MS in Quantitative Finance Curriculum

You can complete your MSFQ degree in just three semesters with a minimum of 39 credits of required courses and graduate-level electives.

Total credits: 39

Required: 34.5 credits

Electives: 4.5 credits including experiential learning course and programming elective requirement

Core coursework includes:

• Options & Futures
• Derivative Securities
• Advanced Derivative Securities
• Investment Theory
• Data Analysis for Investments
• Stochastic Foundations for Finance
• Data Analysis, Forecasting & Risk Analysis
• Mathematical Finance
• Fixed Income Securities
• Fixed Income Derivatives
• Introduction to Python & Data Science
• Quantitative Risk Management
• Professional Business Communication

Electives include, but are not limited to:

• Machine Learning Tools for Prediction of Business Outcomes
• Database Design & SQL
• Big Data & Cloud Computing
• Introduction to Artificial Intelligence
• Data Mining
• Data Structures & Algorithms

Required experiential course options (choose one):

• Internship, Business and Application
• Applied Problem Solving for Organizations
• CFAR Practicum

Program Prerequisites

Successful applicants to the Quantitative Finance program will demonstrate outstanding aptitude for advanced quantitative finance materials and a passion for the quantitative aspects of problem-solving. Students who have majored in mathematics, computer science, quantitative economics, engineering, physics and statistics are especially encouraged to apply to the Quantitative Finance program. Some background in the applications of computing to quantitative problem-solving is especially valuable.