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.
As part of the course, you will take an industrial placement, where you will gain valuable experience by putting your knowledge and skills into practice.
- 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.
- Taking a placement is an excellent opportunity to gain industrial experience (which gives you an extra edge when applying for jobs in the future) and acquire skills that can only be fully picked up in a work environment.
- 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).
Your placement will take up to one year and, if you are an overseas student, your visa will cover the two years of the programme. The placement attracts a salary and is assessed as part of your degree. You will be assigned a supervisor by the host company, who is responsible for directing your work. You will be assigned an academic supervisor, who visits to check if you are integrating successfully and the type of work being undertaken is appropriate, and supports you in general during your placement. If you cannot or decide not to take a placement, you revert to the normal one-year 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. - Work experience and appreciation of how your work fits into the organizational and development processes of a company.
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.