Curriculum

M.S. in Mathematical Finance Curriculum

The M.S. in Mathematical Finance curriculum requires at least  30 hours (10 graduate classes) of coursework. Here’s how that breaks down: 

  • 18 hours (6 courses) of required core coursework
  • 12 hours (4 courses) of concentration courses in either FinTech and Quantitative Finance, Risk Management or Financial Data Analytics
  • Final, comprehensive examination
Core Courses
  • Financial Economic Theory (required)
  • Cross-Section and Time-Series Econometrics (required)
  • Financial Econometrics (required)
  • Financial Elements of Derivatives (required)
  • Fixed Income Securities and Credit Risk (required)
  • Stochastic Calculus for Finance I (required)
Concentration Courses

FinTech and Quantitative Finance Concentration

  • Computational Methods for Asset Pricing
  • Advanced Methods in Mathematical Finance
  • Blockchain, Cryptocurrencies and Decentralized Finance
  • Statistical Learning with Big Data

Risk Management Concentration

  • Risk Management and Financial Institutions
  • Asset and Portfolio Management
  • Risk Management in Corporations
  • Quantitative Risk Management

Financial Data Analytics Concentration

  • Advanced Microeconometrics
  • Algorithms and Data Structures
  • Database Systems or Applied Databases
  • Statistical Learning with Big Data
Comprehensive Examination

You will be required to pass the Comprehensive Examination. The comp exam is the capstone experience for the program and covers three core courses: Financial Economic Theory; Fixed Income Securities and Credit Risk; and Cross-Section and Time-Series Econometrics.

Complete course descriptions, progression requirements and all program requirements can be found in the Graduate Catalog.