Columbia University - MA in Mathematics of Finance

Columbia University - MA in Mathematics of Finance

The Columbia MAFN program is sponsored by the departments of mathematics and statistics

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Location
New York, NY 10027
Application deadline
May 9, 2024
The Department of Mathematics at Columbia University offers a Master of Arts program in Mathematics with specialization in the Mathematics of Finance (MAFN). It is co-sponsored by the Department of Statistics, and it draws on the diverse strengths of the university in mathematics, statistics, stochastic processes, numerical methods, and financial applications.

Admissions

The program attracts students whose academic background is in quantitative areas such as mathematics, statistics, physics, economics, computer science, or engineering. Most have previous work experience or internship experience in finance.

www.math.columbia.edu/mafn/admissions/application-procedures/
www.math.columbia.edu/mafn/admissions/admissions-statistics/

Full Time and Part Time

The program may be followed either full-time or part-time. International students on F-1 or J-1 visas must register full-time. Full-time students complete the program in two or three semesters, while part-time students typically take 2-3 years. In the past, most full-time students graduated after two semesters, but now most of them take advantage of the three semester option.

Governance

The program is overseen by a steering committee consisting of faculty from the departments of mathematics and statistics, including the two department chairs.

Curriculum

We strive for a balance between rigorous theoretical courses and cutting-edge applied courses, the latter in many cases taught by professionals from the financial industry. In addition to the finance, mathematics and statistics course offered by the program, the students can take courses from all over the university.

www.math.columbia.edu/mafn/courses/mandatory-mafn-courses/
www.math.columbia.edu/mafn/courses/elective-course-examples/

Structure

The three semester option: Full time students, including all international students, have the option to stay in the program for three semesters. Most of the students choose this option. It allows them to

(1) take four courses instead of five in each of the two first semesters,
(2) do internships during the summer and the third semester,
(3) take additional elective courses beyond the degree requirements, and
(4) conduct a thorough and well informed job search during the third semester.

In connection with the three semester option, we have introduced an MAFN Fieldwork course (CPT), which allows both domestic and international students to do paid internships in the financial industry and earn credit towards the degree.

The number of finance semester-courses offered directly by the program as electives has grown from 3 per year to around 11-12 per year in 2019-20.

In addition to elective courses offered by the departments of mathematics and statistics, many students also take electives from computer science, engineering, finance (B-school), economics, etc., including courses in data science and machine learning.
2025 Ranking Data
Rank
9
Total Score
77
Peer Score
3.4
% Employed at Graduation
49%
% Employed at 3 months
75%
% Employed in the US
60%
Compensation
$129,249
Cohort Size
102 FT, 7 PT
Acceptance Rate
22.1%
Tuition
$98,930

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49,845
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Ratings

4.00 star(s) 6 reviews
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Latest reviews

J
It has been a long time since the last review for this program, so I hope to provide some up-to-date information. Feel free to message me if you have any questions and I’ll try to get back to you. Just refrain from asking me to evaluate your profile, for files from any classes, or for more information on my background.


Things to note:
- Now that there is the 3rd semester option, it is no longer mandatory to take at least 5 courses per semester, thought 4 are required to have full-time status
- The MAFN program offers its own electives in the spring semester
- Career services have improved since the last reviews were posted and the program continues to build up its own individualized career services


Background
Engineering undergrad and IT work.


Did you get admitted to other programs?
Yes


Why did you choose this program (over others, if applicable)?
NYC location, university reputation, foundation in mathematics, flexibility in course selection


What alternative sources of info you used to learn more about the program?
QuantNet, Columbia MAFN website


Tell us about the application process at this program
Very straight-forward process outlined on the school website. Typically find out if you’re admitted around late May.


Tell us about the required courses in this program.
Fall semester:
MATH GR 5010 – Introduction to the Mathematics of Finance
A thorough, straight-forward overview of various product types and how they are priced, arbitrage, implementation of continuous-time stochastic processes, basic risk management, and basic portfolio construction. Taught by Professor Mikhail Smirnov, sample code/coding for homework is done in MatLab, but what programming language you use for the final project is up to you.

