NYU Courant - Mathematics in Finance Master's Program

NYU Courant - Mathematics in Finance Master's Program

Application deadline
See below

The Master of Science Program in Mathematics in Finance is a professional master’s program at the Courant Institute of Mathematical Sciences, New York University.

Quick Glance:
Available programs of study:
Full Time Masters in Mathematics in Finance (we accept applications for the fall term)
Part-Time Masters in Mathematics in Finance (we accept applications for each semester)
Advanced Certificate in Financial Mathematics (we accept applications for each semester)
Non-Degree Study (we accept applications for each semester)

Petter Kolm, Director of the M.S. Program in Mathematics in Finance

Male: 21
Female: 20

China: 35
France: 1
India: 2
Nigeria: 1
Rwanda: 1
Singapore: 1

Mathematics: 29
Actuarial Science: 1
Chemical Engineering: 1
Electrical Engineering: 1
Economics: 4
Finance: 1
Mathematics in Finance: 3
Statistics: 1

Full-Time Masters in Mathematics in Finance: February 8th. Applicants are encouraged to submit their applications well before the deadline. Full-time students are accepted only for a Fall start date. If you have been accepted by another program with a deadline for a reply, but would prefer Courant, please contact us, mathfinapp@cims.nyu.edu as soon as possible.

Part-Time Masters in Mathematics in Finance: August 1 for Fall, December 1 for Spring.

Non Degree and Certificate program: August 1 for Fall, December 1 for Spring.

3-Day Pre-Term Courses
Offered by adjunct professors
  1. Probability
  2. Finance
  3. Computing

Level 1
Courses Offered Fall Semester
  1. Derivative Securities
  2. Risk & Portfolio Management with Econometrics
  3. Stochastic Calculus
  4. Computing in Finance

Courses Offered Spring Semester
  1. Derivative Securities
  2. Risk & Portfolio Management with Econometrics
  3. Stochastic Calculus

Level 2
Courses Offered Fall Semester
  1. Scientific Computing (4)
  2. Continuous Time Finance (1, 3)
  3. Fixed Income Derivatives: Models & Strategies in Practice (Half-credit course 1, 4)
  4. Credit Analytics: Bonds, Loans, and Derivatives (Half-credit course 1, 4)

Courses Offered Spring Semester
  1. Scientific Computing in Finance (4)
  2. Continuous Time Finance (1, 3)
  3. Interest Rate & FX Models (1, 3, 4)
  4. Advanced Risk Management (1, 2, 4)

Level 3
Courses Offered Fall Semester
  1. Project & Presentation
  2. Time Series Analysis & Statistical Arbitrage (1, 3, 4, 6)
  3. Nonlinear Problems in Finance: Models and Computational Methods (5, 6)
  4. Regulation & Regulatory Risk Models (1, 2)
  5. Advanced Econometric Modeling and Big Data (1, 2, 4)
  6. Data Science in Quantitative Finance (1, 2, 4)

Courses Offered Spring Semester
  1. Project & Presentation
  2. Algorithmic Trading & Quantitative Strategies (2, 4)
  3. Securitized Products & Structured Finance (Half-credit course 1, 3)
  4. Energy Markets & Derivatives (Half-credit course 1, 3)
  5. Advanced Topics in Equity Derivatives (Half-credit course 1, 3, 4)
  6. Market Microstructure (Half-credit course 1, 2, 4)
  7. Active Portfolio Management (1, 2, 4)

The default curriculum for full-time Mathematics in Finance MS students in the Spring semester is to take Continuous Time Finance, Scientific Computing in Finance and two of the other Level 2 or 3 offerings.
Under appropriate circumstances students may substitute more advanced courses for some of those listed above. Permission is granted on a case by case basis.
Click HERE for more information on degree requirements.
Click HERE for information on rooms and instructors.


Offered every Tuesday, see Calendar.

Career Workshops
Offered every Friday, full-time students only
Focused on networking skills, behavioral/technical interview skills. Mock interviews for 1st semester students will be conducted by 3rd semester students before the final of the 1st semester

For tuition information, please click HERE.
All graduate courses are 3 points. Typically, full-time students take 4 courses per semester.

Contact Information
General inquiries: mathfinapp@cims.nyu.edu
Michelle Shin, Program Administrator
(212) 998-3009

Mailing information
New York University
Graduate School of Arts and Sciences
Graduate Enrollment Services
P.O. Box 907, Cooper Station
New York, NY 10276-0907


Videos with our faculty

Professor Gordon Ritter on the special panel "Artificial Intelligence: Will It Deliver On Its Promise for Finance?"

