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.
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).
Core modules -Market Risk Measures and Portfolio Theory -Numerical Analysis for Finance -Financial Data and Statistics -Financial Market Modelling and Analysis
Optional modules -Operational Risk Measurement for Financial Institutions -Stochastic Processes for Finance -Financial Engineering -Supervised Learning -Programming & Mathematical Methods for Machine Learning -Financial Institutions and Markets -Networks and Systemic Risk -Market Microstructure -Algorithmics -Database Systems -Software Engineering -Applied Computational Finance
Dissertation/report 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 an a dissertation. Assessment is through coursework, unseen examinations and a dissertation.
This is a relatively new programme and therefore no 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.
Employability 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 was ranked first in the UK for computer science and informatics in the Research Excellence Framework (REF) 2014. 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.
Selection criteria: The bursary will be awarded based on financial need only as determined by the Student Funding Office.Value, Benefits and Duration: - The value of the bursary is £15,000. The payment is to be applied to tuition fees in the first instance, with any remainder being paid to the successful applicant towards maintenance in termly instalments. - The bursary is tenable for one year only. - The bursary may not be held alongside other tuition fee only awards.
Value of Scholarship(s)
Applicants must be: - prospective full-time UK Master's students who are undertaking a one-year programme of study in the Faculties of the Built Environment, Engineering Sciences or Mathematical & Physical Sciences (BEAMS) in 2015/16 - currently holding a first-class Bachelor's degree; and - in financial need.
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.
Recipient: University College London
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