This course, offered by the Department of Computer Science and the Department of Economics, allows you to specialise in modern quantitative finance and computational methods for financial modelling, which are demanded for jobs in asset structuring, product pricing as well as risk management.
Skills that you will acquire include the ability to:
analyse, critically evaluate, and apply methods of computational finance to practical problems, including pricing of derivatives and risk assessment
analyse and critically evaluate methods and general principles of comput...
This course, offered by the Department of Computer Science and the Department of Economics, allows you to specialise in modern quantitative finance and computational methods for financial modelling, which are demanded for jobs in asset structuring, product pricing as well as risk management.<br/><br/>Skills that you will acquire include the ability to:<br/><br/>analyse, critically evaluate, and apply methods of computational finance to practical problems, including pricing of derivatives and risk assessment<br/>analyse and critically evaluate methods and general principles of computational finance and their applicability to specific problems<br/>work with methods and techniques such as clustering, regression, support vector machines, boosting, decision trees, and neural networks<br/>analyse and critically evaluate applicability of machine learning algorithms to problems in finance<br/>implement methods of computational finance and machine learning using object-oriented programming languages and modern data management systems<br/>work with software packages such as MATLAB and R<br/>work with Relational Database Systems and SQL<br/>You will be taught by world-leading academics. Research in Machine Learning at Royal Holloway started in the 1990’s, at which time Vladimir Vapnik and Alexey Chervonenkis (the inventors of Support Vector Machines) were both professors here. We have developed both fundamental theory and practical algorithms that have fed into the analytics methods and techniques that are in use today. Current researchers include Alexander Gammerman and Vladimir Vovk – the inventors of conformal predictors theory, a radically new method of estimating the accuracy of each prediction as it is made – and Chris Watkins, originator of reinforcement learning who developed ‘Q-learning’, a work that is fundamental to planning and control.<br/><br/>By electing to spend a year in business you will also be able to integrate theory and practice and gain real business experience. In the past, our students have secured placements in blue-chip companies such as Centrica, Data Reply, Disney, IMS Health, Rolls Royce, Shell, Sociéte Générale, VMWare and UBS, among others.<br/><br/>Benefit from strong industry ties, with close proximity to ‘England’s Silicon Valley’.<br/>Graduate with a Masters degree with excellent graduate employability prospects.<br/>Tailor your learning with a wide range of engaging optional modules.<br/>Refine your skills and knowledge with a year in industry at one of the countrys top institutions.
Some courses vary and have tailored teaching options, select a course option below.
Course Details
Information
Study Mode
Full-time
Duration
2 Years
Start Date
09/2025
Campus
Main Site
Application deadline
Provider Details
Codes/info
Course Code
Unknown
Institution Code
R72
Points of Entry
Unknown
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Region | Costs | Academic Year | Year |
---|---|---|---|
England, Northern Ireland, Scotland, Wales, Channel Islands, Republic of Ireland | £14,400 | 2024/25 | Year 1 |
EU, International | £26,100 | 2024/25 | Year 1 |