Quant Finance Master’s Guide 2022
Risk.net’s guide to the world’s leading quant master’s programmes, with the top 25 schools ranked
CLICK HERE TO SEE THIS YEAR’S PROGRAMME RANKINGS
Welcome to the latest edition of Risk.net’s guide to the world’s leading quantitative finance master’s programmes, and ranking of the top 25 courses.
Fifty programmes feature in the 2022 edition of the guide, with the top 25 ranked according to Risk.net’s proprietary methodology. The table shows all 50 programmes – click on an institution’s entry in the table to access its full listing, featuring all programme data and interviews with course directors. A full list of all entries can also be found at the bottom of this page.
The Sorbonne, producer of many storied quants, caps a strong showing for French programmes this year, with the Sorbonne’s Master’s in Probability and Finance climbing to fourth place – taking the palm of top-ranked European course – and the Université de Paris entering the top 25.
That’s about as good as it got for European programmes this year, though: only six feature in the top 25 – the same number as New York – down from nine last year. Among US schools, however, the composition of the rankings has shifted dramatically, with east coast and west coast rivals each making dramatic gains at the expense of some renowned Manhattan colleges to dominate the top 10.
Some have seen their ranking drop precipitously, with scores of successful applicants choosing to defer their places until the start of the next academic year, often because of travel bans and regional restrictions – hurting a university’s percentage of offer-holders’ enrolling. Others submitted data too late to be ranked, while others failed to submit entirely.
As before, the guide covers only master’s programmes in which the teaching of quantitative finance is central. Programmes whose focus is on other subjects – corporate finance, management or statistics – that may still feature quantitative finance courses have not been considered here. The list of programmes is non-exhaustive. Programmes that failed to provide updated statistics were not included in the 2022 edition.
We are grateful for the help of programme directors and faculty administrators when collecting data. Risk.net bears no responsibility for exceptions, oversights or omissions. We will gladly consider feedback in this regard.
The guide should not be relied on for advice, but we hope it proves helpful to would-be master’s students, their teachers and their future employers.
Research and profiles: James Ryder and Charlotte Grimwade. Ranking methodology: Mauro Cesa. Editing by Tom Osborn, Alex Krohn and Louise Marshall.
Ranking methodology
To compile the ranking of the top 25 programmes, we considered eight metrics. These have been standardised with respect to the total pool of entries, and a weight has been assigned to each to reflect their contribution to the final score. The total score is the sum of the eight standardised metrics. The institution with the highest score takes the top position in the ranking.
The methodology used for this year’s ranking is identical to that used for the 2021 guide. The eight variables and the respective weights are:
5% – Average class size;
10% – Acceptance rate;
10% – Percentage of offer-holders who enrol;
5% – Ratio between students and lecturers;
10% – Number of industry-affiliated lecturers over the total number of lecturers;
30% – Employment rate in finance sector six months after graduation;
5% – Number of citations for the five most cited lecturers in the past four years; and
25% – Average salary six months after graduation, adjusted for the purchasing power conversion factor provided by the World Bank.
The average number of students per class, the ratio between number of students and lecturers, and the programme’s acceptance rate – an indicator of the selectivity of a programme – contribute negatively to the final score, so the lower they are, the higher its final score.
For an institution to be considered for this ranking, it needed to provide sufficient data for the calculation of the final score. Institutions that submitted insufficient data have not been considered.
Not all institutions provided the number of citations for their lecturers. Where possible, these figures were sourced from Google Scholar. Where that was not possible, the number of citations is considered as zero.
The ranking, as well as the guide, relies on the figures provided by the institutions to be accurate. Risk.net bears no responsibility for any inaccurate metrics, or their impact on a university’s position in the guide.
North America
Baruch College, City University of New York
Boston University (Questrom School of Business)
University of California, Berkeley (Haas School of Business)
University of California, Los Angeles (Anderson School of Management)
Carnegie Mellon University
University of Chicago
Columbia University
Columbia University (Columbia Engineering)
Cornell University
Fordham University (Gabelli School of Business)
Georgia Institute of Technology
Johns Hopkins University
Lehigh University
University of Minnesota
New York University (Courant Institute of Mathematical Sciences)
New York University (Tandon School of Engineering)
North Carolina State University
Princeton University (Bendheim Center for Finance)
Rutgers University
Stony Brook University
University of Washington
University of Toronto
University of Waterloo
Europe
City, University of London (Bayes Business School)
Imperial College Business School
Imperial College London
King’s College London
University College London
University of Oxford
University of York
ETH Zurich/University of Zurich
University of St Gallen
Paris-Diderot University
Paris-Saclay University
Paris-Sorbonne University/Ecole Polytechnique
University of Bologna
Collegio Carlo Alberto, University of Turin
University of Florence
University of Amsterdam
Erasmus University Rotterdam
WU: Vienna University of Economics and Business
Technical University of Munich
KU Leuven
Asia-Pacific
Monash University
University of Technology Sydney
City University of Hong Kong
Chinese University of Hong Kong, Shenzhen
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