STAT GR 5263 – Statistical Inference/Time-Series Modelling
Course on modelling and inference for random processes. Has a good balance of theory and practical application. Professors vary by semester, but the course content is pretty much the same regardless of the professor you have. Most practical materials, as well as some exam and homework questions, were in R.

STAT GR 5264 – Stochastic Processes - Applications I
Course focused on the foundations of stochastic calculus and continuous-time stochastic processes. This class was the one that seemed to vary the most depending on which professor you had. I had Professor Lars Tyge Nielsen, who provided and taught from his own textbook chapters. His section seemed to focus more on the theory than the other section based on conversations I’ve had, but I found it to be a very thorough and interesting class.

Spring semester:
MATH GR 5030 - Numerical Methods in Finance
This course is still the same as it was when the last review for the program went up. It focuses on interpolation, root solving, finite differences, and some simulation depending on if there is enough time left in the semester. It goes into both the theory of the different techniques presented and the implementation of the techniques in Excel using VBA. Professor Tat Sang Fung is still the professor and is still a practitioner.

STAT GR 5265 – Stochastic Methods in Finance
This course focused mainly on the practical implementation of stochastic methods within finance, along with some mathematical and probabilistic tools for analyzing option markets. This includes pricing options in complete and incomplete markets, equivalent martingale measures, utility maximization, and term structure of interest rates. Can be some overlap with STAT GR 5264 in the beginning.

MATH GR 5050 – Mathematical Finance Practitioners Seminar
A seminar series inviting practitioners in the field of quantitative finance and some senior professors from other universities to discuss the work they do. As a result, the content varies from year to year, but it is still a great opportunity to hear from and speak to those in the industry.


Any elective courses in this program you like?
I liked all of the electives I took, but a few that stood out were:

MATH GR 5220 – Quantitative Methods in Investment Management
The whole class centers around a group project where you need to implement a trading strategy that includes accurate, unadjusted point-in-time data, forecasting, portfolio allocation, transaction costs, risk management, and performance analysis/reporting. Beyond this, the project is open-ended in terms of what sectors/products you want to focus on, programming language you want to use, etc. Professor Alexander Greyserman thoroughly explains what he is expecting and common pitfalls in the first few weeks, then proceeds to invite guest speakers consisting mostly of current financial practitioners who provide insight into how the aspects of the project are handled in practice.

IEOR E4732 – Computational Methods in Finance
Professor Ali Hirsa presents applications of a wide variety of computational techniques that are commonly utilized in quantitative finance, including transform (FFT, FrFT for de-noising and pricing), finite difference methods (for PDEs and PIDEs), Monte Carlo simulation, calibration, filtering, and parameter estimation techniques. Final project revolves around taking an existing code for a technique covered in the course and expanding upon it in a meaningful way. Lecture material and the final code are given in Python. I’d recommend taking this course after the Numerical Methods in Finance course, since it contains topics in that course, expands upon them, and adds more methods.

MATH GR 5360 – Mathematical Methods in Financial Analysis
Primarily focused on econophysics, this course provided by Alexei Chekhlov relates current statistical methods used in quantitative finance to different concepts seen in the worlds of engineering and physics. These include position sizing, statistical fluid mechanics/turbulence, Brownian/Random walks, variance ratio tests, memory effects, mean reverting vs push-response functions, and Levy distributions. Final project consists of developing and testing a trading strategy using concepts presented in the course.


Tell us about the quality of teaching
I found the teaching in my MAFN courses to be fantastic, with all of them having a firm grasp of the material, practical knowledge to offer, and willingness to help students outside the classroom if asked. There are also TAs for all classes, all of whom I’ve found to be incredibly helpful and often go out of their way to assist you understand material if you are willing to reach out to them.


