The Baruch College Financial Engineering MS Program is a professional Masters Program which graduates competitive, high-quality individuals who successfully pursue careers in quantitative finance.
The Master of Science in Financial Engineering (MFE) requires the completion of 36 credits, including 12 credits to be completed from required courses and 24 credits to be completed from elective courses. Students entering the program with exceptional mathematical or financial skills may be permitted to replace one or more of the required courses with additional electives.
The curriculum of the MFE Program is designed to provide students with the background required for modeling and solving problems that arise in the financial services industry across various markets and asset classes. All courses are offered in the evening to accommodate students with work commitments.
Program Learning Goals
Upon completion of the MS in Financial Engineering, students will be able to:
- Exhibit broad and deep knowledge of financial markets and instruments.
- Apply mathematical models to the study of financial instruments across markets.
- Demonstrate excellent presentation and communication skills.
- Display high proficiency in C++ and VBA programming for financial applications.
- Quantify and estimate the risk associated with financial instruments.
- Develop pricing tools that interface with financial data providers such as Bloomberg and Reuters.
- Implement numerical methods for pricing and hedging financial instruments in various financial markets.
Program Curriculum
Courses in Specialization (36 credits) Required Courses (12 credits) | ||
Financial Markets and Securities | 1.5 credits | |
Object Oriented Programming for Financial Applications | 1.5 credits | |
Numerical Methods for Finance I | 3 credits | |
Probability and Stochastic Processes for Finance I | 3 credits | |
Capstone Project and Presentation | 3 credits | |
Elective Courses (24 credits) Choose courses from the following courses: | ||
Big Data Technologies | 3 credits | |
Statistical Natural Language Processing | 1.5 credits | |
Advanced Data Analysis | 1.5 credits | |
Fundamentals of Trading | 1.5 credits | |
Statistics for Finance | 3 credits | |
Optimization Techniques in Finance | 1.5 credits | |
Market and Credit Risk Management | 3 credits | |
Elements of Structured Finance | 3 credits | |
Numerical Methods for Finance II | 3 credits | |
Asset Allocation and Portfolio Management | 3 credits | |
Probability and Stochastic Processes for Finance II | 3 credits | |
Volatility Filtering and Estimation | 1.5 credits | |
Model Review for Quantitative Models in Finance | 1.5 credits | |
Commodities and Futures Trading | 1.5 credits | |
Modeling and Market Making in Foreign Exchange | 1.5 credits | |
Time Series Analysis and Algorithmic Trading | 3 credits | |
Advanced Risk and Portfolio Management | 3 credits | |
Advanced Computational Methods in Finance | 3 credits effective spring 2022 course credit changes to: 1.5 credits | |
Current Topics in Data Science for Financial Engineering Applications | 1.5 credits | |
Interest Rate Models and Interest Rate Derivatives | 3 credits | |
The Volatility Surface | 3 credits | |
Credit Risk Models | 3 credits | |
Interest Rate and Credit Models | 3 credits | |
Interest Rate Models | 3 credits | |
Market Microstructure Models | 3 credits | |
Current Topics in Mathematical Finance | 3 credits | |
Fixed Income Risk Management | 1.5 credits | |
Structured Security Valuation in the Primary Market | 1.5 credits | |
Emerging Markets and Inflation Modeling | 1.5 credits | |
Blockchain Technologies in Finance | 1.5 credits | |
Data Science III: Deep Learning | 1.5 credits | |
Fintech for Quants | 1.5 credits | |
Introduction to Applied Financial Econometrics | 1.5 credits | |
Cryptocurrencies and Their Derivatives | 1.5 credits | |
Time Series Analysis | 1.5 credits | |
Machine Learning | 1.5 credits | |
Behavioral Finance | 1.5 credits | |
Systematic Trading | 1.5 credits | |
Data Science in Finance I: Big Data in Finance | 1.5 credits | |
Data Science in Finance II: Machine Learning | 1.5 credits | |
(Term I) Econometrics I | 3 credits | |
(Term II) Financial Econometrics | 3 credits | |
Financial Markets and Institutions | 3 credits | |
Futures and Forward Markets | 3 credits | |
Investment Analysis | 3 credits | |
International Financial Markets | 3 credits | |
Seminar in Finance | 3 credits | |
Advanced Investment Analysis | 3 credits | |
Options Markets | 3 credits | |
Modern Regression Analysis | 3 credits | |
Time Series: Forecasting and Statistical Modeling | 3 credits |