Master in Financial Mathematics | metrics table at end of article
Less than three hours’ drive away from the US’s second-largest banking hub lies the city of Raleigh, the capital of North Carolina. It may lack Charlotte’s heavyweight banks, but it has another famous connection with finance – the city is home to North Carolina State University (NCSU) and its financial mathematics master’s programme.
The competitive 18-month course offers training in statistics, mathematical modelling, investment theory, derivatives pricing and programming, among other core and elective subjects.
According to alumnus Jeffrey High, it’s a quant programme as rigorous as anything the east coast has to offer.
“I’d heard about the programme for years,” says High, who completed his degree part-time while working at Captrust, an asset management firm. “Its competition, for me, was the Columbia-NYU-Princeton triumvirate. These were the ones I was looking at.”
Despite, at that point, eight years of professional experience in finance, two bachelor’s and a master’s degree in related subjects, he found the NCSU course a welcome challenge.
“The mathematical rigour was a on a different level. It worked symbiotically with what I was doing in my job. Being able to get into AI and genetic algorithms – I would not have been able to do that without the programme,” High says, explaining that he studied artificial intelligence and genetic algorithms as part of the NCSU master’s and was able to apply those skills in his job at Captrust.
But there is more to the course than a focus on mathematics.
“Our course is designed as an intercollegiate, interdisciplinary programme,” says programme director Tao Pang. “Graduates of quant programmes are often well-trained in quantitative skills, but they’re lacking in business skills. We encourage collaboration between departments and we’ve made the management school a part of the programme.”
The programme, taught by staff from the mathematics, statistics, computer science and economics departments, prioritises exposing students to the financial industry as quickly as possible. Applied projects sponsored by a range of firms and part-time internships are an important element, Pang says.
“This summer we had students at Morgan Stanley, Bank of America, KPMG and several software companies. [The programme] is only three semesters, so we focus on data-related skills – risk management and data analysis. We plan to offer courses on machine learning and Python in the next academic year.”
Students have also been working on projects arranged by Sageworks, provider of financial software and data, and First Citizens Bank, all focused on a new US accounting standard for loans – the Current Expected Credit Loss (CECL).
Pang points out another feature of the programme: openness to student feedback. He meets with several student “ambassadors” weekly to discuss how the course can be developed and improved.
“One told me many international students don’t get into school life very quickly,” he says. “They wanted a preparation workshop, so we added one to the programme this summer, just before the semester started. Now we provide training in math, statistics, programming skills and finance for incoming students.”
As well as enabling new arrivals to fill gaps in particular subjects, the workshop helps some international students get used to an English-language teaching environment, Pang adds.
And his emphasis on constantly improving the programme is bearing fruit.
“I’m now one of the industry people who comes back and collaborates with students for their projects,” says alumnus High. “There’s heavy CECL presence, heavy regulatory modelling. It’s been fantastic. I’m a little jealous of the students that are coming out of the programme now.”