Royal Holloway, University of London

Course Introduction

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.

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, Societe Generale, VMWare and UBS, among others. Our graduates have an excellent track record of finding jobs at the end of (if not during) their studies. We bring several companies to our campus throughout the year, both for fairs and for delivering advanced topics seminars, which are an excellent opportunity to learn about what they do and discuss possible placements or jobs. Together with the Royal Holloway Careers and Employability Service, we offer you workshops and one-to-one coaching that prepare you to find a placement or a job and lead a successful career.

Duration & Attendance Qualification Tuition fees Fee type
2 years
Full Time
MSc £11,300 Home Fees
2 years
Full Time
MSc £20,500 Overseas Fees
2 years
Full Time
MSc £11,300 European Fees
5 years
Part Time
MSc £5,650 Home Fees
5 years
Part Time
MSc £10,250 Overseas Fees
5 years
Part Time
MSc £5,650 European Fees

Qualifications required:

  • Domestic entry requirements: Students need to have 2:1 in 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 entry requirements: Students will 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.