University of Michigan Quantitative Finance and Risk Management

University of Michigan Quantitative Finance and Risk Management

Established
2015
Type
Full-time
Tuition
2021-2022 Tuition per Term: Residents-$12,451/ Nonresidents-$25,068
Application deadline
February 1
Location
Ann Arbor, MI
The Department of Mathematics and the Department of Statistics jointly oversee an interdisciplinary Master of Science degree program in Quantitative Finance and Risk Management. The MS program focuses strongly on advanced mathematical and statistical methods and provides graduates with a sophisticated mathematical background and the skills necessary to apply their expertise to the solution of real finance problems. The 36-credit MS program has two paths for students interested in advanced study in quantitative finance: a 3-term track for traditional graduate students, and an accelerated BS/MS program for current U-M undergraduates.

Coursework:

The program consists of 24 credits of core classes, plus 12 credits in electives.

Core Courses:
Advanced Financial Mathematics I & II
Stochastic Processes
Stochastic Analysis for Finance
Computational Finance I & II
Applied Statistics I
Statistical Analysis of Financial Data

Approved electives include many courses in economics, finance, engineering, mathematics, and statistics.

Admissions

The program admits students for the Fall term only. The application opens September 15 and closes February 1. GRE scores are required. Subject test is highly recommended.



Website: University of Michigan Quant Program
Contact: quantfinms@umich.edu.
Author
umqfrm
Views
14,449
First release
Last update
Rating
2.67 star(s) 6 ratings

Latest reviews

Introduction:
I write this review from the perspective of a student who has a balanced mathematics and statistics background whose goals were to get a practical education in quantitative finance to use towards a career in the industry.

1. Curriculum: The core curriculum of financial mathematics (4), probability (2), and statistics (2) may seem quite reasonable at first glance, but the material is presented in such a way that is often overly theoretical and more complicated than it needs to be. Additionally, the applicability of such knowledge to most graduates of this program in their future careers is suspect at best.

The courses of most interest personally were the statistics and probability courses. Overall, the quality of instruction there is somewhat decent and their application in general for students going into software development or data science may not be entirely nil. However, based on my collection of experiences, the quality of course depends greatly on the instructor and utilization of things such as office hours is 100% a must if you want to have a ghost of a chance at doing well in classes.
As for financial mathematics, the coursework is deeply theoretical and often presented in ways that are difficult to digest. The pacing of the coursework is also irregular and exponential in its difficulty. The impression I get in common with multiple cohorts of students from this program, both old and new, is that it is almost entirely impossible to succeed without a collaborative effort. Although it had been mentioned that the course material in these classes may be useful for a quant interview, I would say that point is moot, because studying directly for interviews using things such as ‘the green book’ and other similar study guides is almost surely more effective than trying to do so through studying the course material.

As a whole, the pacing of the coursework is grueling, leaving students little to no time to balance their studies with preparation to enter the industry (a goal to which probably over 95% of the student body aspires to).

Lastly, as a rebuttal to some previous reviews, I would like to say that the faculty teaching most of the classes are most certainly not uncaring about the students – they recognize the difficulty of the material for most and can be of great help if a student just asks for it.

Suggestions:
1. Reconsider the pacing of the coursework, both as a whole and how it is taught in class. The current pace often catches students off guard, sending the students into despair by mid-semester. I would suggest offering alternative settings of curriculum to students and presenting plans for graduation in 1.5 years, 2 years, 2.5 years and 3 years based on how they want to handle their course load.

2. Add flexibility to the graduation requirements for this program. For students who desire to go towards a PHD in financial mathematics, the current coursework may be appropriate, but for most who just want to get a job in the industry a more practical touch may be required. I would suggest allowing multiple similar courses to fulfil the same requirements for topics that may be pain-points for students. Additionally, there should be options to forego financial mathematics in detail, by instead taking courses related to programming, and software development as these appear to be in high demand in the current job marketplace (for quants and otherwise).

2a. Alternative (experimental) suggestion, divide some core courses into half-semester segments, with the first covering material at a high-level with a focus on conceptual understanding, and the second on details, with the second swappable with a finance/statistics/programming course with equal credit. This would allow students to ‘sample’ the ideas before fully committing to it. Then arrange the remainder of the curriculum around it, creating a unique customizable degree that covers some elements in depth, but the more extraneous ones in breadth.

2. Student Placement: Student placement is poor from this program, there is no other way to say it. To any potential candidates hoping to land a lofty job at a top-tier firm in the US after graduation from this program, I wouldn’t say it is impossible, but it would be a rare occurrence and based almost solely on your own skill and innate aptitude. The program will neither be a positive nor a negative influence on this. It is possibly equally or more likely to get into a good quant job from an undergrad degree than from this program.

Suggestions:
1. Realistically, there are not enough positions in high-tier quant firms for all students of all quant programs to go there. However, there are plenty positions in software development and data science that are looking for students with a good statistics background and problem-solving skills.

