Notable Financial Mathematicians in Academia

Hi everyone!

I just want to ask, are there any notable academics who came from industry that takes in doctoral students?

I know it is preferable to pursue graduate study that focuses on the hard sciences. However, in my case, seeing there are many doctoral programs offering specialisations in Mathematical Finance, I’m considering the idea of looking for a suitable supervisor.

These programs are mostly in Europe if I’m not mistaken. An example would be El Karoui, any other notables that employers also know?

Thank you!
 
Hi everyone!

I just want to ask, are there any notable academics who came from industry that takes in doctoral students?

I know it is preferable to pursue graduate study that focuses on the hard sciences. However, in my case, seeing there are many doctoral programs offering specialisations in Mathematical Finance, I’m considering the idea of looking for a suitable supervisor.

These programs are mostly in Europe if I’m not mistaken. An example would be El Karoui, any other notables that employers also know?

Thank you!
I do not know of any notable academics from the industry that takes in doctoral students. Still, I think you can check out these academics and may or may not consider them a potentially suitable supervisor.

1.
Ioannis Karatzas - Eugene Huggins Professor of Applied Probability
University: Columbia University Mathematics Department
Research Interest: Probability and Mathematical Statistics, Random Processes, Stochastic Analysis, Optimization, Mathematical Economics, and Finance.
h-Index: 59
Citations: 34,330

2.
René Carmona - Paul M. Whythes'55 Professor of Engineering and Finance
University: Princeton University - Operations Research & Financial Engineering
Research Interest: Stochastic Analysis (SPDEs, BSDEs, FBSDEs, stochastic control, and large stochastic differential games such as mean field games), High-Frequency Markets, Energy and Commodity Markets, Environmental Finance, and Financial Mathematics Models.
h-Index: 55
Citations: 13,028

By the way, pursuing a graduate study in Mathematical Finance as an aspiring quant is preferable to pursuing a graduate study focusing on the hard sciences. By inference, I consider Mathematical Finance a hard science.
 
Hi, adding on the above answer. I am not sure about the intake procedure or preference of these professors, but found these were doing exciting, industry up-to-date and relevant research in the area-
1) Olivier Guéant - Mean fields game theory
2) Paul Bilokon - Machine Learning in Finance
3) Charles-Albert Lehalle - Market Microstructure/Mean fields game theory
 
I do not know of any notable academics from the industry that takes in doctoral students. Still, I think you can check out these academics and may or may not consider them a potentially suitable supervisor.

1.
Ioannis Karatzas - Eugene Huggins Professor of Applied Probability
University: Columbia University Mathematics Department
Research Interest: Probability and Mathematical Statistics, Random Processes, Stochastic Analysis, Optimization, Mathematical Economics, and Finance.
h-Index: 59
Citations: 34,330

2.
René Carmona - Paul M. Whythes'55 Professor of Engineering and Finance
University: Princeton University - Operations Research & Financial Engineering
Research Interest: Stochastic Analysis (SPDEs, BSDEs, FBSDEs, stochastic control, and large stochastic differential games such as mean field games), High-Frequency Markets, Energy and Commodity Markets, Environmental Finance, and Financial Mathematics Models.
h-Index: 55
Citations: 13,028

By the way, pursuing a graduate study in Mathematical Finance as an aspiring quant is preferable to pursuing a graduate study focusing on the hard sciences. By inference, I consider Mathematical Finance a hard science.
Agreed, thank you for the recommendation!
 
Hi, adding on the above answer. I am not sure about the intake procedure or preference of these professors, but found these were doing exciting, industry up-to-date and relevant research in the area-
1) Olivier Guéant - Mean fields game theory
2) Paul Bilokon - Machine Learning in Finance
3) Charles-Albert Lehalle - Market Microstructure/Mean fields game theory
Thank you! I’ll look into these experts!
 
By the way, pursuing a graduate study in Mathematical Finance as an aspiring quant is preferable to pursuing a graduate study focusing on the hard sciences. By inference, I consider Mathematical Finance a hard science.
I don’t agree with this as a general statement. While banks might prefer people with a math finance degree for pricing quant and risk roles, this is not often true for trading firms / quant funds who are less interested in pricing.

Your list of potential supervisors looks extremely arbitrary. How did you end up suggesting these two..?
 
Julien Guyon is an adjunct @ NYU / Columbia and works at Bloomberg. Not sure he’d be taking students as main supervisor.
I will advise that @LukeAtlas consider a tenured professor as a potential supervisor instead of an adjunct. In more candid terms, you should not apply for a Ph.D. supervised by an adjunct.
 
I don’t agree with this as a general statement. While banks might prefer people with a math finance degree for pricing quant and risk roles, this is not often true for trading firms / quant funds who are less interested in pricing.

