Demand for people who can apply mathematical skills in business and financial environments is growing rapidly, but a typical undergraduate mathematics degree may not adequately prepare a student to work effectively in a business environment. The University of Connecticut’s Professional Master’s in Applied Financial Mathematics prepares a graduate for work in an analytic capacity across a wide spectrum of the financial services industry – investment banks, private equity, hedge funds, mutual funds, consulting firms, investment firms, insurance companies, commercial banks, brokerage houses and other corporations. The program emphasizes finance, investing, and risk-management together with rigorous mathematical modeling and analytical techniques applied to problem-solving in those areas and communications skills required to be effective in a corporate environment.
Students do well in this program if they enter with a high GPA bachelor’s degree in mathematics, statistics, physics, engineering, quantitative economics, or other related fields and want a career applying their already strong mathematics skills and knowledge to the understanding and solution of problems involving finance, investing, and risk. No prior knowledge of business, finance or investing is required but the mathematics background is essential. We expect applicants to have completed undergraduate coursework in differential calculus, integral calculus, multivariable calculus, differential equations, linear algebra and mathematical probability/statistics (taught in a calculus framework). If one of these is missing it can be made up upon enrollment, but usually an applicant’s background should be missing no more than one of these.
In addition to the Graduate School requirements for admission, we want to see three recommendations and it is best if they are from mathematics instructors. GRE quantitative section scores for those we admit average at about the 95th percentile, and rarely fall below the 90th percentile. Undergraduate GPAs for those we admit average about 3.5/4.0 for quantitative coursework.
For international student admission, TOEFL scores of 55 or more in the total of the Reading and Listening scores are preferred; teaching assistantship, when offered, requires either 28 on the Speaking score, or 23-27 plus passing UConn’s micro-teaching test.
For the admissions process see Admission. In the online application, apply for M.S. in Applied Financial Mathematics.
See M.S. in Financial Mathematics – Actuarial Science for the alternative of choosing an actuarial science concentration within the Applied Financial Mathematics degree.
The M.S. in Applied Financial Mathematics qualifies as a STEM (Science, Technology, Engineering, Mathematics) degree with the federal government. Foreign students who earn the degree may be eligible for the STEM extension to the OPT (Optional Practical Training) program, allowing a total of 29 months of post-graduation employment in the U.S.
Overview of Degree Requirements
(Students who entered prior to 2016 can see their advisor to work out details of how their past coursework aligns with current requirements.)
To graduate with an M.S. in Applied Financial Mathematics, a student must satisfy all of the following requirements:
- At least 30 credits, including all of the required courses.
- Graduate Field Study Internship.
- An Exit Project approved by the student’s advisor.
(Number of credits, and semester, F or S, the course is usually offered in.)
Students must complete each of the following Core courses:
- Math 5620 Financial Math I: Theory of Interest (3 F S)
- Math 5621 Financial Math II: Theory of Corporate Finance (4 F S)
- Math 5660 Advanced Financial Math: Stochastic Finance (3 F S)
- Stat 5361 Statistical Computing: Large Financial Models (3 S) — prior statistics knowledge required
Students must complete at least two of the following Finance Focus courses:
- Acct 5327: Financial Statement Analysis (3 F S) – prior accounting knowledge required
- Fnce 5202: Investments and Securities Analysis (3)
- Fnce 5504: Options, Futures and Risk Management (3)
- Fnce 5512: Fixed Income Instruments (3)
- Fnce 5532: Real Estate Investment and Portfolio Management (3)
- Fnce 5533: Real Estate Capital Markets (3)
- Fnce 6201: Introduction to Finance Theory and Evidence (3 F) – consult advisor first
- Fnce 6203: Theory of Financial Markets and Valuation (3 F) – consult advisor first
- Math 5800-005: Yield Curve Models (3 S)
Students must complete at least 6 credits from among the following Practicum courses, including at least 1 credit for internship(s):
- Math 5800-018 Fundamentals of Financial Math (3 F) – this is a required course that must be taken in the student’s first Fall semester
- Math 5850 Graduate Field Study Internship (1-3 F S Summer) – described further below; may be repeated for credit up to 6 credits; internship credit also can be earned through participation in School of Business Experiential Learning Collaborative projects, which will be recorded under a BADM or OPIM course number assigned to the project.
