MSc Mathematical Finance
Challenge yourself on our MSc Mathematical Finance with a high-level mix of mathematic and finance disciplines taught by three of the University’s top departments: Statistics, Mathematics and Warwick Business School.
This mathematically rigorous course is unique in providing training from three top departments at Warwick. It enables you to develop and apply the quantitative skills in machine learning, computational statistics and mathematical finance used in the financial markets and the finance industry.
Build on your strong mathematical background to gain both a deep theoretical and conceptual knowledge of finance, together with the requisite high-level probability, statistics and mathematics, to enable you to undertake advanced quantitative modelling. Lab work will give you hands-on experience of using software packages for simulations and time series analysis, as well as learning programming for quantitative finance in three core languages: Python, C++ and R.
Our departments benefit from excellent links to key financial institutions and employers, and this course has benefited from industry recommendations.
Please note that this course was previously named MSc Financial Mathematics.
Seven compulsory modules cover the four key pillars of the core skill set needed for a career in the finance industry: Financial Statistics, Financial Mathematics, Asset Pricing and Risk, and Simulation and Machine Learning for Finance. Alongside this, you'll learn programming for Quantitative Finance, focusing on C++, Python, and R.
Our optional modules enable you to personalise the course to your own interests, allowing you to focus on your future career path in finance. Please note that availability and delivery modes may vary.
Modules are taught by staff from WBS, Warwick's Department of Statistics, and the Mathematics Institute through a combination of lectures, classes, and computer lab sessions. A one-week induction module will ensure you have the mathematical and statistical prerequisites for the course. Assessment is a mix of exams and coursework with your dissertation bringing all your learning together at the end.
Lectures & classes
Lectures introduce key theories, concepts, and economic models. You will solve financial problems and numerical exercises, analyse case studies, and make presentations of research published in academic journals.
Lab work will give you hands-on experience of using software to perform finance-related calculations, conduct realistic simulations and write code.
Learn from the practitioners
Guest lectures by practitioners from the quantitative finance industry will give an applied context to your course, showcasing how the course prepares you for a variety of graduate destinations, and giving valuable networking opportunities.
External companies also provide a selection of dissertation projects for our students, giving the opportunity for you to apply your knowledge in a real corporate setting.
You will have access to our outstanding learning facilities, including a Postgraduate-only Learning Space and IT suite, as well as all other University facilities. Studying on a Finance-based MSc also means that you gain access to our Bloomberg terminals, Eikon terminals, and financial data via the Wharton Research Data Services.
A 10,000 word dissertation gives you the opportunity to test and apply techniques and theories you have been learning and to complete an original piece of research. You will be supervised and supported by one of our academic staff.
Our MSc Mathematical Finance is a highly specialised and technical programme, and is, as such, mathematically quite challenging. To succeed on this course, you will need strong ability in Mathematics and Finance, and some experience in Statistics or Econometrics, evidenced by a good 2:1 or first in Mathematics, Statistics, Physics or another relevant quantitatively-focused undergraduate degree. A clear emphasis in your choice of undergraduate electives on the aforementioned areas will strengthen your application.
While you will, throughout the course, develop all necessary advanced skills, confident foundations in mathematics (in particular sound knowledge of Probability Theory, Linear Algebra and Differential Calculus) are necessary to build on.
Given the fast pace of the course, it is strongly recommended that you undertake preliminary reading before the start of the course if you have little or no background in areas such as Measure-Theoretic Probability, Statistics, and Financial Economics. Before you join the course, we will make reading recommendations and other materials available via our dedicated pre-arrival pages.
GMAT & GRE
We do not require a GMAT or GRE score but a well-balanced score (700+) may strengthen your application.