NYU Courant - MS in Mathematics in Finance

Can you tell us a bit about your background?

BS in Mathematics/Applied Science from UCLA. A commercial banking internship and buy-side investment risk internship as an undergrad.

Did you get admitted to other programs?

Rutgers MSMF, Columbia MFE

Why did you choose this program (over others, if applicable)?

I liked the location the best. Smaller class size compared to Columbia MFE, and the professors were willing to answer questions while I was already accepted but still considering where to go.

What do you think is unique about this program?

Compared to schools outside of NYC, having professors who are practitioners. Compared to other schools in NYC, superior location.

Tell us about...

Quality of teaching:

The professors were very knowledgeable, but it wasn't always the most well organized. Sometimes the material was too advanced or too fast paced for the students to properly learn the topic before moving on to the next subject. However, I would say the program did a good job covering the essential knowledge needed to do well in interviews and eventually in the industry.

Programming component of the program:

Not much OOP outside of a class in the first semester. Quite a bit of exposure to Matlab, which is good. However we were taught Java instead of C++ which was a bit unfortunate. Even though we learn the core programming concepts, it seems like quants in the industry prefer C++. Most of the assignments and projects are programming based, so students will get plenty of practice.

Career service:

Needs serious improvement. The career workshops done during the first semester were marginally helpful, but should be common knowledge for any serious candidate looking for a finance job. Very few employer presentations, unless students signed up for themselves on company websites. Not many networking opportunities set up by the program, the initiative is placed solely on the student. There were several internship and job postings forwarded to the full time students by the program however, which was nice.

What is your current job status? What are you looking for?

Buy-side portfolio management. To be honest I didn't really want to be a quant, and after my quant oriented internship I realized I would much rather be market facing and a part of the investment decisions. These roles are usually reserved for undergrads and MBAs so I was quite happy landing a role here coming out of a quant program. The obvious long term goal: portfolio manager.

Can you tell us a bit about your background?

I had worked for six years in risk management, managing the asset allocation and the investment risk of Singapore's official foreign reserves. Prior to that, I was an undergraduate at the National University of Singapore, with a double major in applied mathematics and statistics, and minors in computational finance and economics. As much as I enjoyed my job, after six years in the industry I felt keen to go back to school to experience life as a student again. At the same time, I wanted to build upon the basics I had learnt and deepen my knowledge of financial mathematics.

Did you get admitted to other programs?

CMU MSCF, Columbia MFE, Cornell MFE

Why did you choose this program (over others, if applicable)? What do you think is unique about this program?

I'll answer these two questions together since the reasons I chose this program are exactly what makes this program unique.

Firstly, coming from a math background, I was perhaps irrationally drawn towards a program housed in the math department. It definitely didn't hurt that Courant is the top-ranked school in the US for applied mathematics. Secondly, being in New York offers an unbeatable array of networking opportunities, from meeting up with alumni, to attending seminars for financial professionals such as those organized by IAFE and CFA. Thirdly, the classes in NYU are mostly taught by highly-accomplished industry practitioners. These are people who apply what they teach on a regular basis, and I wanted to learn from their experience.

Tell us about...

Quality of teaching: I wasn't worried about the quality of teaching. I think as graduate students, we should already know how to learn something on our own by picking up a good reference text. I saw the instructors as being there to guide our learning by setting relevant assignments. Plenty of our assignments are tasks that are actually carried out in the industry, and we learnt a lot just by working on them.

Programming component of the program: Many of our classes (or perhaps just the classes I chose) require us to work in Matlab. Other classes require Java.

Career service: We have access to Wasserman, which is NYU's career service center. Companies looking for students to fill specific quant finance roles often reach out to the Math Finance program directly, and the job descriptions subsequently get forwarded to us. The program also hires career consultants to coach us in networking skills and interviewing techniques, but I hear this is commonplace among the top programs.

What are the weakest points about this program?

I'll list two.

Firstly, I would have preferred to be taught C++ instead of Java. I am seeing many job openings that require the applicant to be well-versed in C++, and none that prefer Java over C++. I understand that the two are sufficiently similar such that I'll be able to pick up C++ on my own, and I am planning to do just that. Nonetheless, it would have saved me some time if I could have learnt C++ directly in class instead of learning Java and then teaching myself C++.

Secondly, I think more can be done to help students look for internships and full-time jobs. Currently, it is up to the students themselves to make use of the many opportunities available to us, e.g. getting in touch with alumni, approaching instructors who are practitioners. While the fact that these opportunities are present is well and good, I think the program can take more initiative in placing students. For example, instructors can actively look to the class to fill openings that may arise in their place of work, the program director can use his personal connections to learn of unadvertised openings and personally recommend a few students who are suitable for the job. In my view, a personal recommendation from the program director carries much more weight and is more efficient than having the program email us about job openings and collating our resumes for the employer.

What is your current job status? What are you looking for?

I'm graduating in 3-4 months' time so I'm currently looking for a full-time job, preferably in quantitative portfolio management.

