Quant Guide 2022: University of Waterloo

Waterloo, Ontario, Canada

 

 

A small, selective programme, the University of Waterloo’s Master of Quantitative Finance accepted just 18 students into its latest intake. The degree received 155 applications, and gave offers to just 36 hopefuls, for an acceptance rate of 23%. With 17 teaching staff on the master’s, students can expect plenty of contact time.

The programme retains the same line-up of instructors and range of modules as in the previous academic cycle, but new material has been added to existing classes. For example, the Finance 3 course now includes work on the Vix index, optimal trade execution and pegged currency markets.

Popular modules are classes on deep learning in finance and various machine learning-related electives.

Instructors on the programme include: Matthias Schonlau, who researches statistical machine learning; computer science and statistics professor Ali Ghodsi, who also leads the university’s data analytics lab; and associate professor of actuarial science and quantitative finance Ruodu Wang, who teaches classes in statistics, quantitative risk management and the mathematics of financial markets. The degree is led by professor of statistics and actuarial science Alexander Schied.

The master’s has a graduate employment rate of 84%, close to its figure for last year, although the number of students for whom employment data is unavailable has risen slightly. Most graduates still find employment in banking, with smaller numbers taking asset management and fintech positions.

View this institution’s entry in the 2021 guide

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