The Value of a PhD and MFE Degree

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Since writing for this blog in January about the HFT/algo job market, I’ve received many inquiries from students asking about the “requirements” for quant jobs on Wall Street. “Do I need a PhD?” is a frequent question. Each time I receive one of these inquiries, I struggle with the answer. My instinct is no. But when I look at who is working in these jobs, I do see a predominance of PhD’s in the top positions. PhD’s in mathematics, physics, operations research, EE, etc. are common in the quant community. So it’s tempting to tell students that a PhD is helpful, but it feels like the wrong answer. In my gut I know that the people getting these jobs are not getting offers because they have extra letters after their name. The people in these positions are there because they have proved over their academic and professional lives that they are:
List 1
  • Very smart
  • Quantitative thinkers
  • Good at figuring things out with minimal guidance
  • Dedicated
But the above is a generic list of attributes for hiring into just about any job. So what is it that makes someone hirable as a quant? The list isn’t long:

List 2
  • Education in advanced math (stochastic calculus, statistics, probability, etc.)
  • Good software development skills
  • Good data analysis skills
Okay, now combine the two lists, and you have the list of qualifications for a quant.

So, back to the question of whether to get a PhD. Should I get a PhD?, asks one student who is angling for a career in quantitative finance. Will it help me? Is it necessary? No, it’s definitely not necessary. Will it help? Empirically, it seems to help. But does it? I’ve finally come to clarity on the subject with the help of a conversation today with the director of a quant group supporting credit trading for a major investment bank. Of the two lists above, the important qualifications are on the first list. This list has nothing to do with your education. Your success in any field depends on the first list. The 2nd list consists of skills, skills that can come from your education or experience. They are enabling skills, but they are not dictators of success. All career success comes from differentiating oneself with respect to the elements on the first list. You can get a PhD, spend the money and the time, but if you don’t differentiate yourself in the fundamental elements of success, the PhD won’t help.

So why are there so many PhD’s in quantitative roles, anyway? I think the answer is pretty obvious. Very smart people with quantitative instincts are drawn to the PhD path. Later they find that they are well suited to a career in finance. They satisfy both lists and hence are successful in quantitative roles in finance. Almost without exception, these are individuals who pursued a PhD based on their interests and passions (EE, Physics, Applied Math, etc.), not people who pursued a PhD as a means to a job in finance. QED: A PhD is not a requirement for a career as a quant in finance.

The MFE

I feel this article isn’t complete without addressing the MFE degree. The MFE provides students with the fundamental skills utilized in quantitative jobs. If you can afford it, it’s an easy way to satisfy List 2. However, it’s by no means a ticket to success in quantitative finance. I’ll explore the MFE further in my next post, “The MFE, Is it a Contra-indicator?”

As always, you can reach me at peter@affinityny.com. LinkedIn profile: www.linkedin.com/in/peterwagner123 (I keep a listing of active quant roles here).
 
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All relevant skills on the job. (notice none were client facing skills). Yes, I agree that the PhD guy could do things better, ie being the forefront in a specific area. However, being in this industry for a couple of years, I can safely say that with graduate level math classes and two weeks of reading, I can actually understand some of the academic research in financial markets out there. (that's exactly my profile).

In my undergrad by 2nd year you would be able to read any text in mathematics. Trust me, when people describe someone as "good at maths" usually the person in question does not have this skill. Majority in my masters didn't, most did risk jobs and wouldn't have the ability to do quant. Funnily the best thesis I saw was from someone self read enough that, even though classmates from his physics undergrad program were struggling with reading basic notation, he had no problems.

Given that you will have to look at quant research papers to do your work as a quant this is invaluable, and there are other skills aswell e.g. understanding of market structure. As I was once crassly told, quant finance isn't "just calculating".

The whole PhD thing comes down to generalisms - it is a generalisation to say that the Harvard undergrad you described (while a good pick) is rare and that there are enough PhD grads that will have read enough to understand finance (some Imperial PhDs require it). But for recruiters and employers this generalism is close enough (Dominic Connor on Willmot.com is a good point of reference on this topic as he's ex quant and now recruits) that they often run by it. Solution? If you really are that good, but not have the "traditional" quant background, do something a little better than just ringing up employers on spec to get around this. Who knows what this is - focussed thesis brought out into CV, or even internships or even a BA grad publishing papers that will look good on the CV?
 
In my undergrad by 2nd year you would be able to read any text in mathematics. Trust me, when people describe someone as "good at maths" usually the person in question does not have this skill.

Yup, so at least we agree on the distinction here. I see it as four tiers.

Tier 1:
Those with skill up to calc 3, differential equations, linear algebra who claim to be 'good at math' but honestly can't get by reading any research. They can only solve equations.

Tier 2 (very strong undergraduate aka me):
Very strong undergraduate degree with the typical quant classes make up - machine learning, stochastic calculus, real analysis, maybe thesis. I can guarantee you that assuming this kid aces all his classes, spending two weeks and then understanding a research from finance journals (J. of Finance, J. of Financial Economics) is definitely possible.

Tier 2.5 (unrelated PhD):
The unrelated PhD's whom employers value based on their thinking skills and intellectually curiosity than on their specific knowledge. Sure, these guys can read journals to understand the markets. But they aren't experienced with those theories. They can know markets. But they don't know what works or what doesn't. Goes back to the Molecular Biology PhD vs Harvard Econs undergraduate argument.

Tier 3 (relevant PhD aka Math, Finance):
The masters! These are the guys that can read the math and finance journals. They know the theoretical stuff which the tier 2 guys don't, ie an analytical solution to returns via arbitraging two banks assuming the two different pricing models being used. These guys work on something deep in the model, ie alter the volatility, redefine a search algorithm, (Maybe bad examples because clearly I'm not here) Tier 2 guys just understand and implement.

