Quant Guide 2020: University College London

London, UK

 

Two University College London programmes feature in this year’s Risk.net quant guide. Both programmes are ranked in the top 20 – the Financial Risk Management MSc at 20 and the Computational Finance MSc at 19 – which also puts them among the highest-ranked programmes in Europe.

Financial Risk Management MSc

The Financial Risk Management MSc is led by Fabio Caccioli, associate professor in the department of computer science. The programme remains highly selective – of 784 applicants for last year’s intake, 88 received offers, with an application success rate of only 11%.

The curriculum is built on a foundation of four compulsory modules, plus a project – counting for two modules’ worth of academic credits – completed by all candidates. The modules are: financial data and statistics; financial engineering; market risk, measures and portfolio theory; and probability theory and stochastic processes. Students must also choose four elective modules from a large selection, including classes in algorithmic trading, machine learning with applications in finance and networks and systemic risk.

Students can complete the project element as part of an industrial placement. Those taking part in placements have two supervisors – one from UCL and one from the host company. All candidates produce a 50-page dissertation after the project is completed, regardless of their elective.

Computational Finance MSc

UCL’s Computational Finance MSc programme, which ranks eighteenth in this year’s quant guide, is overseen by Guido Germano, senior lecturer in the department of computer science. As its name suggests, the degree’s focus is on computation and programming, as well as on mathematics and financial engineering. Like its sister programme, it requires students to complete four mandatory modules, four electives, and a project and dissertation component.

Among the compulsory modules, the Computational Finance MSc shares only one with the Financial Risk Management MSc – the class in financial engineering. The other three classes – data analytics, financial market modelling, and analysis and numerical methods for finance – are exclusive to the Computational Finance degree. The optional modules on offer include classes in applied computational finance, numerical optimisation and operational risk measurement for financial institutions.

Average salaries among graduates have increased slightly on the previous year, the programme reports: in this edition of the guide, the four-year moving average was $57,534 (roughly £44,000) compared with the average of £42,500 reported in 2019.

View this institution’s entry in the 2019 guide

View other universities and a guide to the metrics tables