Materials used in the program
For most classes, the professor will provide lecture notes/slides. Beyond this, the only outside materials from the required courses are:
MATH GR 5010: Options, Futures, and Other Derivatives by John C. Hull
STAT GR 5264 & 5265: Stochastic Calculus for Finance I and II by Steven Shreve


Projects
Most projects involve creating and back-testing trading strategies, with various degrees of complexity depending on the course. The only project from the required courses is the final project in MATH GR 5010, which is a straightforward creation of a trading strategy with some ties to topics covered within the course.

The practical portions of the MATH GR 5030 homework could also feel like projects, where you are to implement the numerical method you are currently learning that week within Excel/VBA.


Career Services
I see the Columbia Career Services get criticized a lot on here, to the point that many say they are no help at all. I have to respectfully disagree in this regard, as I have been able to take advantage of many great programs like resume help, mock interviews, career fairs, networking/social events, and Lionshare (job website) offered by the University-wide Career Services Center. There are also clubs like the Columbia Quant Group which hold networking and information sessions specifically for quantitative professionals/students.

From the MAFN program, I have been able to participate in employer information sessions and employer open houses aimed specifically towards MAFN students. The MAFN program has also recently hired a full-time career services counselor who provides a listing of job openings, outside employer events like information sessions and hackathons, and holds networking sessions between current students and alumni of the program.

Ultimately, career services and the MAFN program provide plenty of opportunities for you to get your name out there and put your best foot forward in the job hunt.


What do you like about the program?
- Its focus on mathematics and statistics.
- Flexibility in choosing which courses to take.
- Opportunities to meet with companies at info sessions/networking events and to hear from some of the most respected names in the industry through seminars.
- The many resources and opportunities available at Columbia University to explore things outside of your major requirements/courses (ie. I was able to participate in research).
- Projects within classes that have clear practical purposes and allow for flexibility in approach.


What DON’T you like about the program?
- Courses from the statistics department heavily favor R programming over other languages
- Though the number of electives offered in-house by the MAFN program has improved, it still has its limitations.
- The process to register for courses from the Business and Engineering School is not the easiest to find and you are limited to only one course from each in any given semester. You basically have to fill out a Google form for each school where you list 3 courses you’d like to take and hope your #1 choice has an open spot after the 2 weeks of registration are up.


Final Thoughts
I greatly appreciated the time I spent as a student in the Columbia MAFN program and hope that this write up offers some up-to-date new insight into the program. Another post I found helpful and which I think should be posted as a review can be found here:
https://quantnet.com/threads/some-information-about-columbia-mafn.20585/
Upvote 5 Downvote
fastrack
Things worth mentioning:
- Lars Nelson is the new director of the MAFN program
- Application process has been changed
- MAFN website has been updated
- Employment statistics are now being collected


Can you tell us a bit about your background?
Worked in Risk Management for 3 years at an international investment bank in NYC.
Studied Business Administration at a US university.
GRE: 167 quant, 160 verbal
I studied full-time in the MAFN program from 9/2012 to 5/2013
I studied full-time in the QSF (Quantitative Studies for Finance) program from 9/2010 to 5/2012


Did you get admitted to other programs?
Yes


Why did you choose this program (over others, if applicable)?
Location, brand recognition, familiarity with campus


What alternative sources of info you used to learn more about the program?
Quantnet, Columbia MAFN website


Tell us about the application process at this program
Usually find out very late into the year.


Tell us about the courses selection in this program. Any special courses you like?
Fall semester:
MATH G4077 - COMPUTATIONAL FINANCE – not typically offered, but definitely worth taking if it is offered. You will learn about Monte Carlo simulations and how to implement them (you will get very familiar with c++ and object oriented programming)
MATH W4071 - INTRO TO THE MATH OF FINA
STAT G6503 - STAT INF/TIME-SERIES MODE
STAT G6501 - STOCHASTC PROCSSES-APPLIC
STAT W4315 - LINEAR REGRESSION MODELS