Professor Fabio Mercurio speaks about models and interest rates

Professor Marco Avellaneda delivers a minicourse on the statistics and trading of volatility futures and ETNs

Professor Aaron Brown interviewed by Bloomberg TV
4.64 star(s) 11 ratings
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Latest reviews

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 came in with a PhD in Math

Did you get admitted to other programs?

No, I only applied to NYU.

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

It was the only program I applied to. :)

What do you think is unique about this program?

Definitely the chance to learn from practitioners in the field, as opposed to professors. Since this program is career-focused, it makes sense to learn techniques that employers will want us to be able to do on the job, and not just the theory behind it.

Tell us about...

Quality of teaching:

The quality of the teaching is a bit mixed. Some of the instructors are very good and some are not. I think this is the risk you take when you have courses being taught by practitioners and not professors. But it's a worthwhile trade-off I think.

Two issues this brings up though: (1) many instructors are not available outside of class and many TA's are also fairly unavailable because of their career obligations so if you don't understand something in class you could have a very difficult time discussing it again; (2) it takes a VERY long time to receive feedback. It can take weeks to get homework back (one homework took 6 weeks to be returned). This latter issue is probably the biggest negative I have found with the program, but there's probably not much to be done with it.

Programming component of the program:

There is a lot of programming offered in this program, all presented from a practical point of view. There is the Computing in Finance course offered first semester, which is a introduction to Java from a finance perspective. Matlab is introduced in Risk and Portfolio Management, although it's not taught specifically. Rather, you are told to use it and are expected to pick it up as you do the assignments. This is fine for some uses but not for others (for example, it's hard to learn how to vectorize your code in this way). Matlab is also the main programming language in Scientific Computing and Algorithmic Trading, and is the preferred language in the Time Series and Stat Arb course (although C++ is also acceptable). The Computational Methods for Finance course allows one to use Java, C++, or Python. I used Java to sharpen my Java skills, but one could also use this as an opportunity to learn Python.

Career service:

I honestly didn't use career services too much, as I received an internship offer very early and then it became a full time job. But there is a resume book that is sent out to companies and that provided me with a few interviews. There is a career workshop that introduces you to the fundamentals of getting a job, such as writing resumes, networking, interviewing, etc. I think overall the career support is strong, although other students have criticized the career services for being inferior to other programs. The key point is that the school will provide you with resources and advice, but will not hand you a job. Because of that, some students will feel like they're doing it all on their own. But I think that if you follow the advice, you will get a job.

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

I am already hired. I will be working for the Client-facing Strats team at Goldman Sachs.
Can you tell us a bit about your background?

I came in with a BS in Math

Did you get admitted to other programs?

Columbia, Chicago, got to the interview stage at Princeton. Didn't apply to CMU/Stanford.

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

Focus on the math aspect with some computing. It's a well-rounded program. Isn't entirely derivative-pricing focused like some other programs.
Being in New York is definitely a huge plus (networking, and life in the city in general).

What do you think is unique about this program?

A good balance of math (not more than necessary) and computing in different languages. Opportunity to learn about different fields of finance (ask yourself the question if you're interested in trading, pricing, risk, asset management, or something else).

Another thing to consider is that most professors have work experience in the industry, which is something that not all programs have. This helps better connect the theoretical aspects of the lectures with the practicalities of finance.

Courant Institute is also famous (ranked #1) for applied math, so there's a lot going on (seminars in different fields of math/applied math for instance).

Tell us about...

Quality of teaching:

As stated before, good balance between theoretical/applied. Most theoretical developments taught serve a purpose in the financial world.

Programming component of the program:

A lot of programming in different languages: Java and Matlab mostly, and for some classes you may have a choice (Python, R, C++). However, definitely not the programming you would learn in a CS major.

Career service:

A resume book is available online and usually gets you a ton of interview. The program coordinator (Michelle) is really helpful too. Overall, I think this program has been running for over 10 years and benefits from a diversified network of alumni.

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

I will be working in trading.
Can you tell us a bit about your background?

