M.S. in Applied Financial Mathematics

Overview

Introduction

UConn's M.S. in Applied Financial Mathematics (MSAFM) prepares ambitious graduates for high-impact roles across the financial services industry—from Wall Street investment banks and hedge funds to insurance leaders, consulting firms, and global corporations.

Our program combines cutting-edge finance and risk management with rigorous mathematical modeling and data-driven problem-solving, empowering graduates to tackle complex financial challenges with confidence. Along the way, students sharpen their communication and business skills, ensuring they can translate technical expertise into strategic decisions.

Who thrives here? Students with strong quantitative backgrounds—typically in mathematics, statistics, physics, engineering, or quantitative economics—who want to apply their analytical strengths to finance, investing, and risk management. No prior business or finance knowledge is required.

Admissions Snapshot: Applicants should have completed undergraduate coursework in calculus (single & multivariable), differential equations, linear algebra, and probability/statistics (calculus-based). A gap in one area can be made up after enrollment.

The program is STEM-designated, making international graduates eligible for the STEM OPT extension (with qualifying employers). Students may also pursue a Concentration in Actuarial Science within the degree.

Non-Specialized Concentration

To graduate with an M.S. in Applied Financial Mathematics (without the Concentration in Actuarial Science), students must complete the following:

  • 30 credits (including all required courses)
  • A Graduate Field Study Internship
  • An Exit Project, approved by their faculty advisor

Concentration in Actuarial Science

To graduate with an M.S. in Applied Financial Mathematics with Concentration in Actuarial Science, students must complete the following:

  • 30 credits (including all required courses)
  • A Graduate Field Study Internship
  • An Exit Project, approved by their faculty advisor, or passing grades on two professional exams of the Society of Actuaris (SOA).

Courses & Other Degree Components

Courses for Non-Specialized Concentration

Requires Courses

All of following:

  • Math 5600 Fundamentals of Financial Math
  • Math 5620 Financial Math I: Theory of Interest
  • Math 5650 Financial Math II: Theory of Corporate Finance
  • Math 5660 Advanced Financial Math: Stochastic Finance
  • Math 5637 Statistics for Actuarial Modeling or Stat 5361/Statistical Computing: Large Financial Models (prior statistics knowledge required)

Finance Focus Courses

At least two from the following:

  • Acct 5327: Financial Statement Analysis (prior accounting knowledge required)
  • Fnce 5202: Investments and Securities Analysis
  • Fnce 5504: Options, Futures and Risk Management
  • Fnce 5512: Fixed Income Instruments
  • Fnce 5532: Real Estate Investment and Portfolio Management
  • Fnce 5533: Real Estate Capital Markets
  • Fnce 6201: Introduction to Finance Theory and Evidence (consult advisor first)
  • Fnce 6203: Theory of Financial Markets and Valuation (consult advisor first)
  • Math 5661: Yield Curve Models

Practicum Courses

At least 6 credits from the following, including at least 1 credit for internship(s):

  • Math 5600: Fundamentals of Financial Math (required in first Fall semester)
  • Math 5850: Graduate Field Study Internship (described further below; may be repeated for 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)
  • MCB 5900: Professional Writing and Communication Skills
  • Math 5661: Yield Curve Models
  • Math 5670: Financial Programming and Modeling
  • Math 5671: Financial Data Mining with Big Data

Elective Courses

Additional courses, either from the Finance Focus list above, and/or from the following (no more than 6 credits from undergraduate courses):

  • Acct 5121: Financial Accounting and Reporting (strongly encouraged)
  • Math 3160: Probability
  • Math 3170: Elementary Stochastic Processes
  • Math 5637: Statistics for Actuarial Modeling
  • Math 5110: Introduction to Modern Analysis
  • Math 5111: Measure and Integration (consult advisor first)
  • Math 5160: Probability and Stochastic Processes I (consult advisor first)
  • Math 5161: Probability and Stochastic Processes II (with permission, can replace Math 5660)
  • Math 5661: Yield Curve Models
  • Math 5670: Financial Programming and Modeling
  • Math 5671: Financial Data Mining with Big Data
  • Stat 3965: Elementary Stochastic Processes (equivalent to Math 3170)
  • Stat 5585: Mathematical Statistics I
  • Stat 5685: Mathematical Statistics II
  • Stat 5505: Applied Statistics I
  • Stat 5605: Applied Statistics II
  • Stat 5315: Analysis of Experiments
  • Stat 5725 Linear Statistical Models
  • Stat 5825: Applied Time Series
  • Econ 5201: Microeconomics
  • Econ 5202: Macroeconomics
  • Econ 5301: Mathematical Economics
  • Econ 5311: Econometrics I
  • Fnce 5151: Introduction to Economic Markets

