Quantcast Master’s Series: Walter Farkas, ETH – University of Zurich

Swiss planning, large joint faculty and public presentations shape the programme

In the final episode of this year’s Quantcast Master’s Series – part of the Tomorrow’s Quants project – we welcome Walter Farkas, director of the Master’s in Quantitative Finance at ETH Zurich, University of Zurich.

The programme, like most of its peers, has strong connections with the industry, but the way it incorporates these connections into the curriculum is unique; 18 lecturers with industry affiliations complement a group of 48 internal professors, some from ETH Zurich and some from the University of Zurich. In all, the programme’s 66 teaching staff teach just 53 students.

The details of this course, and the specifications of other leading quant finance master’s programmes, will be set out in Risk.net’s forthcoming Quant Finance Master’s Guide 2026.

“Having part-time lecturers from banks, insurance companies, consulting companies, helps us really to bring market insights in the classroom,” says Farkas. “What we teach is not just theoretically sound, but highly relevant in practice.”

It also poses logistical challenges, as many lecturers have full-time jobs at their financial institutions. “One of the Swiss characteristics is good planning. We plan the schedule well in advance, so most of the faculty who are really involved in the coming academic year can balance both professional and teaching roles,” says Farkas. So, he and his colleagues already know their schedules up to December 26.

Quantcast – a Risk.net Cutting Edge podcast · Walter Farkas Risk Quantcast MS

 

The programme is jointly organised by ETH Zurich, a polytechnic school, and the University of Zurich. The idea of merging the two scientific resources into one programme came 20 years ago, when the programme was introduced to satisfy market demand for graduates with theoretical and scientific knowledge, as well as exposure to economic and financial concepts.

Niche derivatives and exotic options are still taught, but more concisely, to make space in the curriculum for newer subjects like machine learning, computational finance and data science.

Internships are strongly encouraged but not mandatory. Other initiatives within the programme also put students in front of financial institutions. An unusual example of this is the presentation of students’ theses at a public event, to which representatives from financial institutions and recruiters are invited. It’s a decisive moment in the programme, in which not only knowledge is judged, but the ability to work under stress and to explain and present to an audience – skills the Risk.net Tomorrow’s Quants survey identifies as key.

The selection procedure for candidates is particularly thorough. Farkas and two colleagues independently review each of the applicants – 500 applied for the most recent edition of the programme. “We do that without any AI!” jokes Farkas, although a different type of intelligence also plays a role. “For each candidate, we have an opinion from an alumnus,” he says, which helps the trio of professors reach their decision.

To hear the full interview, listen in the player above, or download. Future podcasts in our Quantcast series will be uploaded to Risk.net. You can also visit the main page here to access all tracks, or go to Spotify, Amazon Music or the iTunes store to listen and subscribe.

Find all the Tomorrow’s Quants content here.