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University of Chicago - MS in Financial Mathematics

University of Chicago - MS in Financial Mathematics

UChicago - Financial Mathematics

Reviews 4.75 star(s) 40 reviews

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 course...in 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.

Projects
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.
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