A math and computing major from an IIT, I did my undergraduate degree in India. After that, I applied to the NYU program, got admitted and came to the US. No prior work experience
GRE Math - 800 ; Verbal - 670

Why did you choose this program (over others, if applicable)
I had applied to 5 programs - Stanford, CMU, NYU, Columbia and Princeton. Out of these, I got calls from NYU, Columbia and CMU. I had an interview call from Princeton but I had already accepted CMU by then so didn't go ahead with it. When i had to decide on my final choice, I was looking for certain specific things - a rigorous program, good professors, small batch size and good industry connections. NYU - a perfect amalgamation of maths and computing, best professor pool who provide a good mix of both theoretical and practical knowledge, well designed batch size (ours had 26) and fabulous industry connections.

What do you think is unique about this program?

Most of the first-tier FE programs have the same course structure, the same company pool where they send their resume books and pretty much the same alumni spread. What sets a program apart is the student himself. When asked about, say, the SABR model in an interview, an average FE student will write down the parametrization equation, but what sets apart a NYU FE student is that, not only will (s)he write the model down, but would also be able to explain how the model is calibrated using market data and discuss the pros / cons of the model versus other models like Heston. This matters, specially if you're in a group of 100 interviewing for a total of 10 jobs. You gotta know your stuff

What are the weakest points about this program?

Comparatively less focus on placement. The program name gets you the first interview call from almost all places. After that, its pretty much upto the student to convert it into an offer. NYU students have the best resources in terms of study materials / professors, but the program can definitely be more pro-active in the job search, specially given its excellent industry connections. I don't know of any program that guarantees a job. All I'll say is that if you're at NYU FE and have a good background, there is a VERY high chance of getting interview calls from ALL the places you apply to.

Other Comments

I was happy with my decision to do the NYU program. It was a rigorous program, but the small class size enabled everyone to make close friends. It was an enjoyable 3 semesters. I am presently a desk strat at Morgan Stanley NY.
Can you tell us a bit about your background?

I was a math major with a stat minor in college back in China. With limited internship experience, I got an early admission to this program with surprise. I suppose guys on the admission committee do weigh high on our math skills, cuz I happened to see the candidate review file and there's only "math GPA" tag but no "overall GPA" tag.

Did you get admitted to other programs?

MFE: UChicago, UMichigan, USC, Rutgers, Notre Dame
Stat: Stanford, Duke

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

I switched from math/stat to finance because I didn't want to stay in theoretical fields, and would like to see how my quantitative skills can be applied to practical problems. I chose NYU since NYC is the world's financial hub, it is my understanding that the fast-paced environment here would get me a quick start of a career in the financial industry.

What do you think is unique about this program?

• Awesome adjunct professors: our program is perhaps the only program with such a large presence of successful adjuncts from the industry. Their views on the course topics from a practical perspective definitely keep inspiring us.

• Part-time program: the part-time and non-degree students take classes with us. It also offers a great chance for us to talk and work with people with years of experience in this industry. Plus, some of them might get you an interview.

• Rigorous math training: being ranked #1 in applied math, Courant does offer financial courses taught in rigorous math. This helps us develop a more detailed oriented way to approach the problems.

Tell us about...

Quality of teaching:

Our professors have done a good job in organizing the topics and assigning the homework problems. I always appreciate the heated online discussion on the assignments, which gets us to dig deeper into these highly practical and course-relevant problems. Being really serious about the assignments just forces us to learn by ourselves. Btw, Tuesday seminars conducted by industry practitioners are also inspiring.

Programming component of the program:

Petter (the director)'s courses usually requires Matlab cuz he has got a preference for it lol. Computing courses usually go with Java. Stochastic Calculus requires a bit of exposure to R. Interest Rate course asks for Excel VBA.

Career service:

• NYU Wasserman, open to all NYU students where we get on-campus interviews. There are also career fairs held by Wasserman sometimes.

• MathFin network, open only to full-time students in our program. Companies will send a panel of representatives and present at Courant, talking about the job opportunities and getting to know us. Or they might simply send interview invitations.

What are the weakest points about this program?

• Very few adjunct professors might not have enough time to prepare for the lectures.

• The primary programming language taught is Java, and the most commonly used package is Matlab. I'd recommend adding C++ and Python as C++ is required by a lot of quant openings, and programming in Python does not take up as large space as .mat files do.

• As the class size increases, we'd better have career staff targeted at placement of students, instead of having Michelle (the admin) do all the work.

• Interviews of candidates to our program are definitely necessary, and I'm happy to see that we will have interviews for future applicants. So this is not a weakness anymore lol

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

I have an offer from the quantitative advisory team at Ernst & Young. I'm looking for a dynamic team where I can take on a client-facing role and also apply my quantitative skills. If it's not client-facing at least I hope I can interact with internal staff firm-wide.
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?

