University of Chicago Financial Mathematics program

University of Chicago Financial Mathematics program

Full-time, part-time
Chicago, IL
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Founded in 1996 by an exceptional team of educators, the University of Chicago’s Financial Mathematics Program has shaped some of the brightest minds in the financial industry today. Located in Hyde Park, the University of Chicago is well known for housing great minds.

Currently the Program offers 15 months of accelerated, integrated coursework that explores the deep-rooted relationship that exists between theoretical and applied mathematics and the ever-evolving world of finance. To assist our students with applying theory to practice, we offer year-round CPT as well as Project Labs with area employers to help build out our student's skills and knowledge about the quant industry. Our Program, with its unmatched student body and highly accomplished faculty, works hard to uphold the University’s core values by creating an atmosphere that encourages intellectual collaboration and growth.

Lastly, students of the MSFM Program at the University of Chicago enjoy a world-class education. Courses are taught by a combination of established academics and industry professionals. Beyond academics, the MSFM Program offers students the opportunity to grow both privately and professionally. Networking events are held regularly to encourage communication and professional growth.

Interested in learning more, request information by going to:
The University of Chicago | Financial Mathematics and someone from our admissions team will follow up with you shortly.
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3.80 star(s) 5 ratings

Latest reviews

A year out from graduating here, I wanted to give a fair evaluation of the Financial Mathematics Program at the University of Chicago (U of C). The program has its problems, but I gave 5 stars ultimately because my high expectations were met

Came from Australia. Bachelor of Actuarial Studies / Bachelor of Finance. 2 years work experience at an actuarial consultancy, 2 internships at banks in market risk and credit risk. Qualified actuary

Did you get admitted to other programs?
Yes. My next choice would have been Columbia MSOR

Why did you choose this program (over others, if applicable)?
- I was dead set on becoming a trader and Chicago is the trading hub of the world. There are so many trading firms in Chicago, as well as elite hedge funds. The banks mainly operate out of New York

- U of C has a competitive advantage for the job market in Chicago. This is HUGE. There are only two nearby schools I can think of that compete; the University of Illinois and Northwestern. U of I is still annoyingly far away, and as far as I know Northwestern doesn't have a relevant masters program

- Massive brand name. The ranking system that people seem to care about most over here is the USNews one, where U of C is right up there. You'll get interviews in any city. Companies love this school in general

- The actual beauty of the school. Whether it's the amazing libraries, lecture theaters where countless nobel laureates have taught, or the actual MSFM building/house, the school itself is absolutely inspiring. I have to admit, I didn't know U of C was a top school before starting to research graduate programs, but there's no doubt in my mind that it's one of finest academic institutions in the world

- Project Lab (mentioned below)

- The business school. Even though the masters degree is separate, it doesn't hurt to have one of the top business schools on campus. You can try to take courses there (with extra approval). I worked on research in Booth, which was great

- Chicago is beautiful

- The courses are taught by heavyweights in both academics and practice

Application process
Standard process apart from an extra video that you have to provide, answering a couple questions

Course selection
Good range of courses taught on a quarter system (VERY intense). Here are some key points:

- Courses are at night to accommodate for lecturers who work outside of U of C
- One month of refresh courses before the program actually starts. This is a great time to get ready and even start putting in internship applications
- Decent range of electives, including ones on trading directly, machine learning, and time series analysis (taught in Booth). Generally speaking, the core courses are very theoretical and electives are practical
- The options courses are fantastic
- Increasing focus on computer programming. I believe the main language used has been switched to python
- Some very technical mathematics, including stats and calculus courses. These weren't too useful to me, as I wasn't pursuing a pure quant path and had already learned a lot of the material as an undergrad. They were also taught at lightning speed
- Courses on portfolio theory are good. I'm not sure if this is still the case, but both were compulsory; one was on credit risk, which I didn't find useful at all for my career path
- You can test out of some of the programming and an introductory finance course. The introductory finance course I heard was a waste of money

Quality of teaching
Some amazing lecturers and some not-so-amazing lecturers. As I mentioned, there are both academics and practitioners. Being a top school, the academics are very knowledgeable. Being a trading hub, the practitioners are also very knowledgeable (some are current or ex-head quants at top-tier firms). My favourites (in no order) were: Brian Boonstra, Mark Hendricks, Yuri Balasanov, Niels Nygaard, Roger Lee and Chanaka Liyanaarachi

Materials used in the program
A computer and a brain

Notably there is Project Lab, which is a cooperative project between a group of students and a company. This is the MSFM program's trump card. I'm not completely sure on the statistic, but something like 100% of students who apply for Project Lab will end up on a project. The companies are: trading firms (IMC, Belvedere, etc.), hedge funds/asset managers, exchanges and consultancies. I don't believe any banks are in the rotation

Career service
I never really used the MSFM career service apart from our job board, because hustle generally works. Our job board is good. Honestly the careers office seemed a bit small for the number of students and money being hauled in from tuition. This has been restructured since I left though. Outside of the program, there are big career fairs at U of C, as well as companies pencilled in weekly for presentations; these are amazing.

