Concentration in quantitative finance

The Quantitative Finance concentration is a powerful combination of mathematical skills and a strategic understanding of financial business decision-making. Designed for students with a strong math background, the technical curriculum is ideal if your career goals include working in financial services or related industries. You can enhance your academic experience by engaging with the Wells Fargo Advisors Center for Finance and Accounting Research. The program also allows you the opportunity to work at an internship between your second and third semesters.

Location
St. Louis
Duration
18 months
Format
On campus
Start
Fall
Cost
$99,900

a professor writing a formula on a chalkboard

STEM designated

Our MS in Quantitative Finance has a STEM designation for its focus on science, technology, engineering and mathematics throughout the curriculum.

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Quantitative finance curriculum

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

Prerequisites

Successful applicants to the Quantitative Finance concentration 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. Some background in the applications of computing to quantitative problem-solving is especially valuable.

Students in the Build-A-Bear consulting team

Real-world consulting projects

MS finance students in the practicum consulted for Build-A-Bear, Neocova, a local startup fintech firm, and others.

Career prospects

Some career paths for this program include: Risk Manager, Capital Markets and Research Associate, Financial Engineer, Fund Manager.

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Olin’s program emphasizes the practical application of cutting-edge tools and technologies, such as machine learning, deep learning, Python, Tableau, Alteryx, Hadoop and Structured Query Language (SQL), to solve real-world financial problems. This approach ensures that students not only understand the theoretical aspects of finance but also gain proficiency in utilizing advanced software and methodologies for financial case analyses.