At the time of my application, I had worked for three years at a distressed debt hedge fund and was a Math, Computer Science, and Economics major from a top undergrad program in the US. Due to the fact distressed investing tends to be more fundamentally focused, I decided a formal education was probably the best way to learn about the quantitative side of things. I was admitted to the NYU MSMF full-time program though I ended up deciding to work while taking about 2 courses each Fall/Spring semester, 1 course each Summer semester. After two years of hard work, I graduate this month and will be joining JPMorgan as a VP Quantitative Analyst.

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

I was looking to get into a top program in New York that also provided flexibility to take classes part-time if I wanted. That narrows down the choices somewhat to NYU, Columbia MathFin, CMU, and Baruch. Of those four, I actually only applied to the first two, because NYU was my top choice and even if I were rejected, they give you the option to take four classes first on a non-degree basis and then receive credit if you do well and get admitted to the program the following year. For my consideration, NYU provided the best all-around combination of brand, alumni network, location, teaching style, and classmates. If I were deciding where to apply now purely as a full-time student, NYU would still be my top choice, with Princeton and CMU as top options as well.

What do you think is unique about this program?

Having a good school brand and large alumni network are definitely important factors for job placement, but all of the top programs have this. What some other top programs don’t necessarily have are: 1) great location for networking and job interviews and 2) having a small graduating class size. Having a small class size produces a more collegial environment where you actually know all of your classmates and everyone tries to help each other out. The last thing is the quality of the professors. Not to take away from the full-time faculty, but some of the best classes I have taken at NYU and what really differentiates NYU from other schools were from top-notch professionals who work in industry and who enjoy teaching so much that they basically volunteer their free time to do it. The disadvantage to having industry professionals as instructors is there is not as much time allocated to office hours, but we have dedicated TAs, and in my opinion learning how things are really applied in industry outweighs this drawback.

What are the weakest points about this program?

Probably the weakest point for this program in my opinion has been not enough focus on career placement, but that is also an area that is improving. Our program director is a well-known ex-Goldman alum who could be better at using available resources to source opportunities for internships and full-time positions. Currently, there are position postings available only to MSMF students as well as campus-wide postings, but the expectation has always been that the onus falls on the student to secure their internship and job opportunities. A couple years ago, the economics (supply and demand) was such that placement was pretty much guaranteed to be 100% year in and year out. Given that the landscape has become much more competitive, the reality is that all quant finance programs are focusing more of their resources on securing placement for their students. From anecdotal evidence, I know NYU has become more active in terms of finding opportunities for students, and so I expect that will continue.

Other Comments

I was happy with my decision to do the NYU program, even though it was definitely very challenging to balance the rigorous class workload with my job. If you have any questions, feel free to send me a PM.
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
I really enjoyed my time at Courant.

We have some amazing professors with a good balance of academic and practical experience. They are all well-regarded in the industry, but are still very approachable. There are also many classes to choose from that allow you to direct your focus.

Because of our small class size, all the students know each other well. There are also usually PhD and part-time students in our classes which provides a great opportunity to network and learn more about the industry.

In interviews, I found that NYU was always highly regarded and I felt well prepared for work after graduation.

I have absolutely no doubts that I made the right choice in picking NYU.
What do you think is unique about this program?
Weekly seminars run by practitioners in the industry and career workshops that talk about how to write a resume, "sell" ourselves, organize contacts, etc. One-to-one appointments with career consultant are arranged weekly so that students can have their personal questions answered. First semester students will go through mock interviews before real interviews.

What are the weakest points about this program?
The adjunct professors are very busy since they work full time during the day. So they may not always be there when you need them. (But the positive side is that they may hire you back.)

Career services
Students receive frequent emails from admin about various job opportunities, and on campus interviews can be arranged.
We got jobs mainly through online application, corporate connections. Some students got hired by adjunct professors.
The jobs MSMF students get are quite representative of roles in the entire finance industry, such as qr, desk strats, s&t. A few students got highly demanding quant positions.

Student body
A large portion of students are international students, mainly from Asia, particularly China. But the majority of these international students have done a undergrad or graduate degree in the States.
Over half of the students are math majors, and most students have done dual or even triple undergrad degrees. Some students join the program directly from undergrad institution, while others holding a master or phd degree, in quantitative fields like physics, ee, cs, etc.