Quant Guide 2019: University of St Gallen

St Gallen, Switzerland

St Gallen
Photo: University of St Gallen, Hannes Thalmann

Master’s in Quantitative Economics and Finance | metrics table at end of article

The master’s in quantitative economics and finance at St Gallen is a hybrid programme that aims to produce graduates as confident tackling macroeconomic problems as the familiar challenges of quantitative finance.

The course structure reflects this composite approach. Following core classes in economics, finance and mathematics, students can pursue topics of interest across a range of electives including quantitative risk management, computational finance and data analytics.

Several classes include work on financial regulation, including the Basel III reforms which are set to reshape the way banks model their risks – a topic of particular relevance to budding quants.

Programme director Christian Keuschnigg says: “The corporate finance and banking theory classes discuss the rationale and implications of capital standards for banks, and that involves Basel and its effects. That’s taught on top of incentive theory and contact theory. We also have special courses in central banking which cover regulatory issues.”

The degree itself is split across three semesters, although for students who prefer a slower pace, the programme can be stretched across eight semesters. Students must complete modules totalling 90 credits.

There is a strong element of technically demanding maths: the core modules include examined classes in mathematics (introductory and advanced), financial theory, stochastic calculus applied to finance and probability and statistics.

Moving off-piste, students take between 12 and 18 course credits in “contextual studies” classes, which cover anything from traditional business skills like negotiation and team leadership to ethics, cultural studies, programming languages – even formal rhetoric.

Students must also complete a master’s thesis, which is worth 18 credits. Internships are optional. “Students can acquire practice credits which are voluntary,” Keuschnigg says. “They can choose to go to a company in the financial sector and complete an internship. If they come up with written work that we can examine and reasonably connect to the degree studies, they can get credits for it. They might develop a master’s thesis out it if, for example.”

Keuschnigg is updating the structure of the St Gallen programme, with classes in big data and machine learning – previously electives – set to become compulsory in 2019. It’s a necessary change, says Keuschnigg. 

“Technological progress means that banks, governments and the private sectors – whole economies – will transform. And there are going to be skills shortages. So we’ve got to include these statistical methods as a central part of our training.”

Given the broad nature of the master’s, St Gallen’s graduates may find work in a wider range of financial fields than alumni of more straightforward programmes in quant finance or financial mathematics. Staying on in academia is also popular.

“A third of our graduates continue with PhD programmes,” says Keuschnigg. “About a third go into the financial sector, and another third go to consulting firms or big private sector companies. Some of them go to central banks. The training they get makes them versatile, so you find them all over the place.”

St Gallen’s programme is, compared to some of its counterparts, a small one, with just 30 students in the latest cohort. It also has a high acceptance rate – 60% for the same year. It’s going to stay that way, says Keuschnigg.

“Our pool of applicants isn’t big. We do, of course, screen them, but the programme functions well on self-selection. The students we attract know that it’s a tough programme. It’s small, and it’s intended to be small.”

For one recent graduate, the economic study on the course has proved valuable. “[The master’s] provided me with a comprehensive econometric toolbox,” says Andrina Niederberger, who completed the programme in 2016 and has worked for Credit Suisse since, most recently as a treasury ALM specialist. “I’ve been lucky enough to take partial leads in some interesting global and cross-divisional projects, namely the global project on interest rate risk in the banking book.”

“Our programme is perceived by students to be technically difficult, which it is,” says Keuschnigg. “So our job is to convince students that, yes, it’s a big investment, it’s difficult. But that’s what the future demands.”

Click here for links to the other universities and an explanation of how to read the metrics tables

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