of California, Berkeley. This course is not available as an outside option to students on other programmes. This course is available with permission to General Course students.
Requisites
Pre-requisites:
Students must have completed ST213 before taking this course.
Additional requisites:
Students are also expected to have basic Python programming skills.
Course content
Random number generation; the fundamentals of Monte Carlo (MC) simulation and applications in financial mathematics; variance reduction techniques for MC simulation and related issues; stochastic differential equations and their numerical solutions by means of MC simulation and their implementation.
Teaching
20 hours of lectures and 15 hours of classes in the Winter Term.
Formative assessment
Problem sets
Exercises and other pieces of coursework are assigned weekly 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;
S.M. Ross, Simulation, Academic Press (5th edition).
Assessment
Exam (75%), duration: 120 Minutes in the Spring exam period
Project (25%)
Key facts
Department: Mathematics
Course Study Period: Winter Term
Unit value: Half unit
FHEQ Level: Level 6
CEFR Level: Null
Total students 2024/25: 38
Average class size 2024/25: 38
Capped 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