Quant Guide 2022: University College London

London, UK

 

 

Computational Finance MSc

University College London’s (UCL) Computational Finance MSc has grown slightly in size this year, hosting 42 students, while becoming significantly more popular among applicants, boasting 708 for the latest intake versus 377 in 2020. And the programme became significantly more selective this year: 93 hopefuls received an offer for most recent student cohort – almost the same number as in 2020.

The programme is led by professor of computational science Guido Germano. Classes are split across compulsory and optional modules. Core topics for the latest programme include: numerical methods for finance; data science; machine learning; and a project or dissertation component, worth 60 of the programme’s 180 credits.

Optional courses on offer include: operational risk measurement for financial institutions; market microstructure; algorithmic trading; blockchain technologies; and market risk and portfolio theory.

Since the programme’s appearance in the 2020 Quant Guide, average graduate salaries have remained fairly level, with the course now reporting a compensation figure of £42,932 ($57,882). Following completion of the MSc, a majority of graduates find work in banking and asset management, with smaller numbers going into fintech and academia.

Financial Risk Management MSc

UCL’s Financial Risk Management MSc, directed by professor of complex systems Fabio Caccioli, is the smaller of the university’s two programmes by intake, with 26 students in its latest cohort, all of whom are international. It’s more popular with applicants, however, receiving 1,067 applications for the most recent intake.

The programmes share some elective modules, and both require projects or dissertations. The core classes are different, however, save for a class in financial engineering. In the Financial Risk Management MSc, core modules are taken in: data-driven modelling of financial markets; probability theory and stochastic processes; and market risk and portfolio theory.

The programme’s optional modules include classes in machine learning, algorithmic trading, networks and systemic risk.

The two MScs also share some teaching staff. Such instructors include: professor of complexity science Tomaso Aste, who teaches a module in financial data and statistics; economist Paolo Tasca, director of the university’s blockchain tech centre; and the respective programme directors, Caccioli and Guido Germano.

Employment routes taken by Financial Risk Management MSc graduates are similar to those following from the Computational Finance course: most take roles in banking, asset management and fintech. Average starting salaries are lower, however, with graduates earning £37,667 on average following completion of the course. The Financial Risk Management MSc has a slightly higher employment rate, however, reporting 85%, versus 82% for the Computational Finance course.

View this institution’s entry in the 2020 guide

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