Courses for Actuarial Science Concentration

Requires Courses

All of following:

  • Math 5600 Fundamentals of Financial Math
  • Math 5620 Financial Math I: Theory of Interest
  • Math 5650 Financial Math II: Theory of Corporate Finance
  • Math 5660 Advanced Financial Math: Stochastic Finance
  • Math 5637 Statistics for Actuarial Modeling or Stat 5361/Statistical Computing: Large Financial Models (prior statistics knowledge required)

Finance Focus Courses

At least one of the following:

  • Acct 5327: Financial Statement Analysis (prior accounting knowledge required)
  • Fnce 5202: Investments and Securities Analysis
  • Fnce 5504: Options, Futures and Risk Management
  • Fnce 5512: Fixed Income Instruments
  • Fnce 5532: Real Estate Investment and Portfolio Management
  • Fnce 5533: Real Estate Capital Markets
  • Fnce 6201: Introduction to Finance Theory and Evidence (consult advisor first)
  • Fnce 6203: Theory of Financial Markets and Valuation (consult advisor first)
  • Math 5661: Yield Curve Models

Practicum Courses

At least 6 credits from the following, including at least 1 credit for internship(s):

  • Math 5600: Fundamentals of Financial Math (required in first Fall semester)
  • Math 5850: Graduate Field Study Internship (described further below; may be repeated for 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)
  • MCB 5900: Professional Writing and Communication Skills
  • Math 5661: Yield Curve Models
  • Math 5670: Financial Programming and Modeling
  • Math 5671: Financial Data Mining with Big Data

Elective Courses

Additional courses, either from the Finance Focus list above, and/or from the following (no more than 6 credits from undergraduate courses):

  • Acct 5121: Financial Accounting and Reporting (strongly encouraged)
  • Math 3160: Probability
  • Math 3170: Elementary Stochastic Processes
  • Math 5637: Statistics for Actuarial Modeling
  • Math 5110: Introduction to Modern Analysis
  • Math 5111: Measure and Integration (consult advisor first)
  • Math 5160: Probability and Stochastic Processes I (consult advisor first)
  • Math 5161: Probability and Stochastic Processes II (with permission, can replace Math 5660)
  • Math 5661: Yield Curve Models
  • Math 5670: Financial Programming and Modeling
  • Math 5671: Financial Data Mining with Big Data
  • Stat 3965: Elementary Stochastic Processes (equivalent to Math 3170)
  • Stat 5585: Mathematical Statistics I
  • Stat 5685: Mathematical Statistics II
  • Stat 5505: Applied Statistics I
  • Stat 5605: Applied Statistics II
  • Stat 5315: Analysis of Experiments
  • Stat 5725 Linear Statistical Models
  • Stat 5825: Applied Time Series
  • Econ 5201: Microeconomics
  • Econ 5202: Macroeconomics
  • Econ 5301: Mathematical Economics
  • Econ 5311: Econometrics I
  • Fnce 5151: Introduction to Economic Markets

Internship

A key component of the program is a practical internship, typically completed during the summer between a student’s 2nd and 3rd semesters. This experience ensures a strong real-world dimension to professional development. Students earn 1–3 credits by registering for Math 5850, and multiple internships may be combined (along with other approved options) to fulfill the 6-credit Practicum requirement.

With Connecticut serving as the nation’s leading insurance hub—and an unofficial headquarters for the hedge fund industry—plus the proximity of New York and Boston, students have access to a wide range of opportunities. Many secure well-paid, highly attractive internships, particularly when the business cycle is favorable.

While the program provides support in helping students obtain internships, placements cannot be guaranteed due to the cyclical nature of the industry. Ultimately, it is the student’s responsibility to secure an internship. When needed, students can meet the requirement through an unpaid internship, assisting faculty members with research projects. Many faculty bring deep professional experience from financial institutions.

Another pathway to fulfilling the requirement is to apply for and be selected into one of the School of Business Experiential Learning Collaborative projects.

Exit Project

The final requirement for the M.S. degree is successful completion of an innovative exit project, designed to demonstrate independent, scholarly, and pragmatic work. The project can take many forms:

  • a comprehensive literature review on a relevant topic,
  • a solution to a problem encountered during an internship or coursework,
  • a mock journal article or technical report,
  • or the creation and evaluation of a complex financial simulation model.

For students who secure employment before completing the program, a prospective employer may help shape the project to ensure maximum career relevance. In every case, the student and advisor jointly determine the project’s scope and timeline, and the advisory committee evaluates it under University guidelines.

This exit project reinforces discipline-specific expertise while providing a rigorous assessment of problem-solving abilities and professional writing skills.

As an alternative, students may satisfy the requirement by earning passing grades on two professional examinations of the Society of Actuaries (SOA).