克莱蒙研究大学

Offered jointly by the Institute of Mathematical Sciences and the Drucker School of Management, the Master of Science in Financial Engineering (MSFE) provides a flexible interdisciplinary curriculum that allows you to tailor your study to align it with your professional goals. Its hallmark: a close integration of management and mathematics.

The MSFE program provides you the skills to create and evaluate complex financial products to help you become a strategic leader in the field. You will draw on tools from applied math, statistics, and financial and economic theory while integrating managerial concepts and applications. Our program ranks among the top 30 financial engineering programs nationally and gives our graduates excellent preparation for careers in risk management, investment, banking, corporate finance, hedge funds, derivatives, and more.

PROGRAM HIGHLIGHTS

Flexible interdisciplinary curriculum, with a full- and part-time options, lets you tailor your study to align with your professional goals within quantitative finance.
Learn from research faculty and experienced practitioners with expertise ranging from risk management to financial technology (FinTech) and beyond.
Expand your market value by adding a concentration in data analytics or fintech, or by pursuing a dual degree in mathematics.
Financial engineering students may apply directly to the two-year dual MSFE/MS in Mathematics program.
Financial engineering students have the opportunity to participate in client-based projects through the Engineering & Computational Mathematics Clinic program.
Our MSFE program is STEM designated, allowing international graduates of the program to remain in the U.S. for 36 months after graduation and receive work-based training.
MSFE alumni go on to leadership roles in some of the most prominent financial firms and companies in the world, such as Goldman Sachs, Barclays, and AIG.

Areas of Concentration

Data Analytics
FinTech

Curriculum

The Financial Engineering Program at the Drucker School provides a flexible interdisciplinary curriculum. Forty units are required to complete the degree. Twelve of those units are elective courses, which you can choose from the options below.

Core Courses

Corporate Finance
Financial Derivatives
Introduction to Risk Management
Statistical Theory
Financial Engineering Practicum

Stochastic Processes
Mathematical Finance
Time Series Analysis
Quantitative Risk Management
Optimal Portfolio Theory (2 units)

Electives

FinTech
Financial Statement and Analysis
Financial Strategy & Valuation
Macroeconomics
Entrepreneurial Finance
Selected Topics in Finance: Fixed Income
Intro to C++
Numerical Analysis
Partial Differential Equations
Mathematical Modeling

Math Clinic (two-semester sequence)
Linear Statistical Models
Simulation
Numerical Methods for Finance
Data Mining
Discrete Mathematical Modeling
Bayesian Statistics
Statistical Learning
Mathematics of Machine Learning