Quant Guide 2021: Baruch College, City University of New York
New York City, US
Baruch College’s Master of Science in Financial Engineering (MFE) is one of a number of perennially high-scoring programmes in the Quant Guide. In both the 2019 and 2020 guides, the MFE achieved third place. This year, it rises to second, helped along by perfect employment scores for its graduates, and an intimidatingly low chance of acceptance for those applying. When the MFE’s academic director, mathematics professor Dan Stefanica, , he expressed concerns about the pandemic’s impact on the intake size for the programme. The latest class contains 26 full-time students, however – comfortably within the programme’s preferred 20–50 student range, and the same number as last year’s cohort. Applications did fall, but only slightly, from 506 to 490. The right quantity of candidates has been reached despite the “tremendous difficulties” international students experienced getting visas, Stefanica says, praising the “resourcefulness” of the students who were able to make it into the country. Classes are currently delivered in a hybrid format, with both in-person and virtual teaching available. Stefanica adds that some planned course content has been delayed as a result of the virus: a proposed module on artificial intelligence in finance, he points out, has been put on hold. “We decided to postpone it for one year so as not to put an additional burden on a new instructor,” he says. That new member of staff is Yanghui Liu, who has joined the faculty of mathematics as an assistant professor, coming from Tufts University. The rest of the course has gone ahead as normal, and Stefanica says that the online teaching – while undesirable long-term – has been received well by staff and students alike. Everybody misses in-person interaction, he says, but many are glad to save time and money on commuting. The MFE’s graduate prospects remain encouraging, Stefanica says, adding that all of the programme’s partner firms are hiring as normal, despite some short delays, and that the course is on target to place all of its soon-to-be graduates before they qualify in December.
Quant Guide 2021: Princeton University (Bendheim Center for Finance)
Princeton, New Jersey, US
Princeton University’s Master in Finance has dominated the Quant Guide rankings to date, achieving first place in both the 2019, 2020 and 2021 leader boards – a grip it maintains thanks to its excellent research score, high ratio of lecturers to students, and stellar employment prospects for its graduates. The course, led by professor of engineering and mathematics René Carmona, reports consistently high starting salary and employment figures, which have so far edged out those of the competition. This year’s cohort is on the smaller side, compared with those in the 2019 and 2020 Quant Guides, when they comprised 25 and 26 new students respectively, while this year’s contains 20. The programme saw a higher number of applicants compared with the last edition of the guide, with 597 graduates applying for the latest academic year versus 522 in 2020. The programme also made fewer offers, giving just 33 of those 597 applicants the thumbs up. Two new modules have been incorporated over the last year, says the Bendheim Center’s Lindsay Bracken, who oversees career development and alumni relations. One is an autumn course devoted to financial technology, exploring the uses of big data in designing digital tokens, smart contracts, credit rating systems and more. Peer-to-peer lending, cryptocurrency valuation and micro-credit are also studied, Bracken tells . The second new module focuses on financial crises, and is taught by Bill Dudley, former president of the Federal Reserve Bank of New York. Students investigate the 2007–09 crisis and the ongoing disruptions caused by the coronavirus, says Bracken, and evaluate the efficacy of policy responses. Like its peers, the programme has not been immune to Covid disruptions. Classes are being conducted remotely, and Bracken says that precepts – small, seminar-style discussion groups – have had tighter size limits imposed, with the goal of ensuring each student receives individual attention from instructors. One-on-one career coaching sessions, she adds, are favoured over group placement meetings as a way to reduce student screen time.
The Master of Science in Quantitative Finance (MSQF) taught jointly by ETH Zurich and the University of Zurich (UZH) makes another strong showing in this year’s Quant Guide, rising eight places to fourth overall – the highest-ranking European institutions represented. The programme, led by academic director Erich Walter Farkas, has always been highly selective. Competition for a place in the latest intake was especially fierce, with 43 out of 294 applicants receiving offers. The course is also highly popular among offer holders, with 37 out of those 43 accepting. For the previous year’s programme, 51 offers were given to 243 applicants. Farkas says the two university departments involved in the programme’s delivery – the faculty of business, economics and informatics at the University of Zurich and the depart of mathematics at ETH Zurich – responded well to the unprecedented disruption seen in 2020. Classes were offered via Zoom and Microsoft Teams, and additional office hours were arranged for the course’s 32 instructors. Two new members of staff also joined the programme this year: Dylan Possamaï and Beatrice Acciaio, who are both professors in the department of mathematics at ETH Zurich. Both will teach regular courses and supervise master thesis projects, Farkas tells . Like most programmes in this year’s guide, classes were conducted remotely with the option to replay past material. Live elements, Farkas says, were emphasised. Particular classes open to students from other programmes, such as Martin Schweizer’s mathematical foundations for finance, were conducted live for MSQF students only. This, he says, was intended to help foster interaction in the cohort. Examinations were also conducted remotely, on an internal platform used by the universities. Farkas says that assessments went well, with grade distributions comparable to pre-pandemic years.
Quant Guide 2021: Columbia University (Columbia Engineering)
New York City, US
Columbia’s Master of Science in Financial Engineering re-enters the Quant Guide this year, ranking at sixth place. The programme is directed by Sauma Capital’s Ali Hirsa and by quantitative finance pioneer , co-author of one of the first interest rate models (Black-Derman-Toy) and numerous seminal papers on model risk. The Columbia MS programme is housed in the department of industrial engineering and operations research, and is highly popular among would-be students – there were 1,114 applications to join the current cohort. In all, 121 offers were extended to the pool of applicants, and 119 accepted them, which gives the programme the highest offer-holder acceptance rate in the Quant Guide, at 98.3%. After successful completion, the course has a graduate employment rate of 95%. Average graduate compensation is $106,833. The school has made a range of adjustments to the programme in response to Covid-19. The MS reports offering staggered matriculation dates, extending virtual office hours and providing courses “around the clock”.