Spring semester:
STAT W4249 - APPLIED DATA SCIENCE – new course, I thought this class was awesome. You will learn how to use linux, how to code in python, what github, natural language text processing, and L1/L2 regularization is, and more.
IEOR E4718 - INTRO-IMPLIED VOLATILTY – a good course on equity derivatives, the Black Scholes model and the extensions of the Black Scholes model that account for the volatility smile.
MATH G6071 - NUMERICAL METHODS IN FINA – a nice course focused on interpolation techniques, root solving methods, and finite differences. You will get lots of practice using Excel/VBA. Professor Fung is a practitioner (senior manager at Misys) and has useful real-world knowledge (compared to some of the other professors who have been out of the industry for quite some time).
STAT G6505 - STOCHASTIC METHODS IN FIN
MATH G8210 - MATH FINANCE PRACTITIONER
HRMG B8412 - Managerial Negotiations


Tell us about the quality of teaching
Depends on the professor. Some of the core classes only have one professor.


Materials used in the program
For most classes, the professor will provide lecture notes/slides.
John.C Hull - Options, Futures, Derivs (Intro to the Math of Fin.)
Shreve – Stochastic Calculus for Finance


Projects
Trading Strategies (Intro to the Math of Fin.)


Career service
Columbia’s career service is solid: resume help, mock interviews, career fairs, employer presentation sessions, networking/social events, and Lionshare (job website).

The MAFN program does help out with job placement as the program has a strong alumni network. They will email you about openings and job leads but make no mistake, this is the Columbia math department and not the Columbia Business School.


What do you like about the program?
The MAFN covers all the important topics: stochastic processes, time series, numerical techniques, Monte Carlo simulation, option valuation, and etc.
At Columbia, you have the opportunity to meet a lot of smart and motivated people (including undergrads and phds) and interact with top notch faculty.
You are minutes away from the top financial companies of the world.
Tons of resources at Columbia University.
Extensive alumni network.


What DON’T you like about the program?
The only knock on the MAFN program is that it doesn't have a huge selection of elective courses and there are limitations on taking courses with the business school and engineering department. You are allowed to take one MBA course per semester and one IEOR elective course in the spring semester. Otherwise, you must be affiliated with IEOR or CBS in order to take their courses.
It would be nice to have an in-house programming/database class and an exotic products (MBS, CDO, etc.) class. But it would make so much more sense if MAFN students were allowed to take FE and business school electives instead of duplicating courses across departments.



My personal remarks:
- Calibrate your expectations.
- You must take at least 5 courses per semester and a few of the course classes are phd level. The phd level courses are very theoretical so know what you are getting into. The MAFN program is very intense and you will have to manage your time very well if you want to attempt to secure a job offer before graduation.
- The MAFN career service will not be able to place everyone. Just because you get into Columbia MAFN doesn’t make you instantly smart and you sure aren't guaranteed a job. You have to work and hustle to get a job just like everyone else.
- There are so many programs at Columbia that teach more or less the same things: Stats, FE, OR, Applied Mathematics, Management Science and Engineering >> and that’s just the master programs!!! So don’t rely on just Lionshare to find jobs. Use linkedin, monster.com, etc. And of course, network.
- In my opinion, everything comes down to the individual. It’s not so much which program you are in but your knowledge, skills, and ability. I know a student who is just brilliant. He had multiple offers, ranging from AQR, SIG, CS Quantitative Strategies, and MS Strats & Modeling. It didn’t matter which program he was in because he was just that smart. You could put him in any of the lower ranked programs and he would still get job offers because he understood everything inside out. Find out which area you are weakest at (math/finance/programming/communication) and get better at it.
- Columbia has tons of resources >> use them. For example, you need a subscription to view articles on InstitutionalInvestor.com but when you are on campus using the wifi, you can view articles for free. The same goes for many journals and publications.
Upvote -1 Downvote
A
Flexible, cheap and very effective

What do you think is unique about this program?
I don't think there is anything unique in the program as most of the MFE and Math Finance Programs are pretty much identical. The best part though is its flexibility. You can take the best courses in MAFN and in MFE and pay substantially less than what columbia MFEs pay.You can learn a lot in this program by taking good courses or you can just take fraudulent courses under industry practitioners and learn nothing.

