Quant Guide 2020: Princeton University

Princeton University’s Master in Finance tops Risk.net’s quant guide rankings for the second year in a row – the programme boasts a 100% employment rate in financial services for its graduates in the last four years, and an average basic compensation of $120,000. Based at the Bendheim Center for Finance, it is led by professor René Carmona.

The two-year, four-semester programme looks to keep pace with the changing demands of industry: besides the usual core and elective courses and a research project, Master of Finance students can earn a recently introduced machine learning certificate from Princeton’s Center for Statistics and Machine Learning. Requirements for the certificate include the completion of machine learning, statistics and probability courses, plus a graduate seminar that does not contribute credits towards the master’s degree itself.

Carmona says several new staff have joined the programme: Mete Soner, who lectures on stochastic control and financial mathematics; Matias Cattaneo, who teaches regression and time-series analysis; and Michael Junho Lee, a visiting lecturer in finance from the Federal Reserve Bank of New York. Financial engineering professor John Mulvey will be co-teaching an online course on Python and machine learning in asset management on e-learning platform Coursera.

Single-semester master’s projects in machine learning are also proving popular; most students, Carmona says, are choosing to complete such work as a part of the optional certificate. Besides that, Master of Finance candidates are showing interest in the computational finance, C++ and high-frequency markets modules.

View this institution’s entry in the 2019 guide

View other universities and a guide to the metrics tables