2. Due to the high-proportion (90%+) of Chinese international students in the program, it may be appropriate to offer more options to build communication and interview prep skills in the US market.

3. Building off of some suggestions about the curriculum, it may be time to rebrand this degree (again), so as to appeal to more diverse types of employers and to accommodate career decisions that students might make mid-program. Quantitative finance is a small subset of the financial industry as a whole, and the esoteric knowledge requisite for it absolutely useless to jobs outside of the space. I believe its better to give the students options (through course flexibility or otherwise), so that they may be both, 1. Satisfied with the applicability education they received from the program and 2. Land a job where they feel their education will serve them well in the future, because in the most realistic sense of things, 90+% of the graduates from this program will not be going to quant-finance.

3. Student Life: The campus of Ann Arbor is large, with a wide array of things to do in ready walking or biking distance. However, this potentially fun and exciting location may as well be seen through a glass window from a padded room for the students in the quant program. The demanding curriculum essentially keeps students chained to their desks, furiously studying for a vague hope of survival. I’ve known more than several who were stressed to the point of not eating for fear of not being able to keep up with the coursework. Even then, they were hardly able to break the median score when examinations came due. In short, to say the student life is anything less than excruciation would be an understatement. In the past, the kind student coordinator would have been able to alleviate some of this, helping students manage their stress or arranging various avenues for students to manage their course loads, but they have since departed from the program, so new students can expect no such reprieve.

Suggestions:
1. Student life will likely be improved by doing the aforementioned changes to curriculum and placement. Also, get a new coordinator – at least as good as the previous one who was excellent.

Conclusion/Impressions:
If you are a PHD hopeful, you may find this program useful and the right step towards your next adventure in academia. I was lucky enough to end up doing something unrelated to the degree that I love, but, if you just want to get an education that you feel will serve you well in your next job, look elsewhere, there are plenty of other places more deserving of your money.
There are something I can understand and some else I can’t agree in the previous reviews. But basically, I would like to share my personal experience with the program as a 2018 cohort student going for a math finance PhD.

Courses are indeed very rigorous, but not in a bad way
The program comes with a very rigorous line of math courses in math finance, getting you well prepared for an application to a PhD in this field, but I think even for getting a job. I didn’t go through the entire job seeking process, but I did do several online assesments from those quant big names. I can say most (if not all) of the math questions in OA’s and interviews are well covered in course materials. So most of what you learned from class is actually necessary for a quant interview. (You might not use them later in work, but they definitely appear in tests.) Sometimes advanced topics are introduced, but not included in the exams, so don’t seem add your workload too much.

Course selection is flexible
Don’t know why the other post says not, maybe vary from personal experience. Quant program students have almost highest priority in course enrollment within math and stats department (and relatively high priority as Rackham grad students in other departments). And our director of the program is actually quite flexible on the curriculum, as long as you can provide him with a clear plan of yourself. Also, beginning from my cohort many students graduated with a certificate in data science, recently even a secondary master in applied statistics or data science is available.

Instructors are caring
I think it’s very very unfair to say that they don’t care about the students. Umich math department has a strong group of math finance, our courses are all taught by active researchers in the field. Some of them might be unfamiliar with the job market as they mainly live academic lives, but this does not necessarily suggest they are not nice. I once had an instructor who held his helpful office hours as long as lecture times.

Building good foundation for PhD preparation
This point has been repeated even by those who don’t quite like this program. Other than rigorous math courses and wonderful faculty members in the field of math finance, I also would like to mention the rich academic resource at Umich. As a public university strong in almost all subjects, Umich holds a variety of seminars in related areas like math, stats, economy and business. Especially for math finance, not all university can hold a biweekly seminar specifically focussing on math finance.
For those (probably vast majority of) students who don't desire to pursue a phd degree in financial mathematics or find a job in quant research, the QFRM Program at UM may not be a good choice for you. There are several reasons:

1. Curriculum.
The required curriculum consists of 6 math courses and 2 statistics courses, which is solid, tough, but WAY TOO theoretical, lacking real application, especially for core math courses. I have to admit that solid mathematical background is important for quantitative finance field, but how the theoretical knowledge can be connected to real finance world is also crucial. However, seldom do core math courses provide students with application or practice such as hand-on financial engineering related projects to see how the theoretical knowledge learned in class can be applied to the real industry; the only thing that this program teaches students is math, math, and math. Besides, the curriculum is inflexible in that students should take courses in a fixed order (4 required in the first semester, 3 in the second, and 1 in the third), which prevents students from learning as much as what they want in the first year. During the 3rd semester, students can choose enough electives towards their interests such as CS, DS, Stats, Econ, Finance, but as mentioned above how applicable knowledge and skills learned in these electives can be applied to the theretical knowledge learning in math class is what a quant finance program should really teach students.

