Master of Science in Financial Analytics (MFA)
The Master of Science in Financial Analytics program is designed for science, technology, engineering, and math (STEM) students who are pursuing careers in the financial industry. The program focuses on recent development in financial data science from fundamental data processing to machine learning, statistical modeling, and fintech. Program graduates are expected to be able to handle complex financial data, build advanced analytical models, deliver effective visualization product, and utilize cloud-based data-driven analytics technology.
The FA Masters' degree may be completed by taking the core courses and any 12 credits of elective courses. Alternately, students may choose the elective courses in one of the three possible concentrations detailed next.
Financial Analytics Curriculum
Required Core Courses
FE 541 | Applied Statistics with Applications in Finance | 3 |
FE 582 | Foundations of Financial Data Science | 2 |
FE 513 | Financial Lab: Practical Aspects of Database Design | 1 |
FE 535 | Introduction to Financial Risk Management | 3 |
FE 590 | Statistical Learning | 3 |
FE 542 | Time Series with Applications to Finance | 3 |
FA 800 | Project in Financial Analytics | 1-6 |
Electives
Students are required to complete 12 credits of elective courses. The elective courses may be any of the FA/FE course offerings or any course at Stevens with advisor approval. Students may also choose to use their elective courses to pursue one of the three specific tracks (concentrations) detailed below.
Advanced Risk Analytics Concentration
Advanced Risk Analytics Concentration Requirements
Students who pursue the Advanced Risk Analytics concentration are required to complete the following courses. The General Elective course is to be decided with the Advisor's help.
FE 635 | Financial Enterprise Risk Engineering | 3 |
FE 655 | Systemic Risk and Financial Regulation | 3 |
FA 636 | Advanced Risk Analytics | 3 |
| General Elective | 3 |
Data Science and Optimization Concentration
Data Science and Optimization Concentration Requirements
Students who pursue the Data Science and Optimization concentration are required to complete the following courses. "Or" indicates a choice between respective courses.
FE 550 | Data Visualization Application | 3 |
FA 631 | Investment, Portfolio Construction, and Trading Analytics | 3 |
FE 646 | Optimization Models and Methods in Finance | 3 |
| Or | |
MA 575 | Optimization Models in Quantitative Finance | 3 |
MA 630 | Advanced Optimization Methods | 3 |
| Or | |
MA 661 | Dynamic Programming and Reinforcement Learning | 3 |
| Or | |
MA 662 | Stochastic Programming | 3 |
FINTECH and Machine Learning Concentration
FINTECH and Machine Learning Requirements List
Students who pursue the FINTECH and Machine Learning concentration are required to complete the following courses. The General Elective course is to be decided with the Advisor's help.
FE 550 | Data Visualization Application | 3 |
FE 595 | Financial Technology | 3 |
FE 690 | Machine Learning in Finance | 3 |
| General Elective | 3 |