Students develop an advanced knowledge of computational methods in finance, which is a prerequisite for a successful career in the financial industry within 'quant' teams. 'Quants' (development analysts) design and implement complex models and are sought after by banks, fund managers, insurance companies, hedge funds, and financial software and data providers.
Modes and duration
Tuition fees (2019/20)
Note on fees: The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website.
Fee deposit: All full time students are required to pay a fee deposit of £2,000 for this programme. All part-time students are required to pay a fee deposit of £1,000.
An upper-second class UK Bachelor's degree (or equivalent overseas qualification) in computer science, mathematics, statistics, physics, engineering or a similarly quantitative subject. Programming experience is an advantage but is not mandatory. Relevant work experience is also taken into account.
English language requirements
If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.
The English language level for this programme is: Good
Further information can be found on our English language requirements page.
Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.
International applicants can find out the equivalent qualification for their country by selecting from the list below.
Select your country:
About this degree
This degree comprises advanced modules on quantitative and modelling skills, which are essential for 'quant' roles in trading research, regulation and risk. This applied MSc programme is distinctive in that it provides a solid mathematical and statistical foundation together with an education in advanced-level programming.
Students undertake modules to the value of 180 credits.
The programme consists of four core modules (60 credits), four optional modules (60 credits) and a dissertation (60 credits).
- Financial Data and Statistics (15 credits)
- Financial Engineering (15 credits)
- Financial Market Modelling and Analysis (15 credits)
- Numerical Methods for Finance (15 credits)
Students select 60 credits from the optional group.
- Algorithmic Trading (15 credits)
- Applied Computational Finance (15 credits)
- Database and Information Management Systems (15 credits)
- Financial Institutions and Markets (15 credits)
- Machine Learning with Applications in Finance (15 credits)
- Market Microstructure (15 credits)
- Market Risk Measures and Portfolio Theory (15 credits)
- Networks and Systemic Risk (15 credits)
- Numerical Optimisation (15 credits)
- Operational Risk Measurement for Financial Institutions (15 credits)
- Probability Theory and Stochastic Processes (15 credits)
Please note: the availability and delivery of optional modules may vary, depending on your selection.
All students undertake an independent research project which culminates in a dissertation of about 10,000 words or 50 pages. Usually this will be undertaken during a summer placement in an industry environment arranged by the department.
Teaching and learning
The programme is delivered through a combination of lectures, tutorials, seminars, and project work. It comprises two terms of teaching, followed by examinations and a dissertation. Assessment is through coursework, unseen examinations and a dissertation.
Four MSc Scholarships, worth £4000 each, are made available by the Department of Computer Science to UK/EU offer holders with a record of excellent academic achievement. The closing date is 30 June 2019. For more information, please see the department pages.
Scholarships relevant to this department are displayed below.
- Now closed for 2019/20
- £15,000 (1 year)
- Based on both academic merit and financial need
- £25,000 (Duration of programme)
- UK, EU
- Based on both academic merit and financial need
- Deadline: 30 June 2019
- £4,000 (1 year)
- UK, EU
- Based on academic merit
For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.
This is a relatively new programme and therefore no specific information on graduate destinations is currently available. UCL Computer Science graduates typically find work in financial institutions such as Credit Suisse, JP Morgan, Morgan Stanley, and Deutsche Bank as financial analyst application developers, quant developers, and business managers. The University of Cambridge and UCL are among top further study destinations.
Our graduates are particularly valued as a result of the department's international reputation, strong links with industry, and ideal location close to the City of London. Graduates are especially sought after by leading finance companies and organisations.
Why study this degree at UCL?
UCL received the highest percentage (96%) for quality of research in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF2014).
UCL Computer Science hosts the Doctoral Training Centre in Financial Computing and Analytics, which is the only one of its kind in the UK.
UCL's central London location ideally places it close to one of the world's most important financial centres, with which UCL pioneers industrial/academic engagements. Students on the Computational Finance MSc will benefit from teaching input from City of London practitioners.
Department: Computer Science
Application and next steps
Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.
There is an application processing fee for this programme of £75 for online applications and £100 for paper applications. Further information can be found at: www.ucl.ac.uk/prospective-students/graduate/taught/application.
Who can apply?
The programme is suitable for those with a first degree in a quantitative subject wishing to develop a successful career in the financial industry.
- All applicants
- 14 June 2019
Applications close on 14 June 2019, 17:00. Due to competition for places on this programme, no late applications will be considered. Students with visa requirements or applying for scholarships are advised to apply early.
For more information see our Applications page.Apply now
What are we looking for?
When we assess your application we would like to learn:
- why you want to study Computational Finance at graduate level?
- why you want to study Computational Finance at UCL?
- what particularly attracts you to the chosen programme
- how do your academic and professional background and skills meet the demands of this challenging programme?
- where would you like to go professionally with your degree?
Together with essential academic requirements, the personal statement is your opportunity to illustrate whether your reasons for applying to this programme match what the programme will deliver.