Computational Finance MSc

London, Bloomsbury

The MSc Computational Finance at UCL provides students with advanced knowledge of computational methods in finance, which is a prerequisite for a successful career in the financial industry within 'quant' teams. Quants (quantitative analysts) design and implement complex models and are sought after by banks, fund managers, insurance companies, hedge funds, and financial software and data providers.

UK students International students
Study mode
Full-time
UK tuition fees (2022/23)
£26,600
Overseas tuition fees (2022/23)
£38,000
Duration
1 calendar year
Programme starts
September 2022
Applications accepted
All applicants: 18 Oct 2021 – 31 Mar 2022

Applications closed

Notification

Application closes at 17:00 GMT.

Entry requirements

An upper second-class UK Bachelor's degree (or an international qualification of an equivalent standard) in a relevant discipline with a strong quantitative component evidenced by good performance in mathematics and statistics examinations. Good performance is defined as scores in these subjects not falling below a UK upper second-class or international equivalent level. There is not an exhaustive list of relevant disciplines, but individuals with a background mathematics, statistics, physics, computer science, engineering, economics, and finance are encouraged to apply.

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

UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level. International Preparation Courses

Further information can be found on our English language requirements page.

This programme is suitable for international students on a Student visa – study must be full-time, face-to-face, starting September.

Equivalent qualifications

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. Please note that the equivalency will correspond to the broad UK degree classification stated on this page (e.g. upper second-class). Where a specific overall percentage is required in the UK qualification, the international equivalency will be higher than that stated below. Please contact Graduate Admissions should you require further advice.

About this degree

As a student on the MSc Computational Finance, you will learn advanced quantitative, modelling and programming skills, which are essential for quant roles in trading research, regulation, and risk. This applied taught postgraduate programme is distinctive in that it provides a combination of finance, mathematics, statistics, and computer science.

Who this course is for

Not applicable.

The programme is suitable for those with a first degree in a quantitative subject wishing to develop a successful career in the financial industry.

What this course will give you

UCL has received the highest percentage (96%) for quality of research in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF2014).

Over the years, the three most relevant university rankings (QS, THE, ARWU) have consistently classified UCL among the top 5 universities in Europe and the top 20 universities in the world.

The UCL MSc Computational Finance has been ranked 5th in Europe and 19th in the world by Risk.net's Quant Finance Master's Guide 2020.

We take an experimental approach to our subject, enjoy the challenge and opportunity of entrepreneurial partnerships, and place a high value on our extensive range of industrial collaborations.

UCL Computer Science graduates are highly valued as a result of the department's strong international reputation, extensive links with industry, and ideal location close to the City of London.

The foundation of your career

Alumni from this programme have been employed by some of the world's leading investment banks and financial services, financial technology and accountancy companies, including Bank of America, Bank of England, BNP Paribas, Commerzbank, Credit Suisse, Deloitte, Deutsche Bank, Ernst & Young, Goldman Sachs, JP Morgan, Morgan Stanley, etc., plus a long list of small hedge funds and fintech companies, whilst others have gone on to pursue a PhD.

Employability

The programme is designed to teach a blend of skills in mathematics, statistics, computer science and finance which are highly sought after in the financial industry for a successful career as quantitative analyst (or quant).

Accreditation

Not applicable.

Teaching and learning

You will be assessed through a range of methods across the programme, which will vary depending on any optional or elective module choices. The programme’s core curriculum is typically assessed by methods including coursework, programming tests, individual and group projects, class tests, written exams, oral assessments, and a final research project/ dissertation.

Contact time takes a variety of forms, including lectures, seminars, tutorials, project supervisions, demonstrations, practical classes and workshops, visits, placements, office hours (where staff are available for consultation), email, videoconference, or other media, and situations where feedback on assessed work is given (one-to-one or in a group).

Each module has a credit value that indicates the total notional learning hours a learner will spend on average to achieve its learning outcomes. One credit is typically described as being equal to 10 hours of notional learning, which includes all contact time, self-directed study, and assessment.

