The programme aims:
- to provide graduates with a strong mathematical background with the necessary to apply their expertise to the solution of real finance problems.
- to provide students with a systematic understanding of core areas in mathematical models, techniques, numerical methods and data analysis in finance as well as source advanced topics in one or more of these areas.
- to develop the skills to formulate problems from a description in financial language; carry out relevant mathematical and/or statistical analysis; develop an appropriate numerical scheme and/or statistics algorithm and present and interpret these results.
- to lay the foundation for further research or for a career as a quantitative analyst
The MSc course provides access to state of the art developments in stochastic analysis, stochastic control, numerical methods, mathematical modelling, partial differential equations, statistics, machine learning and their financial applications.
Please see the MSc Mathematical and Computational Finance webpage at Graduate Admissions for application deadlines
Our graduates have been recruited by prominent companies such as Barclays Capital, BNP Paribas, Citigroup, Credit Suisse, Deutsche Bank, Goldman Sachs, JP Morgan, KCG, Man-Group, Morgan Stanley, Nomura, Royal Bank of Scotland, Société Géneral, Squarepoint Capital, Systematica, UBS.
Many of our past students have progressed to PhD-level studies at leading universities worldwide.