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Course options

  • Qualification

    MSc - Master of Science

  • Location

    Royal Holloway, University of London

  • Study mode

    Full time

  • Start date

    19-SEP-22

  • Duration

    1 year

Course summary

The course

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.

Tuition fees

Students living in United States
(international fees)

£ 22,000per year

Tuition fees shown are for indicative purposes and may vary. Please check with the institution for most up to date details.

University information

University image

Royal Holloway, University of London

  • University League Table

    33rd

  • Campus address

    Royal Holloway, University of London, Egham, Surrey, TW20 0EX, England

Learn from top experts: Royal Holloway is in the UK’s top 25 universities for research (Complete University Guide).
International collaborations: successful partnerships and sponsorship from industry and governments, leading to first-class career opportunities.
Close-knit community with specific support for international students as well as financial support through a generous package of scholarships and bursaries.

Subject rankings

  • Subject ranking

    50th out of 70 15

    45th out of 104 8

    26th out of 114 13

  • Entry standards

    / Max 236
    131 54%

    40th

  • Graduate prospects

    / Max 100
    66.0 66%

    59th

    11
  • Student satisfaction

    / Max 5
    3.87 77%

    40th

    18
  • Entry standards

    / Max 220
    111 50%

    66th

    23
  • Graduate prospects

    / Max 100
    56.0 56%

    60th

  • Student satisfaction

    / Max 5
    3.82 76%

    61st

    27
  • Entry standards

    / Max 236
    134 57%

    46th

    3
  • Graduate prospects

    / Max 100
    91.0 91%

    22nd

    8
  • Student satisfaction

    / Max 5
    3.86 77%

    42nd

    11

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