Operations Research: Financial Engineering (BSOR:FE)
Setting the Benchmark in Quantitative Finance
The Financial Engineering concentration within the Operations Research program provides training in the application of engineering methodologies and quantitative methods to finance. Financial Engineering integrates financial theory with economics, methods of engineering, tools of mathematics, and practice of programming.
Electives in Financial Engineering
The undergraduate OR:FE concentration requires a total of nine (9) points of electives equivalent to three (3) courses.
- ORCA 2500: Foundations of Data Science (only if taken by the end of sophomore year)
- APMA W4300: Computational Math: Intro to Numerical Methods
- CIEN E4138: Real Estate Finance for Construction Management
- CSOR W4231: Analysis of Algorithms
- ECON V3025: Financial Economics
- ECON W4280: Corporate Finance
- IEOR E4212: Data Analytics and Machine Learning
- IEOR E4525: Machine Learning for OR & FE
- IEOR E4526: Analytics on the Cloud
- IEOR E4601: Dynamic Pricing and Revenue Management
- IEOR E4602: Quantitative Risk Management
- IEOR E4650: Business Analytics
- IEOR E4709: Statistical Analysis and Time Series (Seniors Only)
- IEOR E4711: Global Capital Markets or FINC B6302: Capital Markets and Investments (students may not take both)
- IEOR E4718: Beyond Black-Scholes: The Implied Volatility Smile (Seniors Only)
- IEOR E4720 - E4729: Topics in Quantitative Finance Series
- IEOR E4721: AI Applications in Finance
- IEOR E4731: Credit Risk Modeling and Derivatives (Seniors Only)
- IEOR E4733: Algorithmic Trading
- IEOR E4742: Deep Learning for OR & FE
- ORCS E4200: Data Driven Decision Modeling
- ORCS E4529: Reinforcement Learning
- MATH V2030: Ordinary Differential Equations
- MATH W4061: Intro to Modern Analysis, I
- STAT W4440: Linear Regression and Time Series Methods
If there are other electives of interest, the student should bring the course description to his or her faculty advisor for review.