Student body
Very smart students with not a lot of work experience. Not demographically diverse enough in my year; 95% foreign students from Asia. Cheating is treated harshly, which I think is the right way to go. It's an EXTREMELY intense program though, so many resort to cheating. There are a handful of professionals taking the course part time after work

What do you like about the program?
To sum it up, I entered the Financial Mathematics Program at the University of Chicago to learn, AND THEN from that find a job. That's exactly what happened; I learned a boat load, both through the program and on my own... and out of it have come some fruitful years in the US

Suggestions for the program to make it better
- Shave away some of the worse courses or make them electives
- Try to become more diverse without sacrificing student quality
- Beef up the careers services
- Create alumni events in New York ;)

What is your current job status?
Quantitative options trader at a midsize market making firm

Bachelor degress in Math and Statistics in the US. Worked as a investment analyst before going to UChicago MSFM program. Currently working as a quantitative trader in Chicago.

Did you get admitted to other programs?

Why did you choose this program (over others, if applicable)?
It is the location. Chicago is the hub of trading business. I decided to come to Chicago to start my career in trading.

Application process
The application process is pretty easy. Submit the transcripts , resumes, application statements with a video.

Courses selection

Recently UChicago has been working hard on improving the courses. Right now in the first quarter, it offers a Python class which requires zero background in coding and the class will eventually cover a pretty decent depth in the topic of programming. E.g Inheriance, OOP, Concurrency, TCP servers.

There are a lot of trading related classes which I liked the most. Quantitative trading, applied algo trading and Machine Learning in Finance.

The new Machine learning in fiance is also a great class as to get into the application respective of machine learning in finance and trading. However, the class is not easy and requires a lot of work to understand the Mathematics concepts behind each algorithm.

The option pricing classes are the core classes at UChicago MSMF program. Professor Roger Lee always has a great way of getting you to understand the hard Math concepts.

There are still some required classes which involve heavy math. e.g Stocastic calculus , Fixed income derivates.
Making them as elective classes would be a better choise.

Quality of teaching

Option class are always on the top of the academia. Professor Lee always has his unique way of expressing complicated option concept into plain English. I enjoyed both his classes despite the heavy math concepts behind.

There are many trading professionals lecturing the classes. E.g Quantitative trading and regression classes are great class to get started in trading. I was asked a lot during the interview processes.

I really appreciated the video recording of the lectures. I can review any class again.

Materials used in the program
Notes are enough

Programming component of the program

They are teaching C++ and Python from zero.
Matlab is needed for a lot of classes, you can use Python or R for most of these classes as well
I picked up C++ and Python from almost zero and know using them for daily work.

Lots of interesting projects. Very time consuming but you can learn a lot from it

Career service

Location, location, location. Chicago has a lot of trading firms and exchanges.
Career service provides mock interviews and organizing recruiting events.
However, it is still a lot of work for the students to prepare.

What do you like about the program?
A lot of interesting classes, events and workshops. It prepares me for starting a career in trading industry.
The professors and lecturers are easy to work with.
You can learn programming efficiently and masters it during the program.

The project lab is a great way of getting working experience while still in school. It helps a lot on the resume building as well.

What DON'T you like about the program?
Some of the classes are still pretty theoretical, need to be more pratical
First quarter is very intensive, while we need to prepare for the interviews.

Suggestions for the program to make it better

Consider to drop some of the heavy math classes, add in more practical classes.

What are your current job status? What are you looking for?
I'm currently working as a quantitative trader. I'm planning to become a quantitative portoflio manager soon.
Not bad and sounds like things have been improved

What do you think is unique about this program?
Hard to say because I only have second hand info about other programs, but I will try:

I felt like the pace was really fast. When courses drag on too long, it's easy to lose interest and motivation.

Also, there were some really good professors: Paulsen was an excellent lecturer and was very helpful in understanding the material. Lee did real well at explaining and teaching some pretty complex and deep material (for me). Hanson did a great job making stochastic calculus accessible to someone with an engineering background. Even though Fefferman only did a few days of intro on measure theory, he was also excellent at making very theoretical and deep material accesible. There is no shortage of teaching talent, but not every professor is awesome.

What are the weakest points about this program?
The year I went (2009-2010), there were way too many students admitted (~150, which means around 250 people in lecture, including part-timers from previous years). About half seemed legit and about half seemed like undergrads who couldn't get jobs and whose parents had the money to send them. Essentially spoiled brats with no manners. They made it difficult for the instructors because they don't shutup for lecture and they were always suspect of cheating, so the instructors had to be jackasses during exams and during lecture a lot of times. Some of these kids were really bright and some, well, were just kids with no professional experience and no clue how to conduct themselves. Of course, I believe this has changed and the year I went was definitely a transitional period for the program.

