Quant Guide 2022: Carnegie Mellon University

Pittsburgh and New York City, US

Photo: Carnegie Mellon University

 

 

Carnegie Mellon University’s Master of Science in Computational Finance has seen changes in its delivery of teaching and the make-up of its student body over the past year.

The amount of teaching delivered by visiting staff has more than doubled, from 42 contact hours in last year’s Risk.net Quant Finance Master’s Guide, to 89 this year. Overall contact hours have declined slightly, from 532 to 494. And the gender split among the student body has become more balanced, with 56% men and 44% women this year, compared with 71% men and 29% women last year.

Average graduate salaries and programme fees have remained largely the same. The employment rate has climbed from 99% to 100%, with employment routes similar to those reported in last year’s guide.

Instructors on the three-semester course are drawn from the faculties of statistics, information technology, mathematics, and finance, and include programme co-founders Steven Shreve and John Lehoczky, who teach asset pricing and stochastic processes respectively. Other teaching staff include: adjunct instructors Leif Andersen, previous winner of Risk.net’s Quant of the Year award, who also teaches at New York University’s Courant Institute; and Nick Psaris, a managing director at Bank of America.

In the first year, students tackle modules such as: financial computing and data science; fixed income fundamentals; and a broad investment course, which includes instruction in quantitative portfolio management, risk measurement, portfolio optimisation and price discovery.

Other first-year courses include two machine learning modules and classes in business communication, with the latter covering negotiation, persuasive writing and leadership. Following a summer internship, second-year modules include electives in asset management, advanced derivatives models and projects focused on machine learning.

View this institution’s entry in the 2021 guide

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