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Computational Finance (MSc)

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Course overview

This degree, offered jointly 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. This is an attractive advanced qualification, especially suitable if you are seeking employment in asset structuring, product pricing or risk management, among other fields.

Key facts

Key facts about the course
Qualification Master of Science
Duration 1 year full-time
Department and Faculty Computer Science, Faculty of Science
Partner institution(s) --
Course director Yuri Kalnishkan 
Contact for more information msc-admissions@cs.rhul.ac.uk  

Fees / funding

Please visit the Fees and funding pages for the latest information about tuition fees and the different sources of funding which may be available to you.

How to apply

Applications for entry to all our full-time postgraduate degrees can be made online.

Further information on making an application, including the documentation that you will need to submit with the application is available in the How to apply section of this site.

If you are interested in applying to Royal Holloway, why not arrange a visit to our campus to see for yourself what academic and student life is like here. More information on arranging visits is available on our Open days pages.


Entry requirements

Entry criteria:

UK Upper Second Class Honours degree (2:1) or equivalent in Computer Science, Economics, Mathematics, Physics, or other subjects that include a strong element of both mathematics and computing.

Relevant professional qualifications and relevant experience in an associated area will be considered.

English language requirements:

IELTS 6.5 overall and minimum of 5.5 in each subscore, for equivalencies see here.


Students from overseas should visit the International pages for information on the entry requirements from their country and further information on English language requirements. Royal Holloway offers a Pre-Master’s Diploma for International Students and English language pre-sessional courses, allowing students the opportunity to develop their study skills and English language before starting their postgraduate degree.


Why choose this course?

  • Big Data is now part of every sector and function of the global economy, in particular of financial services and insurance.  Planning and strategic decision-making processes rely on large pools of data that need to be captured, aggregated, stored, and analysed.  
  • You will learn modern quantitative finance and computational methods for financial modeling. People with this set of skills are in short supply and high demand.
  • You will have the opportunity to choose options among an exciting range of topics in Computer Science, Economics, Information Security, Management and Mathematics.
  • Industry connections have informed the content and design of the course. External contacts in both academia and industry enrich the programme of seminars and guest lectures, which are an integral part of the course.
  • Royal Holloway is located in the ‘M4 corridor’, west of London, a major high-technology hub also called ‘England’s Silicon Valley’.
  • Royal Holloway is a very prestigious university in which to study. We are ranked not only as one of the 16 most beautiful universities in the world, but also one of the best:  in 2012/13, the Times Higher Education World University Rankings placed the College 15th in the UK, 45th in Europe and 119th in the world. 

Department research and industry highlights

  • The departments have expertise in a wide set of areas in Computer Science and in Economics, and the topics taught reflect these areas of excellence.
  • Computer Science hosts one of strongest research groups in Machine Learning (the science of systems that learn from data).
  • In the most recent Research Assessment Exercise (RAE 2008), Computer Science ranked 11th and Economics ranked 8th for their research output.
  • Computer Science is ranked third in the UK for graduate employability by the Times Good University Guide 2013.
  • Computer Science has an Industrial Liaison Board that comprises senior representatives from Microsoft, Cognex, CSC, Bank of America Merrill Lynch, Kalido, Bathwick Group, Pentatonix, Blackrock, Oracle, Investec and QubeSoft. 

Course content and structure

You will take taught modules during Term One (October to December) and Term Two (January to March). Examinations are held in May. You then take an industrial placement, after which you come back for your project/dissertation (12 weeks).

Please visit our website for additional information on this degree.

On completion of the course graduates will have:

Throughout your degree, you will have the opportunity to acquire the following skills:

  • Knowledge of the working of financial markets and their role in the context of global economy.
  • Knowledge of modern mathematical and computational techniques used in finance.
  • Knowledge of key ideas, principles, and methods of machine learning and their applications in finance.
  • Ability to apply methods of computational finance to practical problems in computational finance, including pricing of derivatives and risk assessment.
  • Ability to analyse and critically evaluate methods and general principles of computational finance and their applicability to specific problems; to critically evaluate validity and practicality of results.
  • Ability to analyse and critically evaluate applicability of machine learning algorithms to problems in finance.
  • Ability to implement methods of computational finance and machine learning using object-oriented programming languages and modern data management systems.
  • Ability to work with software packages such as MATLAB and R.
  • Knowledge of and ability to work with relational databases (SQL), non-relational databases (mongodb), as well as with Hadoop/pig scripting and other big data manipulation techniques. 
  • Knowledge of and ability to work with Python, Perl, and Shell Scripting.

View the full course specification for Computational Finance (MSc) in the Programme Specification Repository


Assessment is carried out by a variety of methods including coursework and a dissertation. The placement is assessed as part of your degree.

Employability & career opportunities

Our graduates are highly employable and, in recent years, have entered many different finance-related areas, including careers as financial analysts, accountants, bankers, journalists and business analysts. Our graduates are currently working for firms such as Accenture, TNS, RBS, Deloitte, and Baker and McKenzie. At the same time, this course also equips you with a solid foundation for continued PhD studies.

Your careers ambitions are supported by our College Careers Service, located right next door to both departments. They offer application and interview coaching, career strategy discussions, and the opportunity to network with major finance employers on campus. Our careers service is provided by the Careers Group, the main provider of graduate recruitment services in London. Thus, you will have additional access to a wealth of presentations and networking opportunities which make the most of London’s financial centre. 

To find out what Computer Science graduates from Royal Holloway are doing now, please check the Department's website.


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