MSc - Master of Science
Royal Holloway, University of London
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
Teaching & assessment
Teaching is organised in terms of 11 weeks each. Examinations are taken in April/May of each academic year, except for Data Analysis for which the exam is in January. The individual project is taken over 12 weeks during the Summer.
A weekly seminar series runs in parallel with the academic programme, which includes talks by professionals in a variety of application areas as well as workshops that will train you to find a placement or a job and lead a successful career.
Assessment is carried out by a variety of methods including coursework, small group projects, and examinations, the proportions of which vary according to the nature of the modules.
Your future career
Demand for computational finance analysts is buoyant, in the UK and worldwide, with salaries much higher than other IT professions and at least double the UK average full-time wage. Study Computational Finance at Royal Holloway, University of London and you'll graduate with excellent employability prospects in a range of fields.
Our proximity to the M4 corridor also known as 'England’s Silicon Valley' - provides excellent networking opportunities with some of the country’s top technology institutions. 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.
Our graduates enter into successful careers in academia or in companies or organisations operating in highly competitive areas.
In addition to the support provided by The Careers and Employability Service, the department has a dedicated administrator and an academic who coordinates and oversees placements and job opportunities.
- Strong industry ties help to provide placement and networking opportunities with some of the country’s leading institutions.
- Together with our on-site Careers and Employability Service, we run one-to-one coaching sessions and workshops, helping you to find a placement or job and lead a successful career.
- United States
- Antigua & Barbuda
- Bosnia and Herzegovina
- Burkina Faso
- Cabo Verde
- Central African Republic
- Congo (Democratic Republic)
- Costa Rica
- Czech Republic
- Dominican Republic
- East Timor
- El Salvador
- Equatorial Guinea
- Hong Kong
- Ivory Coast
- Korea DPR (North Korea)
- Marshall Islands
- New Zealand
- Northern Ireland
- Palestinian Authority
- Papua New Guinea
- Puerto Rico
- Republic of Ireland
- San Marino
- Sao Tome and Principe
- Saudi Arabia
- Sierra Leone
- Solomon Islands
- South Africa
- South Korea
- South Sudan
- Sri Lanka
- St Vincent
- St. Kitts & Nevis
- St. Lucia
- Trinidad & Tobago
- United Kingdom
- Vatican City
- Western Samoa
£ 21,000per year
Tuition fees shown are for indicative purposes and may vary. Please check with the institution for most up to date details.
University League Table
Royal Holloway, University of London, Egham, Surrey, TW20 0EX, England
40th out of 103 5
28th out of 110 5
50th out of 72 3
Entry standards/ Max 220126 57%
Graduate prospects/ Max 100n/a
Student satisfaction/ Max 53.90 78%
Entry standards/ Max 236137 57%
Graduate prospects/ Max 10093 93%
Student satisfaction/ Max 54.07 81%
Entry standards/ Max 236133 56%
Graduate prospects/ Max 10069 69%
Student satisfaction/ Max 53.88 78%