This is a minor complaint, but I think there could have been a little more flexibility in the curriculum. For instance, I would've liked to take some computer science classes like machine learning or AI. and perhaps some accounting or more pragmatic finance courses in the business school. It would have rounded things out well if I could've done that.

Career services
I tend to think, "You make your own breaks," for stuff like this. There were quite a few companies recruiting and there were opportunities, just not as many as a b-school student would have. But then, b-school grads get hired into a more broad spectrum of industries and job functions. The school had a decent career website and recruiting process.

The career services I thought were done fairly well, but not outstanding. Tim Weithers did a great job, as did the others.

I and many others found pretty good jobs. A combination of the right fit for a position, a little luck and networking really does a lot.

Of course, that doesn't mean everybody had the same experience I did. I also know some people who had trouble finding a job and either had to revert back to their original job function or had to look for an extended period of time. I'm not sure that's the school's or the program's fault. A bad job market and perhaps lack of planning could've contributed.

Student body
Even though the network was smaller, I met and keep in touch with quite a few people from the program. I have many fond memories of U of C and the program and did a lot of learning there. No amount of disparaging remarks about the program, the professors or the students will change that.

I mentioned the class size above, which made it harder to meet more good people. Again, I believe this has changed and thank God for that.
Can you tell us a bit about your background?
B.S. Engineering Physics (High Honors), University of Illinois at Urbana-Champaign, 2002
B.S. Computer Science (Highest Honors), University of Illinois at Urbana-Champaign, 2002
Five years of IT and software development
I studied full-time in the program from 9/2007-6/2008

Did you get admitted to other programs?
Yes; NYC Courant's Mathematics in Finance and Carnegie Mellon's MS Computational Finance
Why did you choose this program (over others, if applicable)?
Short duration, lower cost of program and of living, reputed heavy mathematical focus.

Tell us about the application process at this program
Online application. Had to submit GRE General test scores. Went smoothly.

Does this program have refresher courses for incoming students? How useful was it?
There were free courses offered to incoming students which were nominally "refresher" courses. In practice, these courses were survey courses in material that students were unlikely to have been exposed to. Several of them were very useful; the measure theory course conducted by Robert Fefferman was outstanding, and the finance introduction by Tim Weithers was well-done.

Tell us about the courses selection in this program. Any special courses you like?
Mathematical Foundations of Option Pricing - excellent
Numerical Methods - excellent
Statistical Risk Management
Stochastic Calculus
Data Analysis And Statistics - disastrously bad
Topics in Economics - well-taught, but questionably relevant
Portfolio Theory and Risk Management - good
Foreign Exchange
Fixed Income Derivatives - wildly mixed quality depending on presenter
Advanced Option Pricing
C# Programming (optional)

Tell us about the quality of teaching
Teaching quality ranged from very competent to insultingly poor.

On the "competent" end, Roger Lee deserves particular commendation for his course preparation and delivery in Mathematical Foundations of Option Pricing and Numerical Methods. The design and delivery of both courses was absolutely meticulous and well thought-out. Other instructors who deserve positive mention include: Paul Staneski and John Zerolis (Portfolio Theory), Lida Doloc (Fixed Income Derivatives), and Jostein Paulsen (Stochastic Calculus, Statistical Risk Management).

Sadly, there were also several instructors who did not appear to feel it necessary to assemble a coherent syllabus or present their material in an understandable fashion to the students in their classes. Chief among these was Per Mykland, who "taught" the Data Analysis and Statistics course (and I believe in most years teaches stochastic calculus as well). His lectures were very rough surveys of material which was inaccessible and unknown to most of the students in the course. Generally, no supplementary reference texts were mentioned to provide comprehensible explanations of the topics covered, and his lecture notes were filled with errors that had clearly gone uncorrected for years. Much of the final section of his notes consisted of text copied directly (save an occasional misspelling) from N.H. Chan's _Time Series_. The material covered by the homeworks was often not addressed by the lectures; in fact, the head teaching assistant informed us in no uncertain terms that he expected most of the class to fail the second homework. The teaching assistants were often unable to help with the homeworks, leading me to believe that they frequently did not understand the material any better than we. Students did so poorly in the class that he announced his intention in the final lecture to simply give all students 'A's in lieu of a final exam (though he was later overruled).