Each module has a credit value that indicates the total notional learning hours a learner will spend on average to achieve its learning outcomes. One credit is typically described as being equal to 10 hours of notional learning, which includes all contact time, self-directed study, and assessment.

The contact time for each of your 15 credit taught modules will typically include 22-30 hours of teaching activity (classroom based and/ or online) over the term of its delivery, with the balance then comprised of self-directed learning and working on your assessments. You will have ongoing contact with teaching staff via each module’s online discussion forum, which is typically used for discussing and clarifying concepts or assessment matters, and will have the opportunity to access additional support via regular office hours with module leaders and programme directors.

Your research project/ dissertation module is 60 credits and will include regular contact with your project supervisor(s), who will guide and support you throughout your project. You will dedicate most of your time on this module to carrying out research in connection with your project and writing up your final report.

Modules

The MSc Computational Finance is a one-year programme. 

In term 1, you will be introduced to financial engineering and to numerical methods in finance. You will choose from optional topics which include probability theory and stochastic processes, market risk and portfolio theory, market microstructure, operational risk management, financial institutions and markets, and blockchain technologies.

In term 2, you will study data science and machine learning with applications in finance. You will choose from optional topics that include algorithmic trading, networks and systemic risk, applied computational finance, financial market modelling and analysis, numerical optimisation, and digital finance. You will also begin preparation for your final research project and dissertation.

In term 3, you will focus any examination that take place in the main examination period and undertake your final research project/ dissertation; the project is usually done within a placement organised by UCL at a bank, hedge fund, fintech, or other financial services firm located in London, or sometimes at a regulatory authority.

Not applicable.

Not applicable.

Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability is subject to change.

Students undertake modules to the value of 180 credits. Upon successful completion of 180 credits, you will be awarded an MSc in Computational Finance.

Fieldwork

Not applicable.

Placement

Not applicable.

Accessibility

Details of the accessibility of UCL buildings can be obtained from AccessAble accessable.co.uk. Further information can also be obtained from the UCL Student Support & Wellbeing team.

Online - Open day

Graduate Open Events: UCL Computer Science

Join us for a virtual information and Q&A session with UCL Computer Science. We will have a brief overview from the Head of Department with the opportunity to ask questions. This will be followed by breakout sessions in MSc subject group areas. We will have Programme Directors, Admissions staff and students available to answer your questions about studying an MSc programme in our department. The event will take place via Zoom meetings.

Online - Open day

Graduate Open Events: Applying for Graduate Study at UCL

The Applying to UCL for graduate study session took place in December 2021. The session, covered by our Graduate Admissions and Student Recruitment teams, provides helpful information about the process of applying for graduate study, as well as offering an insight into what we consider to be a competitive application.

Fees and funding

Fees for this course

UK students International students
Fee description Full-time
Tuition fees (2022/23) £26,600
Tuition fees (2022/23) £38,000

The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Where the programme is offered on a flexible/modular basis, fees are charged pro-rata to the appropriate full-time Master's fee taken in an academic session. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website: ucl.ac.uk/students/fees.

Additional costs

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.

Students will require a modern computer (PC or Mac). The minimum specifications should be 8GB RAM and 500GB SSD storage. A computer with the stated specifications will cost approximately £500.

Some students run Linux on their PCs while others run Windows with Linux Virtual Machines installed.

Not applicable.

For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs.

Funding your studies

For more information about funding opportunities for Department of Computer Science taught postgraduate programmes, please see the department's scholarships webpage.

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.

Brown Family Bursary

Now Closed for 2022/23
Value: £15,000 (1 year)
Criteria Based on both academic merit and financial need
Eligibility: UK

DeepMind Scholarship (Computer Science)

Value: UK Home fees, maintenance grant, plus travel and equipment grants (1 year )
Criteria Based on financial need
Eligibility: UK

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 £90 for online applications and £115 for paper applications. Further information can be found at Application fees.

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.

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.

Please note that you may submit applications for a maximum of two graduate programmes in any application cycle.

UCL is regulated by the Office for Students.