MSc in Computational Finance

MSCF is a sophisticated, rigorous course of instruction. Outstanding academic credentials are necessary for admission to the program. Applicants should hold an undergraduate degree in a technical discipline such as mathematics, computer science, engineering or economics. Successful applicants will have taken at least two full semesters of study in differential and integral calculus, the calibre of which is required of engineering, math or science majors (ordinary differential equations, linear algebra, and a calculus based probability course). Applicants should have strong academic performance in mathematics and statistics coursework.

Relevant professional experience is preferred but not required and Applicants must be fluent in a general purpose programming language such as C.

Over the fall and spring semester of the first year, students are taught traditional finance theories of equity and bond portfolio management, the stochastic calculus models on which derivative trading is based, computational methods including Monte Carlo simulation and finite difference approximations of partial differential equations, and statistical methodologies including regression and time series.

Also provided is a "Presentations" course which provides one-on-one assistance in helping students better communicate their ideas before their peers, and the Deutsche Trading Competition which uses CMU's FAST software to emulate a trading environment with cash prizes awarded to the top traders at a special reception at Deutsche Bank.

During the semester following the summer internship, students take courses in asset pricing, statistical arbitrage, risk management and dynamic asset management.

The program concludes with a sophisticated financial computing course, an algorithmic trading competition, and a case-based presentation course in financial engineering. In addition to VBA, Matlab and S+ packages, C++ is incorporated into the curriculum and students create software in several courses.

The Tepper School of Business at Carnegie Mellon, located in Pittsburgh, Pennsylvania, consistently ranks among the top business schools in the world. In 2007, the Wall Street Journal ranked the Tepper School #5 among the top MBA programs in the U.S., and our undergraduate program has been ranked a Top Ten business program by U.S. News & World Report for several consecutive years.

The school’s legacy is closely tied to their pioneering work in introducing management science to the marketplace and B-school arena. More than 50 years ago, the school’s leadership brought forth their vision of a better way to succeed in business.

Management science – the academic alternative to the case study method – has its roots in analytical decision making in complex, dynamic business environments. Its prevalence and popularity has had sweeping effects – today, nearly all leading B-schools include some form of the Carnegie Mellon  management science model in their curriculum.

A commitment to knowledge discovery via interdisciplinary collaboration is at the heart of Tepper School of Business' academic philosophy. As a decidedly small school housed within a decidedly small research university, they are a conservatory of innovation. The linkages across campus are numerous and an inherent part of the culture. Partnerships that would be considered unconventional at other schools are what we do best. Tepper students partner with students, professors and researchers in other schools and centers, such as engineering, robotics, biotechnology and life sciences, product design and computer science.