What are the weakest points about this program?
There are absolutely no electives offered by the department in the 2nd semester. Its not easy to get registered into the MFE courses but if you go to their classes in the first couple of weeks and talk to the professor, you can eventually get registered into the course.

Career services
Career services in general suck at Columbia

Student body
Chinese French US Russian and Indians
Upvote 0 Downvote
A
A very intense phd level Math-Stat Program with concentration in finance

What do you think is unique about this program?
To this question - I don't know how it is in other programs. But I certainly felt very motivated may be coz of that calmness inside the campus and huge amount of energy right outside the gates to broadway. It is definitely unique. Curriculum, it is very demanding, get the heck outta u. One administrator in Kent hall told me it is The most intensive program in the university. Course wise, Whatever course offered are really good and professors are top notch, but when it comes to electives, i see that there is no preference for math fin students when apply for courses in other departments.

What are the weakest points about this program?
Electives in Finance courses, I don't know whether it is that much a hassle to tie with B School or IEOR to intake good amount math fin students for just 2 courses. Secondly career service.

Career services
University career service - Lion Share but again it is meant for ALL Columbia students and Alumni - We have to compete with MFE & BSchool (who also has separate career services) + MA Stat, MSOR, MA Econ, Bachelors in Business/finance etc. So at the end, to get a call for interview from Lion share is like "-------" . I still hope it works.

Student body
I see many students founds jobs in their own countries like Russia, HK, Thailand, Toronto and the like. I know only a couple who got jobs in USA. I think the time is really really bad.
Upvote -1 Downvote
D
Excellent brand, smart people and in NYC.

People say the careers service isnt good but actually found it helpful and got a number of offers through them. I think the problem is people are too late. If you want a full time position then you start interviewing on campus from the first week you arrive and positions are taken by Christmas. Then you are on your own, but even that is okay being in NYC is very easy to go for interviews and networking things.

Other than that I think the program is tough, the people are smart and it has a good brand name.

My background:
1st Class (Honors) Math undergrad in the UK. Internship at Goldman Sachs. 800 on math GRE.
Now working as a currency options trader.
Upvote 0 Downvote
A
Can you tell us a bit about your background?
Worked as a Business Analyst for 2 years in Financial Services before joining the program.
GRE: 800 quant, 650 verbal.
I studied full-time in the program from 9/2009 to 5/2010

Did you get admitted to other programs?
Yes

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

What alternative sources of info you used to learn more about the program?
Quantnet, Forbes Magazine, etc

Tell us about the application process at this program
Respond via email, waitlist candidates usually find out very late into the year

Tell us about the courses selection in this program. Any special courses you like?
Stochastic Finance was very interesting, and very challenging course.

Tell us about the quality of teaching
Depending on the professor, the courses can be extremely interesting or incredibly boring. TA's can be helpful in some courses but not all.

Materials used in the program
John.C Hull - Options, Futures, Derivs Stochastic Processes - Lawler

Projects
Development of Trading Strategies

Career service
Not helpful at all. Very minimal support by the University or the program.

What do you like about the program?
I liked applied courses, where we could see the theory applied in practice

What DON’T you like about the program?
Career Service and Support

Unfortunately the Faculty, and the Department that sponsors my program was not helpful at all. Besides the occasional email about a job posting, or career fair there was really nothing much they did. All the students are pretty much on their own as far as finding a job is concerned.

That was my biggest gripe with the program. I understand markets are tough, but we are paying quite a bit of money to the University, and I feel like we should get more help than we did.

Also I didnt particularly like how at Columbia, you must be affiliated with a program in order to take their courses. Some really nice courses like Quantitative Risk Management, Advanced Derivatives,etc. were only offered by the Business School, and the School of Engineering. Students from our program we're not allowed to take these courses.

It was not all bad though, the core courses that a Quant is required to take (Stochastic processes) were taught by a very high quality professor and staff. I also liked how Columbia does push students to their limits as far as academia is concerned. Hard work is definitely rewarded.

Suggestions for the program to make it better
Improve the Career Service, and make it easier for Students to take courses from other departments

What are your current job status? What are you looking for?
Employed full-time as an associate

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