- Grad 5900-001 Professional Communications (1 F S)
- Math 5800-005: Yield Curve Models (3 S)
- Math 5800-030: Financial Programming and Modeling (3 F S)
- Math 5800-031: Financial Data Mining with Big Data (3 F S)
Additional courses may be selected from the list of finance courses above, and/or from the following list (no more than 6 credits of undergraduate courses 3000+ can be credited towards the MS degree):
- Acct 5121: Financial Accounting and Reporting (3 F S) – strongly encouraged, but not required
- Math 3160: Probability (3 F S)
- Math 3170: Elementary Stochastic Processes (3 S)
- Stat 3965: Elementary Stochastic Processes (3 F) – equivalent to Math 3170
- Math 5637: Risk Theory (3 F)
- Math 5110: Introduction to Modern Analysis (3 F)
- Math 5111: Measure and Integration (3 S) – consult advisor first
- Math 5160: Probability and Stochastic Processes I (3 F) – consult advisor first
- Math 5161: Probability and Stochastic Processes II (3 S) – with permission, can replace Math 5660
- Math 5800-030 Financial Programming and Modeling (3 F S)
- Math 5800-031 Financial Data Mining with Big Data (3 F S)
- Stat 5585: Mathematical Statistics I (3 F)
- Stat 5685: Mathematical Statistics II (3 S)
- Stat 5505: Applied Statistics I (3 F)
- Stat 5605: Applied Statistics II (3 S)
- Stat 5315: Analysis of Experiments (3 F S)
- Stat 5725 Linear Statistical Models (3)
- Stat 5825: Applied Time Series (3 F S)
- Econ 5201: Microeconomics (3 F S)
- Econ 5202: Macroeconomics (3 F S)
- Econ 5301: Mathematical Economics (3 F)
- Econ 5311: Econometrics I (3 F S)
- Fnce 5151: Introduction to Economic Markets (3 F S)
Please also consult the Hartford Campus offerings for many of the above courses. Enrollment in the Hartford Campus can be made only by arrangement with the Applied Financial Mathematics program director.
A practical internship, usually during the summer between the 2nd the 3rd semester of a student’s program, helps to assure a pragmatic dimension to the student’s development. 1 to 3 credits are earned, registering in Math 5850 (see above,) and more than one internship may be used (along with other options, as above) to meet the 6 credit Practicum requirement. With a wide range of financial firms in Connecticut (the leading U.S. insurance center and unofficial headquarters of the U.S. hedge fund industry) and in nearby New York and Boston, many students find attractive, well-paid internships, especially when the business is in a favorable point of its cycle. While we help students where possible to secure a paid internship, we cannot guarantee one because the business can be cyclical. Securing such an internship is the student’s own responsibility. When necessary we enable students to meet the internship requirement by offering an unpaid internship assisting the research projects of faculty members who have extensive working experience in financial institutions. Another option to meet the internship requirement is to apply and be selected for one of the School of Business Experiential Learning Collaborative projects.
The final requirement for the M.S. degree is passing performance on an innovative exit project that will require an independent, scholarly, yet pragmatic piece of work that may take many forms. A comprehensive literature review on an appropriate topic could be performed. Alternatively, the student could formulate a solution to a problem encountered during an internship or in advance coursework. It might be appropriate for the student to write a mock journal article or technical report on such work. Some students create complex financial simulation models and evaluate their results. Some students may already have positions secured prior to completion of the exit project. In these cases the prospective employer could help to determine the type of exercise that would be most beneficial to the student’s preparation for employment. The student and the advisor will agree upon the nature and time frame for completion of the exit project. The Advisory Committee will evaluate the project under University guidelines. It is the intent of this innovative exit project to reinforce the discipline-specific competency and to provide an evaluation tool for relevant problem-solving abilities and writing skills.