Quant Guide 2021: New York University (Courant Institute of Mathematical Sciences)
New York City, US
The Courant Institute’s MS in Mathematics in Finance is a consistent high achiever in ’s Quant Guide. This year, it appears in third place, behind Princeton University and neighbouring Baruch College. Like many of its peers, the three-semester MS, directed by clinical professor of mathematics Petter Kolm, is smaller this year: there are 27 full-time students in the latest intake, versus last year’s figure of 46. They’re outnumbered by an increased number of teaching staff: 37, compared with last year’s 33. Further, 34 of this year’s instructors have an industry affiliation – a key metric for the Quant Guide rankings. Courant’s sister programme at New York University’s (NYU) places a similar emphasis on retaining instructors from the financial services: 61 of Tandon’s 67 teaching staff are industry affiliated, or 91%. Courant also reported both an uptick in median graduate salaries and a drop in fees. The median starting salary is now $103,700, versus last year’s $97,000. The mean figure has held steady at a competitive $115,000, still among the highest in this year’s guide. A figure of $83,000–$85,000 was given for tuition fees last year, while students will see a drop in price this year to approximately $73,000–$76,000. The programme has also gone through a variety of coronavirus-related changes, like many others in this year’s guide. All summer internship placements were moved online, and 100% exams will be conducted remotely. NYU also mounted an ongoing testing effort, as well as requiring campus attendees to complete daily Covid-19 ‘screener’ questionnaires via the university’s mobile app.
Quant Guide 2021: New York University (Tandon School of Engineering)
New York City, US
Once again, the MS in Financial Engineering at New York University’s Tandon School of Engineering is far and away the most popular course by number of applicants in this year’s Quant Guide. This year, the programme reports receiving 1,980 applications for its autumn 2019 intake, and 1,886 for autumn 2020. But, like other US-based programmes that boast a high proportion of international students, Tandon’s latest cohort has shrunk in size, thanks to the coronavirus’s impact on travel restrictions. While extremely popular among applicants, a large number of Tandon’s accepters have deferred their enrolment until 2021. When course director Peter Carr to earlier this year, he predicted that the 2020 autumn intake would be significantly smaller than previous classes as a result of such deferrals. Indian students, in particular, he said, would have an extremely tough time obtaining the necessary student visas. So it has proved. The autumn 2020 cohort has ended up numbering 96 students, a precipitous drop from the previous year’s 157. Ultimately, 120 students have deferred their admission to autumn 2021. “Our large deferral group of 120 students is a consequence of a fairly large deposit – $3,000 – and that several other programmes did not allow deferrals,” says Carr, adding that, on the plus side, “right now, we are forecasting that half of the 120 who deposited and deferred will enrol in autumn 2021, which is our next intake. This means that we can be much more selective than usual”. In addition, the smaller-than-usual cohort this year means the hit to the programme’s percentage of offer holders who enrol – stats that account for 10% of a programme’s score (see the for an explanation of the methodology) – is partially offset by a smaller average class size and an improved student ratio versus the programme’s 67 teaching staff, 61 of whom are industry-affiliated. There are also several new instructors among the group, Carr adds. Faculty staff joining in the last year include: programme alumnus Serge Feldman, formerly of JP Morgan, who teaches a course on financial software engineering; Michael Lipkin, who teaches a new course in event-driven finance; Sateesh Mane, who also leads a financial software course; and Sandeep Jain, who joined the programme in spring, and teaches a class in machine learning and finance. One other new course besides Lipkin’s has been added: a class in fixed income algorithmic trading, led by Sudeep Lahiri.
Cornell’s New York-based Master in Engineering with Financial Engineering Concentration (MFE) programme, split across two campuses, is a persistent high scorer in Quant Guides. This year, it maintains the 9 place ranking it achieved in 2020, leapfrogging rival Carnegie Mellon University’s Master of Science in Computational Finance, another dual-campus programme with a New York presence, which slips to 10 . For Cornell’s most recent programme, total applications have risen strongly, with the MFE reporting 874 this year, versus the previous year’s 737. The programme also extended fewer offers, with 149 given out this year versus last year’s 169, boosting its selectivity score. Fees have risen for the second year in a row, from $84,825 in the last Quant Guide to $87,870 today. The research score of the course’s faculty members has also been impressive over the last 12 months. Instructors such as statistician David Ruppert and computer science luminary David Williamson, for example, were both highly cited throughout 2020. Programme director and professor of practice Victoria Averbukh, formerly of Deutsche Bank, says that a raft of changes have been made to the degree’s structure in response to the coronavirus. Students based on Cornell’s Ithaca campus, she says, were able to take classes in a hybrid format. Those stationed in densely packed Manhattan, however, switched to entirely remote learning. The MFE’s large number of industry instructors, she adds, were provided with extra training in modifying their courses for online teaching. “The quality of the course delivery matters just as much as the content,” says Averbukh, adding that students have given favourable feedback on the programme’s efforts.
The University of Toronto’s Master of Mathematical Finance (MMF) programme maintains its top 10 rating in this year’s Quant Guide – thanks in no small part to its exclusivity. The course is highly selective, extending offers to just 13.5% of its 446 applicants. Luis Seco, a professor in the department of mathematical and computer sciences, remains the programme’s academic director. Despite only a little over half of those applicants taking up their places this year, and fewer students applying overall, the MMF made significant gains in one important category, highly prioritised in ’s ranking methodology: average graduate salaries six months after course completion, across the last four years of the programme. The course reports an average of US$95,000 this year, an impressive jump from last year’s upper bound of US$70,000. That puts Toronto comfortably ahead of the neighbouring University of Waterloo, which reported average salaries of US$65,000 for this edition of the guide. Thanks to the coronavirus, teaching has been conducted 100% remotely for the MMF programme’s first term, as well as examinations. Internships have also taken place remotely, with students receiving the necessary support from their placement sponsors. Internships for the upcoming year will take place in January. The university anticipates that they will also be remote, unless there is a significant change in circumstances and government advice. A programme representative adds that a number of other changes have taken place to facilitate remote instruction, including the creation of a dedicated website for course materials and the relaxation of health insurance fee requirements for students not on campus.
Luis Seco: 228 citations Roy Kwon: 360 citations Kenneth Jackson: 619 citations Tom McCurdy: 511 citations
12 months, inclusive of a 4-month full-time internship. Programme starts in mid-August and ends July 31 of the following year. First term: August to December (13 weeks) second term: January to April (internship period) third term: May to July (13 weeks).
