MSc in Mathematical and Computational Finance

MSc in Mathematical and Computational Finance - Information for Current Students

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 students 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 into a financial or other institution

Alumni Profiles

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.

Course Components

The MSc starts two weeks before Michaelmas term with four introductory courses. The first term is devoted to the Core courses. Students attend two of the three Advanced streams (Tools, Modelling and Data-driven stream) in Hilary term and an intensive short course on Quantitative Risk Management.
The Dissertation project spreads over Trinity term. C++ programming is taught in two parts.

Information for Applicants

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.

Frequently Asked Questions

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