Second Major in Financial Engineering
Financial engineering in a shared major between the McKelvey School of Engineering and Olin Business School. A second major in financial engineering is ideal for students who are interested in careers or graduate study in financial engineering, quantitative finance, or related fields. This program covers courses in engineering, computer science, and business. Students interested in this second major must have a 3.3 or higher grade point average; this includes the cumulative GPA, the Business GPA, and the Engineering GPA. The financial engineering major is offered to any undergraduate day division student as a second major option.
Financial Engineering Requirements
Total credits required: 30 required credits and 15 credits of prerequisite coursework
- Background Requirements: 15 credits
| Code | Title | Units |
|---|---|---|
| CSE 1301 | Introduction to Computer Science | 3 |
| DAT 1201 | Managerial Statistics II | 3 |
or ECON 3150 | Introduction to Econometrics | |
or ECON 4150 | Introduction to Econometrics With Writing | |
or ESE 3260 | Probability and Statistics for Engineering | |
or SDS 4010 | Probability | |
or SDS 4130 | Linear Statistical Models | |
| MATH 2130 | Calculus III | 3 |
| MATH 2500 | Differential Equations | 3 |
or ESE 2170 | Differential Equations and Dynamical Systems Modeling in Engineering | |
or MATH 3520 | Differential Equations and Dynamical Systems | |
| MATH 3300 | Matrix Algebra | 3 |
or ESE 2180 | Linear Algebra and Component Analysis | |
or MATH 4301 | Linear Algebra | |
| Total Units | 15 | |
Engineering Professional Requirements (15 credits)
- Engineering Professional Core Requirements: 6 credits minimum
| Code | Title | Units |
|---|---|---|
| ESE 4150 | Optimization | 3 |
| ESE 4170 | Introduction to Machine Learning and Pattern Classification | 3 |
or CSE 4107 | Introduction to Machine Learning | |
| ESE 4261 | Statistical Methods for Data Analysis With Applications to Financial Engineering | 3 |
| ESE 4270 | Financial Mathematics * ** | 3 |
- Engineering Electives:
| Code | Title | Units |
|---|---|---|
| CSE 2407 | Data Structures and Algorithms | 3 |
| ESE 4031 | Optimization for Engineered Planning, Decisions and Operations | 3 |
| ESE 5130 | Large-Scale Optimization for Data Science | 3 |
| ESE 5200 | Probability and Stochastic Processes | 3 |
Olin Professional Requirements (15 credits)
- Olin Professional Core Requirements: 9 credits
| Code | Title | Units |
|---|---|---|
| ACCT 2610 | Principles of Financial Accounting | 3 |
| FIN 3150 | Capital Markets and Financial Management | 3 |
| FIN 4410 | Investments | 3 |
| Total Units | 9 | |
- Olin Electives: 6 credits required
| Code | Title | Units |
|---|---|---|
| FIN 4370 | Advanced Derivative Securities | 3 |
| FIN 4506 | Financial Technology: Methods and Practice | 3 |
| FIN 4510 | Options, Futures and Derivative Securities * ** | 3 |
| FIN 5017 | Quantitative Risk Management | 3 |
| FIN 5018 | Topics in Quantitative Finance | 1.5 |
| FIN 5321 | Data Analysis for Investments | 1.5 |
| FIN 5390 | Mathematical Finance | 1.5 |
| FIN 5520 | Fixed Income Derivatives | 1.5 |
- *
ESE 4270 Financial Mathematics must be taken after FIN 3150 Capital Markets and Financial Management and can be used to satisfy the FIN 4510 Options, Futures and Derivative Securities prerequisite of Olin Elective courses.
- **
FIN 4510 Options, Futures and Derivative Securities, ESE 4270 Financial Mathematics, or both must be taken to complete the second major.