C$53,050 for both international and domestic students
38% male, 62% female
70% male, 30% female
100% remote teaching for the first term, decisions about subsequent terms will be based on advice from provincial and public health authorities.
For the first term, all examinations will be conducted remotely.
Carnegie Mellon University’s Master of Science in Computational Finance (MSCF) is a persistent high-achiever in the Quant Guide rankings, appearing at eighth place in both the 2019 and 2020 editions. For our 2021 ranking, it slides a couple of places to tenth. The three-semester course, led by executive director and adjunct professor of business Richard Bryant, has had to make adjustments in response to the coronavirus, in common with most of its peers. For applicants unable to obtain student visas, classes have been delivered online. For those students who do attend one of Carnegie Mellon’s physical campuses – in Pittsburgh and New York – class sizes have been cut down, schedules have been adjusted to reduce corridor traffic, and mask-wearing is mandatory. The university has worked to improve ventilation, conducts regular deep cleans, and has also appointed a number of pandemic safety officers. As for the curriculum, students are expected to spend part of the summer in an industry placement. Out of 91 placements in summer 2020, only three were cancelled. However, there were adjustments: the majority of internships were conducted virtually, and some had condensed timeframes. Remote learning has also forced institutions such as Carnegie Mellon to take a fresh look at how to preserve the integrity of the learning and testing process. Speaking in August, Bryant told how staff and students were getting to grips with new , installed to discourage cheating in remote exams. In one case, the software – which also captures audio and screen activity – helped to detect one candidate who was texting during their examination, given away by a telltale tapping sound. But while they might be effective, the measures have drawn criticism from some staff and students. In response, the programme plans to adjust its invigilation approach, says Bryant. Despite various disruptions, the MSCF has remained in high demand. The latest programme received over 1,000 applications – an increase of almost 200 on last year’s figure – and extended 191 offers versus last year’s 167. The course’s graduate employment rate has risen to 99%, and graduate salaries are up, too: the mean base rate of pay over the last two years is $108,846, putting the MSCF in the Quant Guide’s highest salary quartile.
Quant Guide 2021: University of California, Berkeley (Haas School of Business)
The Master of Financial Engineering at the University of California, Berkeley’s Haas School of Business ranks fifth in this year’s Quant Guide – another strong performance, drawing on its strong research score, high number of students taking up offered places, and excellent employment prospects. The programme, led by executive director Linda Kreitzman, has some impressive stats: applications for the 2020–21 intake, at 709, are the highest recorded, while it also reports an increased employment rate of 99.18% for the most recent crop of graduates, up a full nine percentage points on last year’s figure. Student numbers have also increased slightly, with 93 candidates in the 2019–20 intake and 96 for 2020–21. Graduate salaries, however, have dropped slightly to an average of $115,132 – a high figure compared with the overall Quant Guide population, but a decrease relative to this institution’s reported average base compensation of $118,530 last year. Kreitzman says that the master’s – “the programme that never sleeps”, as she calls it – has coped well with the challenges Covid-19 has presented. “We started the programme the very same day governor [Gavin] Newsom put California on lockdown,” Kreitzman tells . “We worked hard to maintain the quality of our teaching, and firms continue to hire from us. One major global investment management firm hired eight interns, and an investment bank made four offers.” The course has also organised a flexible internship programme, allowing students to complete placements in summer, autumn or winter, in response to Covid-19. Course material includes an increased quantity of industry practice seminars. Kreitzman says these are designed to help students get to grips with the influence of the virus on financial markets, with a specific focus on credit and operational risk. A new instructor has also joined the faculty: chair of finance and accounting Christine Parlour, who has been a professor at Berkeley since 2012, will co-teach the financial innovation with data science applications class.
2019–20: 93 2020–21: 96 9 core courses required for both years
2019–20: 441 2020–21: 709
2019–20: 111 2020–21: 120
2019–20: 93 2020–21: 96
540 total contact hours
20–25 hours per week
Mean: $115,132 median: $120,000
Laurent El Ghaoui: 18 397 citations Gert Lanckriet: 9158 citations Martin Lettau: 4898 citations Terrence Hendershott: 4364 citations Nicolae Gârleanu: 3739 citations
$75,108, regardless of status for current MFE21
72.9% male, 27.1% female
87% male, 13% female
During the initial three quarters, all coursework was delivered remotely. Independent study is offered on a hybrid model, allowing for limited in-person contact with advising faculty and staff. Small group classes will be provided in the spring quarter.
Quant Guide 2021: Collegio Carlo Alberto, University of Turin
Like last year, Collegio Carlo Alberto’s Master in Finance, Insurance and Risk Management is one of the smallest programmes by number of students in the Quant Guide. With just 13 candidates in the most recent cohort, the degree programme promises plenty of close attention from its 39 available instructors, 17 of whom have an industry affiliation. The course content is separated into a number of tracks, each of which contain specialised modules. The foundations and fintech track, for instance, includes classes in core topics such as mathematics for finance, econometrics and programming, and coding in Python and R. The track also features three different machine learning modules. Other tracks include: the so-called common track, which covers topics such as market and liquidity risk, financial engineering, and derivatives pricing; the ‘finance track’, with material on quantitative asset allocation, operational risk management, and regulation and banking law; and a professional courses track, featuring topics such as impact investing, private banking and robo-advising, taught almost entirely by industry instructors. A new course dedicated to the Python language, Python and Finance, has been added this year. Students take a look at some of the language’s popular applications, including usage for risk analytics, portfolio optimisation and smart beta investing. Modules that have proven popular among students in 2020 include classes in quantitative asset allocation, financial engineering and asset pricing, says Collegio Carlo Alberto’s head of education programmes management, Cristiana Moretti. She adds that, thanks to a big effort from programme staff and faculty, the shift to online teaching was not a major source of disruption. But she says that some of the degree’s regular industry partners did suspend or postpone hiring for internships and placements. Where classes did take place in person, the university took steps to reduce student presence and enhance cleaning, and masks were made compulsory on campus.
