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Financial mathematics builds on the application of advanced concepts in modern probability theory to enable market professionals to tackle and systematically resolve a huge range of issues in the areas of pricing, hedging, risk management, and market regulation.
On this course you’ll put theory into practice by developing your numerical and computational skills to implement financial models. These are the skills you’ll need to work for a financial institution.
The course has an emphasis on:
- the modelling of the dynamics of financial assets, both in equity markets and in fixed-income markets
- the pricing and hedging of options and other derivatives
- the quantification and management of financial risk.
The course will give you a balanced mixture of advanced mathematics (including modern probability theory and stochastic calculus), modern finance theory (including models for derivatives, interest rates, foreign exchange, equities, commodities, and credit), and computational technique (GPU-based high-performance computing).
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The programme offers six compulsory modules, taken by all, along with three elective modules from which you choose two modules. There are lectures, examinations and coursework in eight modules altogether, including the six compulsory modules. Additionally, all students complete an individual research project on a selected topic in financial mathematics, leading to the submission of a dissertation.
We aim to teach the key ideas in financial asset pricing theory from a modern perspective, using concepts and methods such as pricing kernels, market information filtrations, and martingale techniques. This replaces the more traditional but old-fashioned approach based on the historical development of the subject. At each stage of the course you’ll undertake a critical re-examination of the hypotheses implicit in any financial model, with a view to gaining a clear grasp of both its strengths and its limitations. You’ll learn high-performance computing and the techniques to implement financial models.
Optional modules are indicative and available subject to numbers.
- Computer Intensive Statistical Methods
- Financial Markets
- Interest Rate Theory
- Option Pricing Theory
- Probability and Stochastics
- Research Methods and Case Studies
- Cryptocurrencies and Blockchain Technology
- Fundamentals of Machine Learning
- Time Series Modelling
This course can be studied 1 year full-time, starting in September.Back to top
UK entry requirements
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- A 2:2 (or above) UK Honours degree, or equivalent internationally recognised qualification, in Mathematics.
Applications from candidates with degrees in Engineering, Economics, Mathematical Biology with Maths, Calculus and Algebra modules with B Grade or above in the modules overall.
Other qualifications with relevant work experience may also be considered.
EU and International entry requirements
If you require a Tier 4 visa to study in the UK, you must prove knowledge of the English language so that we can issue you a Certificate of Acceptance for Study (CAS). To do this, you will need an IELTS for UKVI or Trinity SELT test pass gained from a test centre approved by UK Visas and Immigration (UKVI) and on the Secure English Language Testing (SELT) list. This must have been taken and passed within two years from the date the CAS is made.
English language requirements
- IELTS: 6 (min 5.5 in all areas)
- Pearson: 51 (51 in all sub scores)
- BrunELT: 60% (min 55% in all areas)
- TOEFL: 79 (min R18, L17, S20, W17)
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You can find out more about the qualifications we accept on our English Language Requirements page.
Should you wish to take a pre-sessional English course to improve your English prior to starting your degree course, you must sit the test at an approved SELT provider for the same reason. We offer our own BrunELT English test and have pre-sessional English language courses for students who do not meet requirements or who wish to improve their English. You can find out more information on English courses and test options through our Brunel Language Centre.
Please check our Admissions pages for more information on other factors we use to assess applicants. This information is for guidance only and each application is assessed on a case-by-case basis. Entry requirements are subject to review, and may change.
Teaching and Learning
Mathematics at Brunel has an active and dynamic research centre and many of our lecturers are widely published and highly recognised in their fields. Their work is frequently supported by external grants and contracts with leading industry and government establishments. Lecturers are consequently at the frontier of the subject and in active contact with modern users of mathematics. This means that you can be assured that our academics are teaching you truly up-to-date methods and you’ll benefit from a wide range of expertise across the different areas of mathematics.
The Department of Mathematics, home to its acclaimed research centre CARISMA, has a long tradition of research and software development, in collaboration with various industry partners, in the general area of risk management.
The Department is a member of the London Graduate School in Mathematical Finance, which is a consortium of mathematical finance groups of Birkbeck College, Brunel University London, Imperial College London, King’s College London, London School of Economics, and University College London. There is a strong interaction between the financial mathematics groups of these institutions in the greater London area, from which you can benefit. In particular there are a number of research seminars that take place regularly throughout the year which, as a student at Brunel, you’ll be welcome to attend.
Should you need any non-academic support during your time at Brunel, the Student Support and Welfare Team are here to help.