Second Major in Financial Engineering (ESE)
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 classes in engineering, computer science, and business. Students interested in the second major must have completed the background courses or being in the process of completing them and have a 3.3 or higher grade point average to pursue this second major. The grade point average includes the cumulative GPA, the Business GPA, and the Engineering GPA. Students must complete 30 total units (15 Engineering units and 15 Olin Business units).
| Code | Title | Units |
|---|---|---|
| Background Coursework | 15 | |
| CSE 1301 | Introduction to Computer Science | 3 |
| ESE 3260 | Probability and Statistics for Engineering | 3 |
or SDS 3200 | Elementary to Intermediate Statistics and Data Analysis | |
or DAT 1201 | Managerial Statistics II | |
or ECON 3150 | Introduction to Econometrics | |
or ECON 4150 | Introduction to Econometrics With Writing | |
or SDS 4130 | Linear Statistical Models | |
or SDS 4010 | Probability | |
| 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 2130 | Calculus III | 3 |
| MATH 3300 | Matrix Algebra | 3 |
or ESE 2180 | Linear Algebra and Component Analysis | |
or MATH 4301 | Linear Algebra | |
Students must complete 15 Engineering units. At least 6 of those units must be from the Engineering Core Courses:
| Code | Title | Units |
|---|---|---|
| Engineering Core Courses | ||
| 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 Elective Courses | ||
| 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 |
Students must complete 15 Olin Business units, including all 9 units of Olin Professional Core Courses and 6 elective units.
| Code | Title | Units |
|---|---|---|
| Olin Professional Core Courses | 9 | |
| ACCT 2610 | Principles of Financial Accounting | 3 |
| FIN 3150 | Capital Markets and Financial Management | 3 |
| FIN 4410 | Investments | 3 |
| Olin Electives | 6 | |
| FIN 4506 | Financial Technology: Methods and Practice | 3 |
| FIN 4510 | Options, Futures and Derivative Securities | 3 |
| FIN 4370 | Advanced 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 |
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At least one of FIN 4510 or ESE 4270 must be taken to complete the second major. ESE 4270, if taken after FIN 3150, can be used to satisfy the FIN 4510 prerequisite of Olin elective courses.
For more information, contact the director of the program, Vladimir Kurenok.