The University of Chicago’s Master of Science in Financial Mathematics returns to ’s Quant Guide this year with a strong showing, ranking 15 , thanks to its performance on the key metrics of average employment rate, graduate salaries and popularity among applicants. Chicago’s programme, led by associate professor of mathematics Roger Lee, remains in high demand among prospective students. The school reports receiving 1,358 applications for its latest intake, making it one of the most popular participants in the guide. Of that large number of applicants, 68 ended up enrolling this year. The master’s also reports a strong average starting salary of $101,920, and an employment rate of 95% across the last four years. Students tackle an academic curriculum comprising 400 units of mandatory or ‘core’ courses, 400 units of computing, and 450 units of electives. Core subjects include: mathematical foundations of option pricing; probability and stochastic processes; and two sets of classes on portfolio theory and risk management. Available computing courses include classes in Python, C++ and machine learning. The range of electives, meanwhile, include topics such as model risk, multivariate data analysis and market microstructure. Students can also work on a 10-week project lab course, on material provided by partner firms. The course may be taken more than once – according the programme, many students take it repeatedly to build industry experience.
Imperial College London’s MSc in Mathematics and Finance is the highest-ranking UK-based programme in the 2021 Quant Guide, and the second-highest in Europe. Since the previous edition of the guide, the programme has made impressive progress on graduate wages. It now reports an average base pay of $115,000 over the last two years of graduating classes, an increase of $10,000 on the figure in the 2020 guide. Other notable developments include the addition of Aitor Muguruza to its ranks of instructors – he was a member of the three-strong that won the Risk Award in 2020. Also, this month, Paul Bilokon starts teaching computing in C++, a core class in the master’s, in addition to his existing position as a lecturer on advances in machine learning. Bilokon is the former head of credit and core e-trading quant teams at Deutsche Bank, and the founder and current chief executive of consultancy Thalesians, which focuses on quantitative finance, algorithmic trading, machine learning, artificial intelligence and big data. As a result of the Covid-19 pandemic, exams have moved online, and teaching is conducted in a mixture of virtual and traditional classrooms, says course director Antoine Jacquier. He grants that it is more difficult to invigilate a remote exam, but points out that the new format has also led to some improvements. “We are changing the structure of the exams, encouraging more thinking, rather than just repeating lecture content,” he says, adding that the change has provided question-setters an opportunity to make the material more challenging. Students offer their perspectives on the programme via weekly feedback sessions and Jacquier says opinions are favourable overall. The availability of recorded lectures is popular, and students appreciate the opportunity to subject tough material to repeat viewings. “We also run weekly ‘cohort-building’ sessions, splitting the class into small groups and working, online with videos, on short problems,” he adds. “Through them, students get to know each other better – we have been receiving very positive feedback.”
North Carolina State University’s Financial Mathematics master’s programme continues to punch above its weight in the latest iteration of ’s Quant Guide, ranking at 13 place, ahead of many more storied institutions – a product of its excellent student:staff ratio and powerhouse research score. It has, like many of its peers, experienced coronavirus-related setbacks this year. A number of international students weren’t able to enrol because of travel restrictions, says programme director and mathematics professor Tao Pang, and some chose to defer their places. However, it has still managed to grow: 58 offers were extended to 273 applicants, and 44 of those offers were accepted. This gives the programme an impressive offer-holder acceptance rate of over 75%. Nevertheless, just 17 offer holders ended up enrolling as full-time students. Pang calls this blow to what could have been a bumper intake the “biggest impact” the virus has had on the programme thus far. “In-person events, both formal and informal, are important in helping students acclimate, share knowledge and form a cohesive identity as a cohort,” adds Pang. “We’ve had to be creative to foster these outcomes in other ways.” He says that the programme has moved a number of events online, including roundtables, social events and alumni ‘visits’. Cannily, the programme has also moved to provide additional training in remote interviewing and in giving virtual presentations. Such skills will come in handy over the next few months, says Pang, while a majority of white-collar work still takes place from home. A new course that has been incorporated focuses on investment in financial markets, with material on: stock, bonds and derivatives valuation; investment strategy; and portfolio performance evaluation. A new instructor, hired this autumn, is assistant professor Andrew Papanicolaou, formerly of New York University’s Tandon School of Engineering. Papanicolaou specialises in machine learning and data science with applications in finance, Pang tells .
Like many US programmes, students of the MS Computational Finance and Risk Management (CFRM) programme at the University of Washington have felt the impact of Covid-19 this year. However, while some courses have struggled with the switch to remote teaching, Washington had a unique advantage up its sleeve: the programme has an established online option, designed for professionals studying part-time, which long predates Covid-19. As such, says programme director Tim Leung, the programme was able to adapt “fairly easily” when virtual teaching became the norm. While candidates found fewer internship placements overall – 75% of students in 2020, compared with usual numbers of 95–100%, Leung says – those that did ranged far and wide over the US, thanks to the internet. “Internships were based in 11 cities – an increase over 2019,” says Leung, professor of applied mathematics. “Placements included: a data scientist at Amazon Forecasting; a risk analyst at Western Asset Management; a capital markets intern at the Federal Home Loan Bank of Des Moines, Iowa; and a data support intern at Parametric Portfolio Associates.” Other students, he adds, took positions at companies such as QuantConnect, AJO Partners, and took part in Google’s yearly ‘Summer of Code’ programme. Popular courses this year, he tells , included a class in machine learning for finance and a class in credit risk management. The programme also incorporated a new advanced computational finance journal club, and a new module on portfolio performance analysis and benchmarking. Despite being well prepared, the CFRM didn’t escape 2020 totally unscathed. Applications fell relative to last year’s figure of 428, to 332. A greater proportion of successful applicants accepted their offers – 44% this year versus 37% in the previous guide – but fewer students enrolled overall, with 41 in the latest cohort against 54 in the previous intake.
Co-sponsored by the departments of mathematics and statistics, the Master of Arts in Mathematics of Finance at Columbia appears at 17 in this year’s quant master’s guide. The MA continues to be led by Lars Tyge Nielsen. The programme is popular among students – for its current intake, the MA received 1,250 applications – its employment statistics giving a good indication as to why that is. Like its fellow Columbia programme – the – the course has an employment rate of 95% after successful completion. Also, like the MS programme, the MA’s graduate compensation figure, at $102,335, is a strong one relative to the rest of the guide’s constituents. Based in one of the most concentrated metropolitan areas, the course has met the challenge of the coronavirus in creative ways. Its administrators have moved some classes to early summer, in order to reduce the number of students on its New York City campus, and provides a broad range of web-based career support. Its efforts include meetings with employers and alumni, careers fairs and individual career coaching appointments – all conducted virtually.