Can you tell us a bit about your background?
undergraduate math major and started the program right after undergrad

Did you get admitted to other programs?
CMU, cornell, michigan, rutgers

Why did you choose this program (over others, if applicable)?
in the end it was a close call between CMU and NYU, mostly just based off reputation of the two programs. But in the end, i chose NYU mostly because of its location

Tell us about the courses selection in this program. Any special courses you like?
first semester 4 required core courses
second semester 2 core courses and 2 electives
3rd semester you get more choices
i would recommend any course taught by marco avellaneda

Tell us about the quality of teaching
it varies a lot. some professors were good teachers and really involved, but others can be difficult to learn from because they're just industry professionals who are obviously very knowledgeable but dont know how to teach the material

Programming component of the program
the first computing course is completely in java. you use a lot of matlab and excel in almost every other course

Career service
honestly, the career services didn't do much. NYU as a school has a wasserman career center that you may be able to get some on campus interviews for, but thats about it.

Can you comment on the social interaction between students of different ethnics, nationalities in the program?
its a small program so you get to know almost every one in the program and its definitely a very diverse group of people.

What do you like about the program?
the projects are long and tough but really prepare you well for your first job

What DON'T you like about the program?
professors teaching ability can be very hit or miss
career services isn't all that great. you're pretty much on your own to find a job (but the reputation of the program is very strong so it will help you to get interviews just by having the program name on your resume)

What are your current job status? What are you looking for?
just started working as an options trader

Can you tell us a bit about your background?
I had majored in math as an undergrad, and taken several graduate level courses. I knew that I wanted to do something heavily quantitative for a career. After college, I worked for a year at a European bank with a small US office doing municipal finance, which was a pretty good way to get some basic exposure to the financial markets.

Did you get admitted to other programs?
I was admitted to NYU, CMU, Baruch, Columbia (FE), and Rutgers.

Why did you choose this program (over others, if applicable)?
I liked the three semester setup, with the opportunity to do an internship. Moreover, I figured that being in New York would be the best bet for landing a job on Wall Street. I also felt like most NYU courses were taught by really famous practitioners, and that it was a great opportunity to get to know these people and learn first-hand from them.

Tell us about the application process at this program
The application process was pretty uneventful. I had a deadline to respond to a graduate school in February, and they provided me with an expedited response to meet that deadline.

Tell us about the courses selection in this program. Any special courses you like?
The courses cover a variety of topics. There are the traditional sell-side courses - mainly, a two-semester sequence in the pricing of derivatives: Derivative Securities and Continuous Time Finance, as well as more mathematical courses like Stochastic Calculus and PDE in Finance.

There is also a strong buy-side focus that most programs don't have (I think), with four courses - Risk and Portfolio Management, Active Portfolio Management, Algorithmic Trading and Quantitative Strategies, and Time Series and Statistical Arbitrage - the latter three are electives.

There are three required computing courses. There are also a number of electives, including risk management, interest rate and credit modeling, mortgage backed securities, energy trading. Most students are able to take 4 electives over 3 semesters.

Tell us about the quality of teaching
Almost all of the courses are taught by practitioners. As such, they are a bit less accessible than tenured faculty would be, although most of them make time for office hours and are quite responsive to emails. In the classroom, some teachers left something to be desired, while others were rather inspired lecturers. Overall, I was pretty happy with the teaching.

As an aside, we could choose a number of electives, and some courses had multiple sections. I tended to sit in on classes at the beginning, and make my course selections based on which professors I liked. So I didn't have any experiences with really bad teaching.

All the courses have a TA - usually a PhD student, sometime a 3rd semester student in the math finance program. Most of them weren't especially helpful.

Materials used in the program
There are some standard texts used in the first semester - Hull, Shreve (Vol II). Most courses, though, use instructor's notes.

Programming component of the program
There are three computing courses in the program - Computing in Finance, Scientific Computing, and Computational Methods in Finance. Many students place out of scientific computing.
Computing in Finance is the object oriented programming course, done entirely in C++.

There were regular assignments as well as a very large end-of-semester project, building an object oriented pricing library.
Scientific Computing was more of an introduction to numerical analysis. It involved weekly assignment in C++ and Matlab.

Computational Methods in Finace was the hardcore numerical analysis course. We implemented very recent numerical techniques and models - papers that were written in the last few year. There were three large assignments, all in C++.

Many other classes had computational assignments. These usually involved MATLAB or VBA, although at least one class used R. Risk and Portfolio management involved using a lot of MATLAB.

When you finish the program you will definitely have solid C++ aptitude (although you won't qualify as an expert), and you will be very good at MATLAB.

Projects
In the first semester, in the mandatory computing class, there was a group project involving building an object-oriented pricing library for a variety of projects.

