Quant Finance Master’s Guide 2020

Risk.net’s guide to the world’s leading quant master’s programmes, with the top 25 schools ranked

Click HERE to view the 2021 edition of the Guide

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 (full list below) feature in the 2020 edition of the guide. Of these, 25 have been ranked according to set criteria including a programme’s selectivity, its research power, and its faculty’s links with the financial industry, among others (jump to How to read the metrics tables).

US programmes continue their dominance in this year’s rankings, but the overall make-up is more diverse: eight of the top 25 programmes are European, while another two are Canadian. Five programmes from Asia-Pacific also feature in this year’s guide, including City University of Hong Kong’s MSc Financial Engineering programme, which makes its debut, as does the Chinese University of Hong Kong, Shenzhen’s Master of Science in Financial Engineering – the first institution based in mainland China to feature in the guide.

As before, the rankings give particular weight to average graduate salaries and, in a slight tweak to the methodology this year, slightly more prominence is given to a strong graduate employment rate (jump to Ranking methodology below for details).

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 – which may still feature quantitative finance courses, have not been considered here. The list of programmes is non-exhaustive; and programmes that failed to provide updated statistics were not included in the 2020 edition.

We are once again 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.

Click on universities in the table below for full course details. If the table is not displaying properly, click here for a pop-out version

 

Research and profiles: James Ryder. Ranking methodology: Mauro Cesa. Editing by Alex Krohn, Louise Marshall, Joan O’Neill and Tom Osborn.

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 very similar to that used for the 2019 ranking, with two metrics modified and some weightings updated: instead of the ‘total number of students’ metric used in 2019, this year average class size was considered instead, with smaller average class sizes weighting more favourably; and instead of the absolute number of industry-affiliated lecturers, the ratio between that number and the total number of lecturers was considered, which describes the contribution of industry practitioners to the programme more accurately.

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 lecturers and students;
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;
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 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.

In order 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.

 

 

Americas

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
Columbia University
Cornell University
Fordham University
Georgia Institute of Technology
University of Illinois at Urbana-Champaign
Johns Hopkins 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
Rutgers University
Stony Brook University
University of Washington
University of Toronto
University of Waterloo

Europe

City, University of London (Bayes Business School, formerly Cass Business School)
Imperial College Business School
Imperial College London
King’s College London
University College London
University of Oxford
University of Warwick
University of York
EPFL
ETH Zurich/University of Zurich
University of St Gallen
Sorbonne University/Ecole Polytechnique
University of Paris
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
Hong Kong University of Science and Technology
Chinese University of Hong Kong, Shenzhen

View the 2019 guide