Quant Guide 2020: University of St Gallen

St Gallen, Switzerland

St Gallen
Photo: University of St Gallen, Hannes Thalmann

The University of St Gallen’s Master’s in Quantitative Economics and Finance is one of three Swiss-based programmes in this year’s quant guide. The cohort of students for the programme is intentionally small, last year totalling 24. They are outnumbered by a faculty of 35, a group of instructors drawn from across St Gallen departments including statistics, economics and mathematics.

The programme takes 18 months – split across three semesters – to complete. Students must study eight compulsory modules, which include classes in mathematics, statistics and data analytics. A large number of elective courses are on offer: there are currently more than 35 available, on top of which students are encouraged to take part in contextual studies courses to supplement the basic master’s qualification.

Executive director Romina De Martin says a new module has been added in the past year, entitled ‘digitisation and big data analytics’. It involves applications of databases in finance and economics. Machine learning topics, she says, have already been covered at St Gallen for some time; they are part of the core curriculum in econometrics.

De Martin cites the programme’s responsiveness to student demand as a key factor in staying up to date. A course that struggles to attract sufficient numbers is scrapped if there is “no other strategic reason” to continue with it, De Martin says. Conversely, new courses are often popular because students see value in sharpening skills that are of practical value in the modern job market.

View this institution’s entry in the 2019 guide

View other universities and a guide to the metrics tables

Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.

To access these options, along with all other subscription benefits, please contact info@risk.net or view our subscription options here: http://subscriptions.risk.net/subscribe

You are currently unable to copy this content. Please contact info@risk.net to find out more.

Most read articles loading...

You need to sign in to use this feature. If you don’t have a Risk.net account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here