Postgraduate Studentships - Search for funding opportunities.
Postgraduate Studentships - Search for funding opportunities.
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 computational finance and their applicability to specific problems
work with methods and techniques such as clustering, regression, support vector machines, boosting, decision trees, and neural networks
analyse and critically evaluate applicability of machine learning algorithms to problems in finance
implement methods of computational finance and machine learning using object-oriented programming languages and modern data management systems
work with software packages such as MATLAB and R
work with Relational Database Systems and SQL
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.
Benefit from strong industry ties, with close proximity to ‘England’s Silicon Valley’.
Graduate with a Master’s degree with excellent graduate employability prospects.
Tailor your learning with a wide range of engaging optional modules.
Choose from a one-year programme structure or add an optional year in industry.
From time to time, we make changes to our courses to improve the student and learning experience, and this is particularly the case as we continue to respond to the Covid-19 pandemic. If we make a significant change to your chosen course, we’ll let you know as soon as we can.
2:1
Computer Science, Economics, Mathematics, Physics, or another subject that includes a strong element of both mathematics and computing.
Normally we require a UK 2:1 (Honours) or equivalent in relevant subjects but we will consider high 2:2 or relevant work experience. Candidates with professional qualifications in an associated area may be considered. Where a ‘good 2:2’ is considered, we would normally define this as reflecting a profile of 57% or above.
International & EU requirements
English language requirements
All teaching at Royal Holloway is in English. You will therefore need to have good enough written and spoken English to cope with your studies right from the start.
The scores we require
IELTS: 6.5 overall. No subscore lower than 5.5.
Pearson Test of English: 61 overall. Writing 54. No subscore lower than 51.
Trinity College London Integrated Skills in English (ISE): ISE III.
Country-specific requirements
For more information about country-specific entry requirements for your country please see here.
For fees and funding options, please visit website to find out more
Royal Holloway, University of London, is one of the UK’s leading research-intensive universities, home to some of the world’s foremost authorities in ...
