Math Masters vs Quant Masters

I said in a recent video and in many past videos that program rigor is important. And it is! A subscriber asked the question, "would a math masters be better than a quant finance masters because it has more rigor?"

First off not all math masters are more rigorous than quant masters but I get the main point that most math programs will be rigorous. A math masters (either pure or applied) is a possible path into quant finance as well as other hot fields like data science. The one drawback is that these fields (industries) need an array of skills in math, stats, CS, and finance (or the industry focus). A math masters will teach you the math portion however making sure you cover relevant topics is important but you also need to make sure to cover stats, CS and finance. Some of these will be easier to obtain than others.

Now there are math heavy areas of quant finance like financial engineering where a math masters would be preferred given you have a great attitude and can be taught the other skills.

Should you get a math masters or a quant masters? It depends on your interests. If you enjoy a topic you will often do better at it in school and in the industry. If you absolutely love math the a math masters could be a great fit. The one big downside of a math masters could be finding a job in other industries if you decide later on that you don't want to work in quant finance.

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[steez]

I chose the MS in applied math route. The pro of my decision I have seen is a much deeper understanding of the theory. All the MS in quant finance programs I looked at felt like they shoot for breath but lack depth. You will cover way more topics in 1.5 years but at a much more shallow level and faster pace. With a math masters at least you can say you truly understand 10 classes super well rather than walking away wondering what in then world you just learned. A quant finance degree just seems like your drinking from a fire hose and not remembering everything you should. I think the ideal is to attend a MS in applied math program at a school that has a quant finance program that allows you to take electives in the quant finance program. That way you still get really good depth in math and stats and then just take some stochastic calculus electives and maybe a computational finance class where you implement some code for derivatives pricing and you should be good! My path: financial econ undergrad, applied math undergrad, applied math grad student and hopefully quant when I graduate! I'm happy with my decision to do a MS in applied math. Better to be really good at a few things rather than average at 20 different things in my opinion.

Edit (2023) : I wrote the original post as a grad student and just landed a job in 2023 in a sell side capital markets quant rotational program. After being in the job a few months I have noticed more and more in 2023 that for front office the banks are really only willing to hire students with either PhD in STEM or MS in quantitative finance. I quickly learned that I was the exception. I was the only person in a cohort of 20 at the bank with an MS degree and I was even more rare in that I got in because I didn't do a quant finace MS degree. I think I got in because I had worked as a trading assistant for an exotic derivatives desk and then as a software engineer for 4 years before going back to grad school. I also had a very strong undergrad financial economics degree that was basically enough rigor to pass CFA level 1 and 2. When I started my job I was pretty far ahead of my peers on derivatives, option pricing, and other knowledge having worked on a trading floor and read all of John Hull's book and most of Shreve's books. I think the banks are foolishly overvaluing PhD degrees as numerous of my peers are coming in with a PhD in engineering and are weak in many areas of math (compared to a PhD in applied or theoretical math) and don't have a clue what an swap, option, or future is. Even the theoretical physics PhDs take about 3 years to figure out up from down on the trading floor. I really do think an MS in applied math with specific targeted courses relevant to quant finace is much better than an engineering PhD degree or even a PhD in stats especially if you can get some work experience in a legit finance job. However I was very calculated about what courses I took and knew exactly where I wanted to be after graduation. Front office sell side derivatives quant or die. Every class I took was focused on that goal and than one goal only. I don't think MS in applied math is good enough unless you tailor every class to the exact role you want to land. My advice may not apply to other areas of quant finance like credit loss forecasting. I think more traditional stats and time series would be helpful there than what I do. Or for a buy side role more optimization and operations research would help.

Here are the classes I took:

1. Probability and Statistics (non measure theory)
2. Matrix theory
3. Discrete and Hybrid Optimization
4. Introduction to Financial Derivatives (John Hull's text from Options, Futures, and Other Derivatives)
4. Stochastic Processes I
5. Stochastic Processes II
6. Stochastic Calculus (Continuous time models) - Shreve, Oksendal, and Klebner
8. Interest Rate and Credit Derivatives (2nd half of Hull's book)
9. Monte Carlo Methods
10. Theory of Machine Learning

[artem.shiryaev]

Thanks for answering my question and presenting your perspective! Interesting to hear your reflections // Math student

[nealpatel]

NYU Has a Master's in Mathematics in Finance under the applied math department, but also offers the MFE at the engineering school. Both of these programs are competitively ranking, but I never really was able to pin when a student should pursue one over the other. How do you generally compare a dedicated Math-Finance masters to a MFE?

[kemalafi]

Just out of curiosity, how were you able to understand stochastic calculus without a math background? After all it's a lot of measure theory and functional analysis

[vamosLeo]

Couldn’t you do a math masters and take finance and cs courses that are also offered within the program

[krystoferbaker]

Sir,
First of all thank you for your videos. They are great and have helped me out tremendously. Hopefully one day I can repay the kindness to you. I was wondering if you know of any ways to gather experience in quantitative finance before committing to a job? Are there opportunities like freelance work, contests, internships, or projects that people need help with? Any advice would help. I'm asking because I would like to get a feel for the work before I commit whole-heartedly to it, and I'd like to have some work experience under my belt going into it.

Thanks again!

[sumitsah]

Hi sir,
I have completed my BBA from nepal . So is it tough to pursue master of quantitative finance in USA . In BBA, i was studied statistics, Data analysis & modeling, Business mathematics, finance, investment analysis, corporate finance . These all provide basic concept to some specific knowledge . So i nervous for selecting mqf degree . Is it good decision for me ?

[kekw]

In an earlier video, you said that you would prefer someone with an academic masters but in this one it seems that you would prefer someone with a professional masters. What seems to be the change in opinion?

[colinjohnson]

Hi Dmitri, love the videos. If one were to get a PhD in mathematics, would your thesis topic have to be something related to financial mathematics in order to become a quant researcher or is it just the research experience that is important?

[rmrkingd]

Do you think having work experience before getting your Masters is important or is undergrad straight to masters a solid path to quant?

[chikkifay]

hey, I'm doing my current undergrad program in Mathematics and I'm thinking of opting for Financial Mathematics as my Masters, do you think it's a good route to becoming a quantitative researcher/ analyst? also, where should I do my masters from? is UNSW (Australia) a good option? do firms from the USA hire internationally?