Ioannis Karatzas: 6349 citations Amal Moussa: 287 citations Julien Guyon: 322 citations Lars Tyge Nielsen: 206 citations Alexei Chekhlov: 184 citations
Most full-time students will complete the programme in two or three semesters. For the two-semester option: two semesters of 14 weeks each, plus exam period. Fall semester 2020: September 8–December 23 spring semester 2021: January 11–April 23.
$110,369 (includes tuition, fees/insurance and living expenses)
Like many of its North American peers, the University of Waterloo’s Master of Quantitative Finance programme has been taught entirely remotely for much of this academic year, thanks to the impact of the coronavirus. “The hope is to be 100% in-person for fall 2021, but, of course, it is not really possible to predict that far in advance,” says graduate programme administrator Helen Chen. She adds that internships during the spring of this year were conducted wholly remotely, and that exams were either remote or take-home throughout the autumn, with some on-campus classes starting up again in the winter. The programme is highly selective, with its current intake numbering 13. Waterloo’s master is also particularly strong when it comes to popularity among offer holders: it extended just 27 offers to 127 hopefuls this year, 20 of whom accepted. That gives the programme a competitive offer-holder acceptance rate of 74%, an improvement on last year’s figure of 57%. With teaching staff also growing – 17 this year, versus last year’s 12 – that means a boosted student:staff supervision ratio of better than one to one. Waterloo has a clear differentiator in one key area: that of tuition fees, a priority consideration for many students. The programmer charges C$18,732 (US$14,500) for domestic students and C$25,472 for internationals.
Georgia Tech’s Master of Science in Quantitative and Computational Finance returns to the annual Quant Guide after a strong debut last year, in which the programme was one of the highest-ranking new entrants, appearing at 13th place on the leader board – a position it improves on this year by rising to 12 . The course is taught by faculty from a number of departments at the university, and is led by Sudheer Chava, who says this interdisciplinary approach provides students with a substantial range of optional modules. New courses incorporated in the past year include classes on popular machine learning libraries TensorFlow and PyTorch, and a class tackling quantitative asset management. He adds that students are most keen on the “practice of quantitative finance” module, which involves experiential learning projects. This year, the master of science reports an employment rate of 100%, with most graduates taking positions in banking or asset management, and an average of 4% moving on to further study. Mean base compensation has risen slightly, up to $94,513 from last year’s $93,105. The programme has not been immune to the impact of Covid-19, however. Chava says it has seen a disappointing fall in internship placements compared with previous programmes. “For the past several years, we’ve had 100% placement for internships,” he says. “Unfortunately, because of Covid, that number has reduced to 74%.” He is hopeful for the next iteration of the programme, however, pointing out that the cohort – which is expected to be large, due to the high number of Covid deferrals, in line with many peers – will benefit from the significant number of new teaching appointments. “We had an issue with international students coming to the US for the fall 2020 semester, so we have a record number of deferrals to fall 2021,” says Chava. “Fortunately, we’ve doubled the size of our staff this past year, so we should be able to accommodate a larger cohort.” The programme has brought an impressive 23 new instructors into the fold since the last Quant Guide, bringing the total number of teaching staff to 33.
The University of Warwick’s 12-month MSc in Mathematical Finance (MSMF) is taught jointly by the university’s departments of statistics, mathematics and Warwick Business School. Led by academic directors Alex Mijatovic and Roman Kozhan – professors of statistics and finance respectively – the course has grown in size slightly over the past year, with a larger intake of students and a bigger crop of applications compared with its appearance in last year’s Quant Guide Over three terms, students work on a set of mandatory or ‘core’ modules, a set of electives, plus a master’s dissertation. In the first term, core classes focus on fundamental topics such as: machine learning for finance; financial statistics; stochastic calculus; asset pricing and risk; and programming for quantitative finance. In the second term, there are three compulsory modules to be tackled – applications of stochastic calculus for finance; a second programming class; and financial econometrics – plus two electives, chosen from a wide range of options. The electives on offer include: statistical learning and big data; advanced trading strategies; partial differential equations for finance; advanced risk management; and behavioural finance. The third term is devoted to dissertation work. The MSMF also emphasises student access to a pair of notable centres housed in the statistics department: the Centre for Research in Statistical Methodology (CRiSM), a research body that offers workshops, seminars and a PhD programmer, led by statistician and applied probabilist professor Gareth Roberts; and Stochastic Finance at Warwick ( ), a group that runs stochastic finance seminars and a reading group, as well as a spring school in collaboration with Shanghai’s Fudan University. Over the past year, the programme has also made changes to teaching in response to the coronavirus. Live teaching sessions are recorded for remote students, staff run additional virtual office hours, and academic tutors provide guidance to students along with a dedicated programme support team.
The University of Oxford’s 10-month MSc in Mathematical and Computational Finance has grown significantly in size over the past year, despite pandemic pressures: the programme, taught at Oxford’s mathematical institute, has 36 students in the latest cohort, up from 24 in the previous year. Professor of mathematical finance Álvaro Cartea, who led the course last year, has been replaced by Justin Sirignano, associate professor of mathematics, whose research focuses on machine learning applications for finance. Cartea remains a member of the programme’s teaching staff. Besides hosting a greater number of students in total, Oxford’s MSc also had more applications compared with its previous outing. For the latest class, 265 applications were received, 60 offers were made, and 39 were accepted. Last year, 221 applications were received, 47 offers extended, and 36 accepted. The course has therefore become slightly less selective: 21.3% of applicants were successful last year, versus 22.6% for the most recent class. It was also slightly less popular among offer holders, with an offer-holder acceptance rate this year of 65%, versus last year’s 76.6%. Courses on offer include a group of mandatory classes, a computing course and a set of elective classes that take place in the programme’s second term. Each elective course – including topics in stochastic volatility, Monte Carlo methods, market microstructure, and asset pricing – comprises eight lectures and two classes. The compulsory courses across the first and second terms include topics in deep learning, quantitative risk management, financial derivatives, and statistics and data analysis. In response to the coronavirus, the MSc has moved some elements of the programme online. Autumn teaching was conducted “mostly in person”, Sirignano says, and then, due to the UK’s national lockdown, teaching between January and March has taken place virtually. He adds that it’s likely that yearly internships, which take place in the spring, will be conducted remotely.