A number of other courses involved doing an end-of-semester project instead of a final, or in addition to a final exam. An example of this was the Interest Rate and Credit Models class, where the final project was to build a Monte Carlo simulator for synthetic CDOs, or Time Series and Statistical Arbitrage, where we had to get market data, clean it, and develop a trading strategy using it.

Finally, there is a required course called project and presentation, where students work on a semester-long project - comparable to a master's thesis - with an advisor and some team members. We are able to choose our own projects and have to find our own advisers. Most students found advisers who teach in the program, although some found them from their internships or other networking. The projects are varied - some are very computational or data intensive, while others are rather theoretical.

Career service
The program is three semesters long - so students are encouraged/required to do an internship over the summer. Finding an internship was a challenge, mostly due to the uncertain economic climate. Recruiting for internships, though, picked up a lot in late April and early May. Finding a full-time job was much easier.

We have access to all of NYU's career services (except for the business school MBA recruiting), which are pretty comprehensive. A lot of companies recruit on campus for analyst positions, and they are more than happy to interview MS students. Some post jobs through NYU's career portal. A handful of places come on campus specifically to recruit Math Finance finance students. The program is well connected, and we frequently get notified of job openings at various places which we can apply to, as well as sending around a resume book from which some students have gotten jobs and internships.

The program runs a career workshop that meets every week for a several hours during the first few weeks of the program. In it, he goes over making a resume, networking, and preparing for quantitative and behavioral interviews.

Can you comment on the social interaction between students of different ethnics, nationalities in the program?
I can only speak for my graduating class - pretty much everyone got along. A couple of the chinese students tended to keep to themselves, but the rest of them were very social with everyone. As far as the handful students doing their own thing, some were older, some just chose not to be too social. Everyone else was very social with one another, and tended to work together on various projects/assignments.

What do you like about the program?
I think the opportunity to work with and learn really high-quality practitioners is a great aspect of the program. It's not every day that you get to be taught by people like Peter Carr, Bruno Dupire, Robert Almgren, just to name a few. Most of them are very approachable, and they all supervised student projects in the third semester.

There is also an effort to expose students to a lot of cutting edge stuff - particularly in the continuous time finance course, and in the computational methods course. Useful stuff to learn in general, and also useful to discuss in job interviews.

I feel like the career support was very good for an MFE/MSMF program. It wasn't business school recruiting, but there was a definite effort to provide professional career services. We were made aware of a lot of job opportunities, and we also had access to the NYU career center.

The approach in the program is very balanced, I feel. There is an effort to teach finance, mathematics and computing. In spite of it being housed in a math department, there is definitely NOT an axiomatic approach to teaching finance. In teaching material, there is definitely a philosophical emphasis on understanding the weaknesses of one's assumptions and model risk.

What DON'T you like about the program?
The workload is very heavy. There is no hand-holding either. Oftentimes, the TAs aren't particularly helpful with a specific assignment, so students have to work together (although this is arguably a useful skill).

As I mentioned before, some of the lecturers leave something to be desired. Some of the more complicated, drier material is hard to sit through a lecture through once you get lost. Another drawback with having a lot of adjunct professors teaching classes is that most of them are very busy outside of teaching. Some of them are really hard to get in touch with outside of class, and refer you to the TA, who usually isn't that great.

While you are provided with a number of resources and job postings, you are pretty much on your own to find a job. This works well for some students, doesn't work so well for others. It is very different from a business school - you have to be much more proactive.

While you are given a lot of assignments that involve programming (often at a high level), there isn't too much programming being taught. You are generally expected to learn C++ by yourself, it seems. Most people, even those who don't have an extensive programming background, get up to speed though.

Even though the program has a number of part-time students, there is pretty minimal interaction between part-time and full-time students. I honestly only know three (excluding full-time students who switched to part-time after finding a job).

Suggestions for the program to make it better
I'm not exactly sure what I'd do to make the program better - all in all, a year and a half isn't too much time to learn a lot of stuff AND interviewing for jobs and internships, so I think the program does the best with what it does.

There is an obvious tradeoff between having practitioners and faculty teach, and I think those running the program have decided to lean towards having more practitioners teach. I think there is an honest effort to evaluate teachers and get good lecturers.

A lot of students (myself included) were more interested in working in finance (as traders, structurers, risk, strategists) than being quants per se - so I'm not sure adding more programming instruction would necessarily be a positive thing. If anything, I would try and create a little more room for electives (although we probably have more than most), and maybe add one or two classes that are geared more towards students with these sorts of interests, or even create a slightly separate track for them.

What are your current job status? What are you looking for?
I have accepted a job offer to trade equity derivatives at a major investment bank, which is exactly what I wanted.

Most of my classmates already have jobs, and most of them are front-office jobs at well known banks.

Other comments
Overall, I was really happy with NYU Math Finance. I think it is a well designed and well-taught program. It is very intense, though. It's just a year and half, so I think it helps a lot to have some expertise in something (math, programming, finance) before coming in, and having some work experience helps too. It's hard to figure out exactly what you want in a short time period, so it's good to have some idea about that before starting.