Professor Mykland's disregard for his teaching obligations is legendary; there are discussions on Wilmott Forums of his lack of concern for his audience's comprehension all the way back in 2005 and it seems that little has changed. Unfortunately, data analysis and statistics are fundamental to financial mathematics, and for those of us who did not enter with graduate degrees in statistics, we were left woefully unprepared for the remainder of the courses (particularly stochastic calculus and statistical risk management) as well as job interviews. As a particularly pointed example, I was unclear on what a "standard error" was until I engaged in a program of self-study after his which I got an A-.

Materials used in the program
Primary texts included:
- Hull's _Options, Futures, and Other Derivatives_
- Carmona's _Statistical Analysis of Financial Data in S-Plus_
- Ingersoll's _Theory of Financial Decision Making_
- Bjork's _Arbitrage Theory in Continuous Time_

I also found Baxter and Rennie's _Financial Calculus_ to be an excellent introductory text, though it was not used directly in the courses.

Programming component of the program
Excel, R for statistical analysis, MATLAB for numerical methods, C++ with Quantlib for some interest-rate derivatives work. The introductory programming courses were taught in C# and covered basic ASP.NET. Many of the homework assignments had a programming component.

There were few "projects" per se, though much of the homework was group work.
Career service
Unknown; I didn't use them.

Can you comment on the social interaction between students of different ethnics, nationalities in the program?
Many of the Chinese students formed a fairly tight social group, I suspect due to shared language. The remainder of the students were very outgoing and mingled and worked together freely.
What do you like about the program?
Excellent instruction in a few topics, a good reading list, U of Chicago name on the diploma, meeting a lot of great people.

What DON’T you like about the program?
The general disregard for the quality of education received by the students.
Suggestions for the program to make it better
- Dismiss Per Mykland.
- Solicit feedback from students to ensure that professors generally are doing a good job, and reward them or remove them accordingly.
- Ensure that professors are aware of how their courses fit into the overall curriculum. Many of them seemed unaware of what students entering their classes would and would not be expected to know.

What are your current job status? What are you looking for?
I am employed by an investment bank as a software developer, and would like to find more quantitative challenges in the near future.

Other comments
If you have a graduate level of statistical experience, are very comfortable with PDEs (and preferably SDEs), and are willing to put up with having to fight to learn in some classes, you could get a lot out of this program. Otherwise, I would suggest going elsewhere.
Master's degree in computer science. Worked for a bank as a risk analyst and currently working as an energy trading strategist for a major energy company. I am located in Singapore and report to boss in UK.
I studied part-time in the Chicago MSMF Singapore program since Sept 2009

Did you get admitted to other programs?

Why did you choose this program (over others, if applicable)?
I only applied for UChicago MSFM Singapore as it seems the best choice in Singapore or even Asia in terms of reputation.

Application process
The website was and is outdated. Most of the information regarding this program was found in online discussions. They responded my emails selectively.

Courses selection
1. Course selection is not flexible. I like Statistical Risk Management, Mathematical Foundation Option Pricing and Fixed Income so far.
2. Singapore students can study in Chicago for 1 or 2 quarters our of 3 quarters. a lot of us chose to go to Chicago in Spring quarter Apr - Jun
3. We can choose one course from Chicago Booth, which is only available in Chicago campus

Quality of teaching
1. Practitioners teaching Fixed Income are good. because the course is reduced for some reason they insist offering additional seminar which is not counted in grading.

2. the class is like a video-conference bringing people from Chicago, Singapore and Stamford together. the video quality is good. we can ask questions using a microphone. all classes are recorded and can be played back later.

3. Teachers for each course normally come to teach in Singapore for 2 weeks, giving lectures and office hours.

4. Singapore program has local TAs for every course, mostly previous graduates. They are very helpful. Without TA's help it's not possible to figure out homework. In terms of homework, TAs are much more useful than lecturers.

Materials used in the program
Notes are enough

Programming component of the program
Matlab is dominant. There's C# class but i haven't taken. For me not much programming except the Matlab programming in statistical risk management and regression analysis.

so far i haven't done any project, expecting one for Regression Analysis.

Career service
1. We visited a couple of banks in Singapore
2. Our resumes are compiled and sent to banks
3. Other than campus recruitment, quite a few immediate openings have been sourced by local career service.
4. nothing specific to intern

Student body
Ethnics are quite diversified and balanced. we are also invited to Chicago Booth alumni gathering in Singapore.

What do you like about the program?
I am much more confident about my math now. previously i picked up some models on my own, which can't compare to what I learn in the program in terms of both coverage and depth.

What DON'T you like about the program?
1. the most important course Stochastic Calculus should be taught much better.
2. the management doesn't care much about publicity. i think for a professional program this is very important. the more people appreciate the program the more value that the current students and previous graduates get.

Suggestions for the program to make it better
I would hire a public relationship manager to advertise the program better.

What are your current job status? What are you looking for?
as a quant strategist in energy trading. i want to expand my skill set further and look for more challenging opportunities, e.g. trading, portfolio manager, deal originator, etc