2. Connection with real industry.
This program lacks opporunities for students to connect or network with professionals in the real industry. There is no chance to work with local corporates for finishing projects in the real industry like some of the other programs have. The program do have some academic seminars, but all of them are about theretical math, instead of real talk with real quants who can share working experiences as a quant, or introducing different topics in the real finance world. Of course, beginning from winter 2020, the program opens a new course called "Machine Learning for Finance" only for students in this program, and the instructor is a real quant. However, the structure of this course is a little bit messy, and the instructor can hardly explain materials clearly, and he never pay attention to how students learn, forgetting about the advantage of having a real quant as an instructor. But anyway the program is making progress that is a positive signal.

3. The care about the students.
Neither the program director nor your academic advisor care about how students learn, or students' job placement, or what difficulties students encounter. The only person who really cares about students is the program cordinator, who is a super enthusiastic lady, negotiating students with any kind of issues, updating job posting information, scheduling mock interview, helping current students network with alumni of this program. But unfortunately effort from one person in the program is not enough.

Overall this program is not recommended for you unless you want to apply for phd in mathematical finance, work as a quant researcher, or you really really love math.
The instructors in math and stats departments of U of M are generally bad. Program does not teach students at all and just want to grab money. Tuition is ridiculous compared to value offered by other programs. Also campus is in the middle of nowhere and very difficult for students to network. You'll also have to deal with a lot of ignorant in-state people who have not been to other places in their whole life. Save your money to a private university.
I got enrolled in the program in 2017 and graduated in December 2018 (one can choose to graduate in 1 year and a half or in 2 years). I highly and sincerely recommend this program and in my opinion, the pros and cons for this program are as follows.

Several reasons for recommending this program:

1. Great mandatory curriculum, staff and professors. The professors are all really nice, professional and funny, and the staff members are all helpful and care about students. Our program coordinator is an excellent lady who always helps us with resume and cover letter writing, interview preparation and alumni networking by coordinating quant seminars with Michigan alumni and forwarding possible working opportunities from alumni's companies. To be honest, the curriculum is challenging since some of them are PhD classes, but this is exactly why we all have a solid theoretical understanding of financial mathematics, and exactly how the program is designed -- our director for the program believes that sold math knowledge is the reason that lots of Math PhDs could end up having a quantitative job. So here we go.

2. Flexible elective curriculum and tons of studying opportunities with Department of Mathematics and with other departments. You can almost always choose whatever interests you as an elective course, such as a course in Ross School of Business, or in College of Engineering, or in School of Information, and even get enrolled in another master's program. I know some friends in this program choose to pursue a Master's in Statistics at the same time, or a Master's in Engineering to learning more about programming. I myself got enrolled in Multidisciplinary Development Program (MDP) to have more practical experience. In a summary, as long as you want to learn something, getting enrolled in this program can and always will serve you as a first step.

3. Wonderful campus culture and lots of chances to get involved and make a contribution to the community. This program is with University of Michigan, and U-Michigan always goes with great alumni network, academic excellence, and especially rich tradition in football! When you walk on campus, you will always feel as if you were part of something bigger than yourself and had the ability to make a difference. With International Student Lunch Conversation, Women In Mathematics, Women's Ultimate Frisbee etc. (just a few examples; these are the ones I was quite often enrolled in), you'll feel welcomed and you'll always have the chance to learn more and contribute more.

4. Job hunting assistance. I suppose most students who want to get enrolled in these Financial Engineering programs are looking for an excellent job afterwards, and definitely you're in for a treat! Not only does this program have an experienced program coordinator for resume and cover letter revision, but we as U-M students also have U-Michigan Career Center for FREE mock interview, FREE professional clothes closet, and everything you can think of related to internship or job hunting for FREE! Just remember to ask for help, and you'll get it for sure.

The biggest con for this program, which I must admit, is that it doesn't have the geographical advantage, as it's not in New York or Boston or any other big city. Ann Arbor is quite possibly the quaintest, funkiest, most cosmopolitan college town in the US, but it doesn't have that many employers. However, we have Career Fairs where tons of employers all over the country will show up and want us -- because we are in University of Michigan and we are in Quantitative Finance!

This is a really young program, and it needs each one of us to take care of and make it become better. Hope you can be one of the Wolverines!!

Whoever is reading this, thanks for your time and patience! Wish you the best luck in the future, and forever Go Blue!!!
Worst program ever existed. Program's director is a super tough guy, caring about nothing regarding students' placement. He does not even respect students. Courses are badly designed. They simply used previous PhD courses to open this master program.Core courses are not practical at all.
We're from 2017 class, which is the best group of people they ever admitted. However, our placement record is worse than some programs that we reject offers from back in 2017.
Plus, tuition is ridiculously high, they just use students as cash cows. Don't donate your money to them!
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