For Rutgers University’s three-semester Master’s in Mathematical Finance programme, the coronavirus arrived at the best possible time: in the middle of the programme’s annual spring break. With the campus already deserted, says senior programme co-ordinator Ana Mastrogiovanni, the transition to online delivery was rapid. “We had to go from in-class instruction to online courses with less than a week’s notice,” she says. “We got lucky, since students were off at the time.” The situation is far from ideal: no-one is thrilled about the move to virtual teaching, Mastrogiovanni adds – 100% of classes and examinations now take place online, and, “in general, the students are not finding the online courses to be as effective as the in-class courses”. Internships have been cancelled entirely for the programme’s autumn semester, she says, which hasn’t happened “in a very long time”. Of course, some level of student dissatisfaction is inevitable — few students will have anticipated their studies taking place during a pandemic. The programme has worked hard to make the online offering as accessible as possible, Mastrogiovanni adds: if a student misses a live class due to scheduling conflicts or time zones, lectures are available to view on demand. Virtual office hours with faculty members have also been rescheduled to accommodate students in all regions. On a more positive note, the programme reports a strong upward trend in graduate salaries for this edition of the Quant Guide. The average base pay for a Master’s in Mathematical Finance graduate is now $87,000, up from last year’s figure of $70,200. Modules this year include a broad range of compulsory and optional classes: electives may be taken from among courses offered by the mathematics, statistics, computer science, and electrical and computer engineering departments. In some limited cases, students may also take electives from the business department.
Master’s in Financial Statistics and Risk Management
Paris-Saclay University’s Master of Quantitative Finance programme appears for the first time in this year’s Quant Guide, belying the university’s powerhouse reputation for mathematics. The programme is led by academic directors Stéphane Menozzi and , both professors of mathematics. At the start of this year, Paris-Saclay superseded the University of Paris-Sud (Paris XI in ). Thanks to low tuition fees throughout France, Paris-Saclay’s is also one of the cheapest course represented in the guide, with an approximate cost of $300. There are currently 32 students on the one-year programme, 17 of whom are international. The master’s is both fairly selective and popular among offer holders, with 55 out of 300 applicants receiving offers, 32 of whom accepted. Structurally, the course is split into two semesters, both of which contain a range of mandatory and elective modules. The second and final semester requires students to tackle an industry internship, which awards a large amount of course credits, as well as an English proficiency exam, the standardised TOEIC (Test of English for International Communication). Modules in the first semester include classes in programming, deep learning, stochastic calculus, and financial econometrics. The second semester features more specialised classes, in topics such as: machine learning techniques for options pricing; advanced asset management; and corporate finance and insurance modelling. Course director Menozzi says a range of measures have been introduced in response to the coronavirus. Prior to the second government-mandated lockdown, which took place on October 30, some classes were taking place on campus. After the lockdown was announced, instruction was conducted 100% remotely. Because of Paris-Saclay’s policies, Menozzi adds, students have not been tackling take-home or remote exams – assessments are being delayed instead.
The Master’s in Probability in Finance, hosted jointly by Sorbonne University and Ecole Polytechnique, climbs two places in this year’s Quant Guide, to 16 – the third-highest European programme featured. The course lasts one academic year, across two semesters and an industry internship. The first semester includes classes in probability and optimisation, derivatives, econometrics, and European Union markets. The second semester involves more advanced material, with classes on stochastic algorithms, US options, parallel computing, high-frequency trading and machine learning. A set of introductory ‘refresher’ classes are also available, prior to the beginning of the first semester, for students who want to revisit the fundamentals of quant finance. The course, like last year, is led by a trio of : Emmanuel Gobet, a professor of applied mathematics at partner institution Ecole Polytechnique; Gilles Pagès, a professor in the faculty of sciences and engineering; and Mathieu Rosenbaum, a professor at Ecole Polytechnique’s centre for applied mathematics. Course founder, the mathematician Nicole El-Karoui, is teaching an expanded range of classes this year in: longevity risk; interest rate models and derivatives; and stochastic processes and derivatives. While the programme, like many others, reports a fall in its average graduate employment rate compared with last year’s Quant Guide – 77% versus 90% – it remains highly competitive in other key areas. The average starting salary for its graduates has leapt to $94,211, compared with $58,000 last year, and the course has become even more popular among offer holders. Last year, 75 out of 83 offer holders accepted, a rate of 90.4%. This year, 71 out of 78 offer holders accepted, pushing the rate to 91.0%. It also remains one of the least expensive of all the courses represented in the guide, with tuition fees of just €330.
The Master’s in Financial Engineering (MFE) at the Ecole Polytechnique Fédérale de Lausanne (EPFL) is one of a few courses in this year’s Quant Guide that have seen intake sizes increase, rather than shrink, amid the coronavirus pandemic. It is also one of the top-ranked European programmes featured in this year’s guide, ranking 19 . EPFL’s master’s – led by new course director, and current chair of the European Finance Association, Rüdiger Fahlenbrach – reports a cohort of 59 students for its most recent iteration, up from 32 in the last guide. The course received a slightly higher number of applications, too, at 200, and extended more offers. Structurally, the MFE requires students to tackle a series of foundational, advanced and optional courses. They also conduct a short project and complete a six-month industry internship. Course director Fahlenbrach says that a new module – Financial Applications of Blockchains and Distributed Ledgers – has been added over the past year, covering topics such as decentralised cryptos, Byzantine fault tolerances, bitcoin platform mechanics and smart contracts. It’s proven popular with students, he adds, along with a perennial favourite, a machine learning module taught by EPFL’s department of computer science. Fahlenbrach says that, fortunately, his programme was spared the internship-related travails experienced by some other institutions represented in this year’s Quant Guide. “All students found internships, although several had a mostly remote experience in the spring. Placement was, surprisingly, not much affected,” he tells . “Our students write a master’s thesis concurrently with the six-month internship, and traditionally many students receive permanent job offers afterwards.” The MFE reports an employment rate of 90.6% among its graduates this year, albeit with 25% of data unavailable. Salaries have also increased, up to a highly competitive average base rate of $104,000.
