Quant Guide 2020: Fordham University

Fordham University’s Master of Science in Quantitative Finance programme is taught at the Gabelli School of Business, with associate professor of finance and business economics Sudip Gupta as programme director. Students can choose to complete the programme in a minimum of 12 months and a maximum of two years, and the average candidate completes in around 18 months.

Of the rankings in this year’s guide, Fordham’s programme has one of the most gender-balanced student cohorts. Although men still make up the majority of the programme, 48% of its most recent class are women.

The Manhattan-based programme has introduced a range of new course content over the past year, according to Gupta. The additions include a “new project with limit order book data”, he says, as well as a new course on algorithmic trading with machine learning applications. Also on offer is a workshop where natural language processing techniques, such as latent Dirichlet allocation, recurrent neural networks and convolutional neural networks, are investigated. An advanced workshop in machine learning will also be available as a progression from the core machine learning course, as will an elective module focused on blockchain, where students create their own digital coin.

“We have placed multiple students in the data science divisions of top hedge funds this year,” says Gupta, “and we see growing demand in this sector.” Master’s students at Fordham are, like many other recent graduates, showing increasing interest in data science careers rather than traditional finance roles in trading, Gupta adds.

View this institution’s entry in the 2019 guide

View other universities and a guide to the metrics tables