Quant Guide 2022: Paris-Diderot University

Paris, France

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Paris-Diderot continues a strong showing by French universities in this year’s guide, breaking into the top-20 ranked programmes for the first time. This year, it has cut down its cohort size slightly, going from 70 to 65 full-time students, most of whom are domestic. Applications also increased, from 320 to 348. The programme’s offer-holder acceptance rate fell from 78% to 63%, however – a function of a larger number of offers being extended to applicants. This year, 103 were invited to become the latest cohort, versus 90 last year.

Huyên Pham now shares leadership of the programme with two others: professor of applied mathematics Jean-François Chassagneux; and probability and stochastic analysis specialist Eva Löcherbach.

Average graduate salaries have increased, reaching $68,000 – a strong return on investment, considering that the one-year programme costs just €250 for domestic students and €3,700 for internationals. The programme’s teaching staff have also been active in research, with a number of instructors – including co-director Pham, as well as quantitative finance professor Peter Tankov and mathematics professor Stéphane Boucheron – amassing more than 1,000 new academic citations apiece since last year’s guide.

Modules are offered in eight key topic areas: a core set, including classes in stochastic calculus and machine learning; a quantitative finance set, including derivatives, quant analysis and interest rate modelling classes; data science, including optimisation for machine learning and a project component; asset management, including stochastic control and algorithmic trading material; computer science, including programming in C++; risk management, including credit risk modelling; statistics and machine learning; and numerical and computational methods, including partial differential equation (PDE) methods and Monte Carlo simulation.

View this institution’s entry in the 2021 guide

View other universities and a guide to the metrics tables

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