Princeton tops inaugural Risk.net quant master’s ranking

Course sees off competition from Berkeley’s Haas and three New York schools

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This article accompanies Risk.net’s updated guide to the world’s leading quantitative finance master’s programmes. The full guide and a ranking of the top 15 courses can be found here.

Princeton University’s master in finance programme has topped Risk.net’s 2019 ranking of quantitative finance-focused graduate programmes – the first global ranking of its kind.

The ranking factors in metrics including graduate salaries, selectivity, student-lecturer contact hours and faculty research scores to evaluate over 40 leading quantitative finance master’s programmes worldwide. Particular weight was given to average graduate salaries and a strong employment rate. The full methodology will be published online later this week, alongside the ranking.

Princeton prevailed against stiff competition, both international and domestic. Master of financial engineering programmes at the Haas School of Business, part of University of California, Berkeley, and City University of New York’s Baruch College, took second and third place in the ranking, respectively. Mathematics of finance master’s programmes at New York University’s Courant Institute of Mathematical Sciences and Columbia University round out the top five.

René Carmona, programme director of Princeton’s course, highlights the programme’s small size, strong focus and one-to-one interaction between students and faculty as core drivers of its success. Its intake is smaller than most of its peers, at 25; its acceptance rate – just 5% of those who apply get in – is among the tightest.

“The programme is small, and a small number of faculty ensure its continuity. Four or five people have been with the programme since the beginning, and they’ve devoted a lot of time to its design and evolution,” he says. “We give individual attention to the student, which you will not find in many other programmes.”

The course resulted in an average 100% employment rate among graduates, and average earnings after six months of $160,000 – both high-water marks among its peers.

The programme also leans heavily on its alumni network: former students interview applicants during the admissions process, and act as mentors once students arrive on campus. Successful applicants then complete a career development survey and are connected, on the basis of their stated strengths, weaknesses and ambitions, with an alumni mentor.

“Before they set foot on campus they are involved with the alumni of the programme and alumni of the university. So when they make the final decision after being admitted to come to Princeton, they have a very precise and good taste of what life is going to be during the programme and after,” Carmona says.

Besides their involvement in mentorship relationships, some alumni have even returned as instructors.

“Some have been out for 10 years and become successful running hedge funds, for example,” he says. “And they come back to teach a course. I think this makes [the programme] extremely special.”

Of the other institutions in the top five, programme sizes varied: from the 110 students on Courant’s mathematics in finance course to the cosy cohort of 40 at Baruch College. But what all the top-ranked programmes had in common was they were heavily oversubscribed. Acceptance rates for the top five were uniformly low – likely an indicator that their reputation garners high numbers of applicants.

Commenting on US schools’ dominance in Risk.net’s rankings, Carmona argues their more vocational focus may give them an edge when it comes to matching the needs of employers compared with European master’s programmes, which have historically tended to be more theoretical.

For instance, European institutions “still train Q quants”, he says, referring to the risk-neutral method of valuing derivatives trades, as compared with assumptions based on historical data. “Q quants are extremely theoretical and mathematical – and they can be superb – but what the industry wants now is more P quants. They’re people who can look at real data. The philosophies are different.”  

Princeton’s intake is also among the most gender balanced of quant courses, with 56% of the intake male, and 44% female.

Editing by Tom Osborn and Alex Krohn

Correction, January 15, 2019: This article previously gave Princeton’s annual intake as 35 students; in fact, it is 25.

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