Quant Guide 2022: King’s College London

London, UK

QUANT 4 KCL_King's_Building_2.jpg

London, UK

 

 

King’s College London’s Financial Mathematics MSc programme received 769 applications last year, placing it second in the Risk.net Quant Guide’s ranking by number of applicants.

Financial mathematics lecturer Roxana Dumitrescu is the programme’s academic director: her research focuses on stochastic control, Lévy processes and optimal stopping. Full-time students complete the course in 12 months, while part-timers – of which there are just two in the latest cohort – take 24 months.

This year, King’s has been unable to submit data in a number of key categories, including its graduate employment rate, sectoral concentrations and average salaries, making assessment of the master’s degree more difficult. Last year, the programme reported average graduate earnings of $59,886 up to six months after completion of the degree – a strong showing among UK programmes.

Students of the degree take a set of required modules in probability theory and risk-neutral validation, as well as a 60-credit financial mathematics project component. Available optional models include classes in stochastic analysis, C++, numeric and computational methods for finance, exotic derivatives and econophysics – a discipline that applies physics methods to economics problems.

The programme’s seven academic staff include: Tiziana di Matteo, a professor of econophysics; mathematical finance professor Teemu Pennanen, a specialist in convex optimisation and probability; Martin Forde, whose research interests include Gaussian fields and multiplicative chaos; and Markus Riedle, a professor of probability theory.

Among the non-European Union programmes represented in this year’s guide, this MSc’s costs are on the lower side – for domestic students, at least. UK students can expect to pay £11,040 ($14,976) for a year’s study, while international students are charged £32,940.

View this institution’s entry in the 2021 guide

View other universities and a guide to the metrics tables

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