Royal Holloway, University of London

Royal Holloway, University of London

Computational Finance

Computer analysis of 'Big Data' has countless applications in the modern world, from architecture to business intelligence to cloud computing. Study Computational Finance at Royal Holloway, University of London and you'll learn and refine contemporary computational methods of financial modelling, allowing you to specialise in modern quantitative financing. This flexible programme is offered jointly by the Department of Computer Science and the Department of Economics, giving you the chance to choose from a large variety of engaging optional modules, including Fixed Income Securities and Derivatives, Origins of the Financial Crisis and Digital Forensics. Royal Holloway is located in the M4 corridor to the west of London - a major technology hub often referred to as 'England's Silicon Valley' - providing students with proximity to some of the country's leading technology institutions. Study Computational Finance at Royal Holloway and you'll become a part of a leading research culture. The Department of Computer Science was ranked 11th in the UK for the quality of its research publications by the Research Excellence Framework 2014, while the same survey placed the Department of Economics in the country's top ten. You'll graduate with an attractive Masters qualification in a sector with excellent graduate employability prospects. Our recent alumni have gone on to enjoy rewarding careers in banking and finance and management consultancy, as well as academic and research positions at prestigious organisations including Google, Amazon and American Express. - Study in two highly-regarded departments, respectively ranked 11th and 8th in the UK for research quality (Research Excellence Framework 2014). - Benefit from strong industry ties, with close proximity to 'England's Silicon Valley'. - Graduate with a Masters degree with excellent graduate employability prospects. - Tailor your learning with a wide range of engaging optional modules. - Choose from a one-year programme structure or add an optional year in industry.

Entry requirements

- UK upper 2nd class Honours degree (2.1) or equivalent in computer science, engineering, mathematics, physics, statistics or other subjects that include a strong element of both mathematics and computing.

- Relevant professional qualifications and relevant experience in an associated area will be considered.

- English language requirements: IELTS 6.5 overall and minimum of 5.5 in each subscore.

Course modules

Mandatory modules: Data Analysis; Programming for Data Analysis; Database Systems; Foundations of Finance; Investment and Portfolio Management; Individual Project. A range of optional modules are also available.

Assessment methods

Assessment is carried out by a variety of methods including coursework and a dissertation.

Qualifications

Qualification Study mode Start month Fee Course duration
MSc Full-time September 2017 GBP 8,300 per Year 1 (Channel Islands) 1 years
MSc Full-time September 2017 GBP 8,300 per Year 1 (EU) 1 years
MSc Full-time September 2017 GBP 8,300 per Year 1 (England) 1 years
MSc Full-time September 2017 GBP 18,500 per Year 1 (International) 1 years
MSc Full-time September 2017 GBP 8,300 per Year 1 (Northern Ireland) 1 years
MSc Full-time September 2017 GBP 8,300 per Year 1 (Scotland) 1 years
MSc Full-time September 2017 GBP 8,300 per Year 1 (Wales) 1 years
MSc Part-time September 2017 GBP 8,300 per Year 1 (Wales) 2 years
MSc Part-time September 2017 GBP 8,300 per Year 1 (Channel Islands) 2 years
MSc Part-time September 2017 GBP 8,300 per Year 1 (EU) 2 years
MSc Part-time September 2017 GBP 8,300 per Year 1 (England) 2 years
MSc Part-time September 2017 GBP 18,500 per Year 1 (International) 2 years
MSc Part-time September 2017 GBP 8,300 per Year 1 (Northern Ireland) 2 years
MSc Part-time September 2017 GBP 8,300 per Year 1 (Scotland) 2 years

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