Academics
Building on the University of Michigan’s long history of academic excellence, the Quant program approaches the study of quantitative finance with an intensely theoretical perspective. Our close focus on advanced mathematical and statistical theory sets us apart from our peer programs in financial engineering, computational finance, and mathematical finance and provides graduates with an unparalleled foundation for a career in finance.
Learning Goal 1: Apply advanced stochastic analysis and probability theory to solve complex mathematical and financial problems.
Assessment of goal: Performance in core and elective courses in probability, stochastic calculus, and financial mathematics, as well as on comprehensive exams that assess theoretical understanding and applied capabilities
Learning Goal 2: Translate real-world financial questions into mathematical models and analyze them critically.
Assessment of goal: Assessment of students’ ability to clearly formulate assumptions and represent financial problems mathematically
Learning Goal 3: Implement quantitative solutions using advanced computational and numerical methods.
Assessment of goal: Evaluation of programming assignments and computational projects using tools such as Python
Learning Goal 4: Make informed, data-driven decisions grounded in mathematical reasonings.
Assessment of goal: Coursework that include a decision-making rationale grounded in quantitative results, as well as internship or practicum supervisor evaluations, if applicable
Course Plan
The Quant Program requires the completion of 36 credits, comprising 27 credits from core courses and 9 credits from electives. The curriculum is structured around 9 core courses, which are spread across 4 semesters. Students are required to follow the prescribed course sequence outlined below.
While students have the flexibility to complete the program in 3 semesters by taking all approved electives during that time, the core courses must be taken in their scheduled semesters. A total of 36 credits must be completed to graduate. Per the Quant Program Core Course Policy, deviating from this schedule and deferring core courses to other semesters will result in being dropped from those courses. Adhering to the core course sequence is essential for building a strong foundation and meeting the program’s learning objectives.
2-Year / 4-Semester Program
First Semester: Fall I
12 credits (full-time)
- Numerical Analysis with Financial Applications (MATH 472)
- Discrete State Stochastic Processes (MATH 526)
- Advanced Financial Mathematics I (MATH 573)
- Statistical Learning I: Regression (STATS 500)
Second Semester: Winter I
9 credits (full-time)
- Stochastic Analysis for Finance (MATH 506)
- Advanced Financial Mathematics II (MATH 574)
- Statistical Analysis of Financial Data (STATS 509)
Third Semester: Fall II
9 credits (full-time)
- Computational Finance (MATH 623)
- Mathematical Methods for Algorithmic Trading (MATH 507)
- 3 credits of electives (read “Electives” information below)
Fourth Semester Winter II
6 credits (part-time)
- 6 credits of electives minimum (read “Electives” information below)
- See note below*
*Note: International students must enroll in at least 8 credits to maintain full-time status. Taking fewer than 8 credits and being considered part-time is only allowed in the final semester with an approved Reduced Credit Load (RCL). For RCL-related questions, students can contact the International Center at icenter@umich.edu.
Alternative: 1.5-Year / 3-Semester Program
First Semester: Fall I
12 credits (full-time)
- Numerical Analysis with Financial Applications (MATH 472)
- Discrete State Stochastic Processes (MATH 526)
- Advanced Financial Mathematics I (MATH 573)
- Statistical Learning I: Regression (STATS 500)
Second Semester: Winter I
12 credits (full-time)
- Stochastic Analysis for Finance (MATH 506)
- Advanced Financial Mathematics II (MATH 574)
- Statistical Analysis of Financial Data (STATS 509)
- 3 credits of electives (read “Electives” information below)
Third Semester: Fall II
12 credits (full-time)
- Computational Finance (MATH 623)
- Mathematical Methods for Algorithmic Trading (MATH 507)
- 6 credits of electives (read “Electives” information below)
If you are currently an undergraduate Mathematics major at the University of Michigan, you are eligible for the Accelerated Master’s Degree Program (AMDP), which offers a unique one-year course plan. Click the button to the right to view the accelerated course plan.
Core Courses
You will complete 9 core courses, totaling 27 credits, in graduate-level mathematics and statistics. The master’s program is organized into four-course sequences that form the core of the curriculum. To progress to subsequent courses, you must successfully complete the initial course in each sequence. The details of these sequences are outlined below:
MATH 573 – Advanced Financial Mathematics I +
MATH 574 – Advanced Financial Mathematics II
Introduces students to the main concepts of financial mathematics and financial engineering, with special emphasis on the application of mathematical methods to the relevant problems in the financial industry.
MATH 526 – Discrete State Stochastic Processes +
MATH 506 – Stochastic Analysis for Finance
Analyzes in more detail the mathematical tools used in MATH 573 – MATH 574 with additional focus on mathematical challenges associated with financial problems.
MATH 472 – Numerical Analysis with Financial Applications +
MATH 623 – Computational Finance +
MATH 507 – Mathematical Methods for Algorithmic Trading
Focuses on the implementation of the models using tools from numerical methods for solving partial differential equations and Monte-Carlo methods. Students develop computer programs to calculate the prices of financial derivatives and find ways of hedging risk.
STATS 500 – Statistical Analysis I: Regression +
STATS 509 – Statistical Analysis of Financial Data
Introduces the basic statistical tools for financial data, including regression and time series models, as well as various inference techniques.
Electives
Quant students select 9 or more credits of approved electives from across the university. This flexibility allows students to tailor their academic path to align with their specific interests, such as programming, data science, finance, or advanced mathematics. In addition to the approved elective courses, students may propose other courses for consideration, subject to approval by the Quant program. Requests for approval should be emailed to quantfinms@umich.edu.
It is highly recommended to take MATH 628/629 – Machine Learning for Finance I/II (2 + 2 credits, offered in Fall/Winter). These courses can be taken in either the first or second year of the program.
Graduation Requirements
To earn a master’s degree in Quantitative Finance and Risk Management, students must adhere to the following additional requirements, in addition to completing the specified coursework:
- Complete all required core courses with a minimum grade of C- or better.
- Fulfill a minimum of 9 credits from approved elective courses.
- Earn a total of at least 36 credits applicable to the Quant program.
- Maintain compliance with all academic regulations set forth by Rackham Graduate School, including maintaining a cumulative GPA of 3.0 or higher.
- Submit an official transcript(s) directly from the issuing institution(s) prior to applying for graduation.
- Submit an application for graduation as per the deadlines specified by Rackham Graduate School.
Academic Probation Policy: Students are required to maintain a cumulative GPA of 3.0 or higher to remain in good academic standing. If this requirement is not met, students may be placed on academic probation. Our program follows the Rackham Graduate School’s academic probation policy and procedures, but we also have our own specific probation policies. For detailed information on both sets of policies, please consult the Rackham Graduate School’s website as well as our Quant Program Academic Probation Policy.
These requirements collectively ensure that students meet all necessary criteria for the completion and award of their master’s degree in Quantitative Finance and Risk Management.