Master of Science in Finance - Quantitative (MSFQ)
Contact Info
In the 18-month Master of Science in Quantitative Finance (MSFQ) program, students gain skills in mathematical and strategic decision making. Designed for students with a strong mathematical background, this technical curriculum is ideal if the student's career goals include working in financial services or related industries. Experiential learning is a degree requirement, so all MSFQ students will gain hands-on experience during their program.
Our quantitative finance program requires the completion of 39 credits, and it is STEM-designated for its focus on science, technology, engineering, and mathematics. The curriculum includes 33 required credits and 6 elective credits that focus on advanced quantitative skills, which provide students with a current and innovative approach to finance.
Orientation Programs
All Specialized Master’s Programs students kick off their degrees with a multipronged orientation program designed to prepare them for academic, personal and professional success.
Students will participate in various online and in-person orientation activities prior to beginning their fall semester at Olin. SMP Start is a set of online modules that introduce students to the ins and outs of Washington University including policies and procedures, health and wellness, leadership opportunities, and more. SMP Orientation Week includes workshops, events, and cohort overviews including introductions to faculty and advisors. This week is set up to help students with their final preparations before the start of their first semester. Orientation includes career sessions, which serve as catalysts for students to help them get started in their career search. These programs are packed with opportunities for students to bond with their program cohort and to connect with their peers in all of the Specialized Master's Programs.
Students new to the United States may have the opportunity to participate in Passport, during which they will acclimate to the Olin Business School culture and strengthen their English and business communication skills.
Simultaneously, students will complete required online, asynchronous foundation courses to bolster their background and maximize their academic preparation before the start of their degree program.
Required Courses
Students must complete the following courses:
| Code | Title | Units |
|---|---|---|
| FIN 500Q | Quantitative Risk Management | 3 |
| FIN 500R | Topics in Quantitative Finance | 1.5 |
| FIN 524 | Options and Futures | 1.5 |
| FIN 524B | Derivative Securities | 1.5 |
| FIN 525 | Fixed Income Securities | 1.5 |
| FIN 527 | Financial Markets | 1.5 |
| FIN 532 | Investment Theory | 1.5 |
| FIN 532B | Data Analysis for Investments | 1.5 |
| FIN 534 | Advanced Corporate Finance I - Valuation | 1.5 |
| FIN 534B | Advanced Corporate Finance II - Financing | 1.5 |
| FIN 537 | Advanced Derivative Securities | 3 |
| FIN 538 | Stochastic Foundations for Finance | 1.5 |
| FIN 539 | Mathematical Finance | 1.5 |
| FIN 552 | Fixed Income Derivatives | 1.5 |
| MGT 537 | Financial Industry Platform for MSFQ and MSFWAM Students | 0 |
| MGT 560F | Professional Business Communication | 1.5 |
| DAT 537 | Data Analysis, Forecasting & Risk Analysis | 3 |
| DAT 561 | Introduction to Python and Data Science | 3 |
Experiential Courses and Electives
Students select one of the following options:
Option A:
- 1.5 experiential course credits plus
- 4.5-6 elective credits from the approved list plus
- 1.5 additional approved elective credits (if only 4.5 credits are completed from approved list)
Option B:
- 3 experiential course credits plus
- 4.5 elective credits from the approved list
Experiential course options:
| Code | Title | Units |
|---|---|---|
| MGT 501V | Applied Problem Solving for Organizations | 1.5 |
| MGT 502V | Applied Problem Solving for Organizations | 1.5 |
| MGT 551E | Internship, Business and Application | 1.5 |
| FIN 501P | CFAR Practicum | 3 |
Approved MSFQ elective courses:
| Code | Title | Units |
|---|---|---|
| DAT 500S | Machine Learning Tools for Prediction of Business Outcomes | 3 |
| DAT 560G | Database Design and SQL | 1.5 |
| DAT 560M | Big Data and Cloud Computing | 1.5 |
| CSE 412A | Introduction to Artificial Intelligence | 3 |
| CSE 417T | Introduction to Machine Learning | 3 |
| CSE 427S | Cloud Computing with Big Data Applications | 3 |
| CSE 502N | Data Structures and Algorithms | 3 |
| CSE 514A | Data Mining | 3 |
Additional approved elective options (if necessary):
| Code | Title | Units |
|---|---|---|
| FIN 557E | Introduction to Blockchain and Cryptocurrencies | 1.5 |
| FIN 558E | ESG Investing | 1.5 |
| MGT 578E | Strategic Data Storytelling and Visualization for Business | 1.5 |
| MEC 531 | The Global Economy | 1.5 |
| Other courses with Academic Director approval | ||