No tuition, but enrolment fees of Sfr3,120 ($3,500)
76.25% male, 23.75% female
77.78% male, 22.22% male
The academic year started with 25% of courses ‘in presence’ (course live-streamed and recorded via Zoom, 1/3 of students in class and 2/3 of students watching the course on Zoom). All courses switched to 100% online on October 26, 2020, as per decree by local government.
Not yet fixed for fall 2020 semester. In spring semester of 2020, all exams were postponed and held on site in August.
Melbourne-based Monash University’s Master of Financial Mathematics has a new academic course director this year: senior lecturer in the school of mathematics Ivan Guo now heads up the variable-length programme. The previous director, Gregoire Loeper, took a position as a senior scientific adviser for BNP Paribas in January 2020. He remains a professor within Monash’s mathematics faculty. Like last year, the programme is taught in three phases: the first part consists of orientation studies; the second specialist studies; and the third is devoted to professional practice. Several changes have been made within the framework, however, says Oscar Tian, a senior lecturer in the school of mathematics. More practical electives have been added, he says, including programming classes in the R and Python languages. Other new modules focus on “machine learning techniques, fund management, treasury and trading”. The final phase of the programme has also been tweaked to incorporate a “mixed pathway”, enabling students to take some electives on top of their part-time internship or project. Many of the master’s students, Tian says, weren’t able to make it to Australia. Seventeen of the 23-person cohort are international, and he says that a large number are undertaking study without setting foot on campus. The current Covid-19 travel restrictions prohibit most prospective entrants from entering the country. A small list of exemptions includes Australian citizens, immediate family members and diplomats. “Due to the travel ban introduced by the government in February, most of our students are in their home countries,” says Tian, adding that remote examinations have so far been reasonably successful. While online exams are not ideal for financial mathematics, he adds, “most units have found a good balance between assessing the students’ understanding and maintaining integrity. Some units have even started to incorporate programming-based tasks where relevant”.
Quant Guide 2021: University of Illinois at Urbana-Champaign
Urbana and Champaign, Illinois, US
The University of Illinois at Urbana-Champaign’s Master of Science in Financial Engineering (MSFE) makes its second appearance in this year’s Quant Guide. The programme, directed by clinical professor of finance Morton Lane, takes place over 16 months and includes industry partner-sponsored practicum projects as a key element. Like many others, the course has seen a decline in student numbers this year – the latest cohort contains 22 students, against the last programme’s 50, the result of a large number of deferrals – it has made impressive gains in other areas. The average employment rate has increased since the MSFE’s last Quant Guide appearance, and graduate salaries have rocketed from an average of $87,500 to $102,343, putting the programme among the higher-earning segment of this year’s Quant Guide population. The MSFE is taught between two of the university’s colleges: the Gies College of Business; and the Grainger College of Engineering. Students, says Lane, have access to the career services teams in both colleges. He adds that the pandemic caused problems with recruiting for the current cohort, saying that staff saw a “drop-off in general inquiries from prospective employers”. Luckily, however, employers seeking particular expertise continued to court the programme. “[The drop in general interest] was offset by a pick-up in inquiries for specific skill sets – fortunately, ones that our students represent,” says Lane. Although remote teaching is not the programme’s preferred approach – Lane says that online classes are often more time-consuming than traditional ones – students have responded well to the coronavirus situation. The director adds that the MSFE has also introduced dedicated conversation sessions for students in China and the US, to foster the community atmosphere that cohorts expect to experience on campus.
Quant Guide 2021: Hong Kong University of Science and Technology
Hong Kong, China
Hong Kong University of Science and Technology’s (HKUST) MSc in Financial Mathematics (MAFM) has swollen its ranks of instructors over the past year, reporting an additional 10 individuals joining the teaching staff, up to a total of 20 – half of whom have an industry affiliation. Thanks to the ongoing impact of the coronavirus, teaching currently takes place in a mixed format, with some students attending sessions in person and others following along online via a simultaneous interactive livestream. Successful completion of the programme requires students to pass 36 credits of course material, 27 of which have to come from a dedicated – and lengthy – group of financial mathematics models. Students are also able to take up to nine credits of free electives, or opt to complete project tasks set by industry supervisors in fields such as statistics or machine learning. Regular modules on offer include classes in foundational topics, including stochastic calculus, quantitative risk management and portfolio optimisation, as well as newer, modish areas such as distributed ledger technology in financial applications and artificial intelligence. A dedicated module on financial markets in Hong Kong and China is also offered. While the course does host a small number of international students, the majority of the intake comes from institutions throughout Hong Kong and mainland China, like Sun Yat-sen University, Wuhan University, and the neighbouring .
The MSc in Mathematical Finance and Actuarial Science at the Technical University of Munich (TUM) has shrunk in some ways over the past year, probably at least in part due to the coronavirus. It received 100 applications for the current academic year versus the previous year’s 200 and enrolled 25 full-time students, compared with 40 previously. But that does not mean the university has scaled back its ambitions for the course. While most quant finance programmes have a single director, this master’s has three. Since the 2020 edition of the Quant Guide, programme leaders Rudi Zagst and Nina Gantert – chairs of mathematical finance and probability theory respectively – have been joined by Mathias Drton, a professor of mathematical statistics. Two new modules have also been incorporated into the four-term programme, taught in both English and German: a class in high-dimensional statistics and a class in fundamental mathematical statistics. A high proportion of the course’s graduates move on to further study, with 35% of students tackling PhD programmes or another master’s-level course after graduation. For those who enter the job market, TUM reports a 100% employment rate, with average starting salaries of $50,874. Aleksey Min, a mathematics professor, says teaching has been delivered largely online in the last 12 months, and some classes have proven particularly popular: discrete- and continuous-time finance; portfolio analysis; computational statistics; and quantitative risk management. Still, students regret the loss of on-site lectures and face-to-face discussions, he says. And, as have , the TUM programme has experienced some foul play in the new environment. Staff have identified several cases of cheating on take-home assessments, Min says: “Those students failed the corresponding exams.”
