Quant Guide 2020: North Carolina State University
Raleigh, US
The Master’s in Financial Mathematics at North Carolina State University was a newcomer in the Risk.net quant guide and ranking last year; in this edition, it takes tenth spot. The public university owes its strong showing to a small class size, an improved average graduate employment rate in finance and the research power of its faculty, with the work of industry heavyweight statisticians David Dickey and Jim Wilson garnering tens of thousands of citations in the last four years.
On top of a group of mandatory modules – ranging from quant finance fundamentals like options pricing and statistical inference to stochastic techniques and computation – students pick from a number of elective classes. Electives are split into predesigned tracks, developed by the programme with graduate careers in mind. Candidates who aim for a career as a risk manager, for instance, can choose a less maths-heavy track, with modules on corporate finance and enterprise risk, for example.
The data science track includes classes in experimental statistics, data mining, linear models and regression, and statistical programming. And for those considering further study, the PhD preparation track involves classes in Bayesian inference, linear transformations and matrix theory, and functional analysis. Overall, the master’s takes 18 months to complete.
Programme director Tao Pang, professor of mathematics, says recent updates to the curriculum include new courses on machine learning and financial risk regulation. In particular, the master’s has continued its focus on current expected credit loss (CECL) – last year, the university hosted a workshop on US banking regulation and, more generally, credit risk attended by delegates from the Federal Reserve and the Office of the Comptroller of the Currency.
Management consultancies have stepped up their demand for quant hiring recently, Pang adds. He names McKinsey, EY and KPMG as recent hirers of graduates of the programme.
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