Mathematical Finance (M.A.S.)
The Master of Mathematical Finance program advances education in theoretical, computational, and business aspects of quantitative methodologies relevant to the financial industry to help students pursue careers in financial risk management.
Illinois Tech's Master of Mathematical Finance program provides a superior quantitative education to prepare students to pursue careers in quantitative analysis and financial engineering. Become immersed in the quantitative principles of valuation and hedging of financial securities.
The Master of Mathematical Finance program offers an ideal balance of theoretical knowledge and practical application. Learn from professors affiliated with the Department of Applied Mathematics and Stuart School of Business, as well as adjunct professors who are financial practitioners providing practical insight into fixed income modeling and practice, computational methods in quantitative finance, trading strategies, and more.
Chicago is a vibrant, global hub for the financial community. It is home to prominent financial exchanges as well as some of the nation’s major banks, hedge funds, investment firms, and insurance companies. Research and internship experiences, as well as future employment opportunities, are enriched by the resources available in Chicago.
Program Overview
The program strikes a balance of theoretical knowledge and practical application. Learn from applied math and business professors, as well as financial practitioners with insight into fixed income modeling and practice, computational methods, and trading strategies.
Career Opportunities
Master of Mathematical Finance alumni are employed by CME Group, Citigroup, Discover Financial Services, Envestnet, Goldman Sachs, Intercontinental Exchange, JPMorgan Chase & Co., Morgan Stanley, OCC, PrivateMetrics Group, and Quantitative Risk Management, Inc. (QRM).
- Quantitative trader
- Quantitative analyst
- Quantitative modeler
- Quantitative software developer
Admission requires a bachelor’s degree in a quantitative discipline such as mathematics, quantitative finance, engineering, or statistics with a minimum cumulative GPA of 3.0/4.0.
Applicants must have a background in undergraduate-level probability theory, multivariate calculus, and linear algebra. Background in ordinary differential equations will enhance the chance of admission to the program.
If required, TOEFL scores should be a minimum of 90/250 (internet-based/computer-based test score), or the IELTS score should be a minimum of 6.5.
A two-page professional statement of goals and objectives, and a curriculum vitae, must be submitted.
Two letters of recommendation are required, and at least one must be from academia.
An interview may also be required.
Typically, admitted students score at least 156 on the quantitative portion of the GRE and at least 3.0 on the analytical writing portion.
Additional Information
Featured Faculty
Igor Cialenco
Matthew Dixon
Fred J. Hickernell
Ruoting Gong
Sang Baum “Solomon” Kang
Andrei Lyashenko
Benjamin E. Van Vliet
John F. O. Bilson