Quant Guide 2021: University of California, Los Angeles (Anderson School of Management)
Los Angeles, US
Despite the impact of the coronavirus on every aspect of academic life in 2020, UCLA Anderson’s Master of Financial Engineering (MFE) is in reliably strong shape. The course, led by professor of finance and faculty director Mikhail Chernov, ranks 13 in this year’s Quant Guide, helped along by a strong average graduate salary and employment rate. Over the past 12 months, average salaries have fallen very slightly – from $97,644 to $97,500 – but the programme’s average employment rate six months after graduation has risen, from 94% to 96%. The size of the intake has fallen somewhat this year, likely a result of a high number of deferrals – something many programmes have experienced. Last year, the programme reported hosting 81 full-time students: this year, it has 48. The MFE still received a high volume of applications – 724 – and extended 171 offers, 71 of which were accepted. The 15-month programme concludes with an applied finance project, conducted in partnership with an industry sponsor. Back in August, the MFE said traditional summer internship placements were proving challenging for students to secure. The result was a larger emphasis on the projects, as well as virtual internships with banks such as JP Morgan and Citi. The MFE reports that 100% of the internships that did go ahead ending up being conducted remotely, along with 100% of exams for the autumn quarter. “We have always recorded courses, and continue to do so for on-demand access,” says the MFE’s interim executive director, Sheila Benko. Earlier this year, UCLA’s plans for an entirely new financial engineering programme – in collaboration with China’s Peking University. Another consequence of the coronavirus, the plans have stalled – but the university has not given up on them entirely.
Ivo Welch: 15550 citations Avanidhar Subrahmanyam: 14603 citations Francis Longstaff: 8870 citations Peter Rossi: 6482 citations Carla Hayn: 3772 citations
71% male, 29% female
87% male, 13% female
100% remote instruction for the fall quarter of 2020. For the winter quarter of 2021, the aim is to continue providing primarily remote instruction, with a plan to offer 15–25% of courses in an in-person/hybrid format.
Quant Guide 2021: Imperial College Business School
The MSc Risk Management and Financial Engineering at Imperial Business School is among the most popular and selective of those featured in ’s Quant Guide. For the latest intake, the 12-month programme received 1,390 applications – among the highest – and enrolled 158 students. The MSc also expanded its team of teaching staff, adding five new instructors over the past year. Lara Cathcart, associate professor of finance, remains the programme’s academic director. Many participants in this year’s guide reported a drop in student numbers as a result of deferrals or travel restrictions. Imperial College Business School didn’t seem to have a problem on that front, with just one student fewer in the latest intake versus last year’s cohort. It also enrolled the same number of international students this year, 147. Currently, around 60% of the programme’s instruction is conducted remotely. The business school, like a number of other institutions featured in the guide, has adopted a hybrid teaching model, designed to accommodate both in-person classes and virtual remote learning. “We rotate the classes in small groups of 35, so that students all have some in-class and online teaching,” says Christopher Neill, assistant director for finance programmes. “We can schedule timetables to suit students’ time zones, although the vast majority have come to the UK.” Imperial also has its own contact tracing system in operation, Neill adds. If a student develops symptoms of coronavirus, they – and their bubble, if they live with fellow students – will be asked to self-isolate. In the case that an instructor needs to self-isolate, their programme material is delivered online.
Covid didn’t disrupt the University of Technology Sydney’s (UTS) Master of Quantitative Finance programme quite as much as it may have affected others. Despite its relatively small size — with an average class size of 20 students in compulsory modules — the programme attracts a high number of part-time students. The present cohort comprises 16 full-time students and 12 part-timers. The move to online teaching and pre-recorded lectures for much of 2020 did not faze students who are mixing study with work or other efforts, although there was mixed feedback about some aspects of the shift, according to programme director and senior lecturer in finance Nadima El-Hassan. “Students seem to really like the pre-recorded lectures: they give students a lot of flexibility in how and when they learn,” she says. However, some report that they “miss the interaction with academics and other students, especially in lab sessions”, she adds. Exams were also given as take-home or timed online tests. For the latest intake, applications increased slightly over the previous year – from 72 to 78 – and UTS extended 43 offers versus 41 for the prior intake. Contact hours, homework hours, and rates of employment and further study have all remained static, as have post-graduation salaries. In a slight shift in employment choices following the completion of the programme, there was an increase in the percentage of graduates entering banking jobs versus the previous year’s cohort.
The University of Amsterdam’s (UVA) Master’s in Stochastics and Financial Mathematics was one of the smaller programmes in last year’s Quant Guide. Its latest cohort, however, has ballooned in size by comparison, the new class comprising 25 students against the preceding 14. Throughout 2020, the course has been led by Peter Spreij, a professor in the faculty of science. For 2021, the programme will be overseen by Asma Khedher, from the same faculty. In tandem with student numbers, the faculty has also expanded: a group of new instructors has joined its ranks, including: Joris Mooij, a professor of mathematical statistics; Tim van Erven, an associate professor in UVA’s Korteweg-de Vries Institute for Mathematics, formerly of Leiden University; and Eni Musta, an assistant professor of statistics. “As everywhere, the main issue was that teaching had to take place online,” says Spreij of this year’s MSc. “[It was] much regretted by students, since it was harder to maintain contacts among them.” Despite teething troubles, both the programme and the student body have adapted to the new realities of remote learning: only one seminar in the programme’s autumn semester was conducted on location, with remote participation remaining an option. Student internships were also conducted remotely, adds Spreij. “Students filled in questionnaires at the end of the spring semester, and we are waiting to see the results,” he says. “But the informal indications are that students are, given the circumstances, in general satisfied with the adjustments made for teaching.” While the delivery of course content has been overhauled in light of Covid-19, the MSc’s structure remains unchanged. Students tackle compulsory classes, select one of three specialisations – financial mathematics, data analysis and statistics, and probability and decision-making – and undertake electives, which may be chosen from among modules in other specialisations or other master’s-level programmes altogether. New modules introduced this autumn, Spreij says, include classes on causality and wavelets.