Your list of potential supervisors looks extremely arbitrary. How did you end up suggesting these two..?
1. You don't have to agree with my opinions or suggestions. I stand by my statement about pursuing a graduate degree in Mathematical Finance as an aspiring quant instead of pursuing a graduate degree focusing on the hard sciences.

2. You don't need to be disrespectful when disagreeing with someone else's suggestions. The best thing to do is come up with a better list of potential supervisors. We are on this platform to learn from each other and not to prove a point.

I wish you the best.
 
I don’t agree with this as a general statement. While banks might prefer people with a math finance degree for pricing quant and risk roles, this is not often true for trading firms / quant funds who are less interested in pricing.

Your list of potential supervisors looks extremely arbitrary. How did you end up suggesting these two..?
For quant prop trading is it better to pursue a hard science such as Applied/Pure Mathematics or Physics?
 
1. You don't have to agree with my opinions or suggestions. I stand by my statement about pursuing a graduate degree in Mathematical Finance as an aspiring quant instead of pursuing a graduate degree focusing on the hard sciences.

2. You don't need to be disrespectful when disagreeing with someone else's suggestions. The best thing to do is come up with a better list of potential supervisors. We are on this platform to learn from each other and not to prove a point.

I wish you the best.
1. You tend to make very confident and general statements that lack foundation - I observed that across multiple threads here. If these statements are based on the particular role you are in, then it would be useful to say something along the lines of “If you are aiming for a role in …, then …”. You’ll notice that I do this as well.

2. What is disrespectful about asking how you came up with these two names? You say you don’t know quants with an industry background and then seemingly just give the names of two professors out of a huge universe of tenured professors in financial maths. Having read some of his papers myself, I would put Karatzas in the more theoretical camp.
 
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For quant prop trading is it better to pursue a hard science such as Applied/Pure Mathematics or Physics?
It depends. Trading firms are generally open to more diverse backgrounds than banks. Even at most option trading firms, only a minority of quants work on the pricing algorithms themselves. A good understanding of pricing is useful in most roles though. The majority of people work on time series prediction / trading signals, the market making algo stack or execution strategies. For these roles, a background in statistics, machine learning, physics, econometrics, signal processing, … is often more useful than mathematical finance. The applies to an even greater extend to more delta-focused firms. PhDs are also often hired not for their particular domain knowledge but for their demonstrated ability to work independently on complex and often undefined problems. I should also say that a PhD is not needed to land these roles, though its a plus and a good signal.
 
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It depends. Trading firms are generally open to more diverse backgrounds than banks. Even at most option trading firms, only a minority of quants work on the pricing algorithms themselves. A good understanding of pricing is useful in most roles though. The majority of people work on time series prediction / trading signals, the market making algo stack or execution strategies. For these roles, a background in statistics, machine learning, physics, econometrics, signal processing, … is often more useful than mathematical finance. The applies to an even greater extend to more delta-focused firms. PhDs are also often hired not for their particular domain knowledge but for their demonstrated ability to work independently on complex and often undefined problems. I should also say that a PhD is not needed to land these roles, though its a plus and a good signal.
I just want to clarify, apologies for the ignorance, doesn’t a Mathematical Finance PhD cover these areas as well? (Stat/ML/TS/metrics/SP)

If PhDs aren’t needed to land the a role for Quantitative Research is it possible for an undergraduate degree holder or at least a Masters?
 

Daniel Duffy

C++ author, trainer
Instead (or as well) of looking for famous names, why not draw up a list of the best universities and their PhD programs. I am sure there are many top professors out there at the hieight of their intellectual powers.
 
I just want to clarify, apologies for the ignorance, doesn’t a Mathematical Finance PhD cover these areas as well? (Stat/ML/TS/metrics/SP)

If PhDs aren’t needed to land the a role for Quantitative Research is it possible for an undergraduate degree holder or at least a Masters?
It depends on your area of research and your supervisor. But indeed - you could work on these topics in a math finance PhD as well. And yes - many quants at trading firms have a masters degree. Undergraduate is less common unless you are a local applicant from a prestigious university and have some other outstanding achievements (top of class, IMO, very strong internships, ...).
 
I just want to clarify, apologies for the ignorance, doesn’t a Mathematical Finance PhD cover these areas as well? (Stat/ML/TS/metrics/SP)

If PhDs aren’t needed to land the a role for Quantitative Research is it possible for an undergraduate degree holder or at least a Masters?

You don't need a PhD to get into quant trading roles. Trading is combination of art and science. You just need to demonstrate you have a big brain (PhD/IMO etc).

You also don't need a PhD for pricing quant. However you will need to demonstrate sophisticated understanding in math finance and very strong programming in C++. You need to show that you have the fundamental knowledge to pick up Local Vol/SABR/SLV.

When you ask for renowned mathematician in finance. My initial assumption is that you want to go into academia. That is very different ball park. Then I might recommend,

Rama Con
Jim Gatheral
Liuren Wu
Dilip Madan
 
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