For me, I see it as 1 < 2 = 2.5 < 3
 
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Examples probably are simplistic but this is precisely the stuff non-mathematical people don't understand. It's not like selling houses where you can return to it anytime, albeit just get into the swing of things. Still I seriously cannot understand how 95% of the population would reject what is stated on this thread as if they're somehow employment experts after doing 1 or 2 Mickey mouse jobs. I mean few will have experience of maths degrees never mind being a quant.

I've returned to mathematical work after 6 years of working in finance without it - it was still fresh, but I could see a difference between that and my stopgap job where I was redoing market research calls, which took 1 week to get back into the swing of things. Although to be fair I'm finding reading through MapReduce and machine learning papers very easy as probably 4 out of the 5 years I did in college involved it.
 
In my undergrad by 2nd year you would be able to read any text in mathematics. Trust me, when people describe someone as "good at maths" usually the person in question does not have this skill.
Indeed.
 
Dare I ask what people consider of someone with a PhD in a technical field (such as EE) AND a MSCF? I feel that it qualifies as "Tier 3" described above but alas could make you look like you're trying too hard and make you "overqualified." Curious what the community thinks of this, or if someone has run into this type of individual personally what they thought of him/her.
 
Dare I ask what people consider of someone with a PhD in a technical field (such as EE) AND a MSCF? I feel that it qualifies as "Tier 3" described above but alas could make you look like you're trying too hard and make you "overqualified." Curious what the community thinks of this, or if someone has run into this type of individual personally what they thought of him/her.
These are the guys that can read the math and finance journal

Depends on what you mean by "can read".
 
Dare I ask what people consider of someone with a PhD in a technical field (such as EE) AND a MSCF? I feel that it qualifies as "Tier 3" described above but alas could make you look like you're trying too hard and make you "overqualified." Curious what the community thinks of this, or if someone has run into this type of individual personally what they thought of him/her.

They tend to be career switchers / people who finished their PhD and realized they don't want to go into academia. An extra year or 1.5 years after 5-7 years of a PhD isn't too bad bang for the buck.

I think they are welcomed by employers, since they have a highly technical research training along with formal mathematical finance training, so they can get up to speed more quickly.
 
off-topic anecdotal: I took a course last semester and there was a physics PhD student in there, the dude couldn't wait to "get done" with his PhD so he could go work at a bank or a hedge fund.

I felt a bit confused because I still don't get why you'd spend 5 years of your life researching something that you have no interest in (obviously)? I'm sure there are PhDs in mathematical finance out there more suited for these goals? isn't that better?
 
I feel like if you do a PhD in "mathematical finance" you learn the same things as everyone thats already gunning for a quant job. If you do a PhD in Physics or EE or whatever, you can take theories not already found in computational finance and apply them there to see if you can turn it into money. Machine learning and other theoretical concepts weren't created to be used in finance, they have just found a home there because other people were interested in them and realized they could be used to make decent returns. At the end of the day, if you understand the same concepts as everyone else in the room, how are you gonna make any money? Thats just my rationale.
 
I felt a bit confused because I still don't get why you'd spend 5 years of your life researching something that you have no interest in (obviously)?

A lot of the time (most of the time?), the research adviser holds the Ph.D. student's hand and guides him step by step towards an acceptable dissertation. There's a lot of drudgery involved but not necessarily that much "research." The exceptions would be the best students with the best research advisers.
 
off-topic anecdotal: I took a course last semester and there was a physics PhD student in there, the dude couldn't wait to "get done" with his PhD so he could go work at a bank or a hedge fund.

Maybe he started his PhD starry-eyed and full of hope and five years of PhD life turned him cynical & $$$-hungry.
 
Interesting article and points raised. But how about an individual with an undergraduate degree in Economics and mathematics but has a passion for Quant. Does this individual stand a chance?
 
Interesting article and points raised. But how about an individual with an undergraduate degree in Economics and mathematics but has a passion for Quant. Does this individual stand a chance?
a chance to do what?
 
This is an old thread but here it goes...
Looks like most people who replied completely missed the point. I personally doubt anyone who did are really quants or even close to being one.

Just gonna throw my 2 cents here....

For me. I'm not exactly a quant. I've interviewed for several quant trading positions. But I didn't like the trading path. I know some traders. Most don't have an advanced degree, because being a quant trader doesn't really require super advanced knowledge.

I like research. To a certain extent, I am a "quant" researcher. Because I am applying the exact same skills that would be used by quant researchers at some companies. But, I'm not titled one. If I made a lateral move to one of those companies, I'd be a quant researcher. Nonetheless, I'm planning on doing a PhD.

Now let's talk about research. And then quant researchers. Yes, you're right. Quant researchers do research. Some people are smart enough to do research without a PhD. But they're rare. There is no formal way to learn the important research skills without doing a PhD. PhDs also have a track record. They are "somewhat" proven.

Also consider how far up the ladder can you go up without a PhD. Most quants are just extremely well-paid grunts. Some become senior researchers, then PMs or heads of research or whatever,... Would you put some guy without a PhD as a head of research? What credentials does he have? Can he do all the work that a PhD can do? Most likely, there are some things that a smart person with a Masters or just a bachelor's cannot.

Are PhDs in industry not good enough to be in academia? Grossly wrong. Plenty have publications in too research journals. They just wanna make loads of $$$ and not deal with the BS that goes along with being in Academia.
 
Some people are smart enough to do research without a PhD. But they're rare. There is no formal way to learn the important research skills without doing a PhD. PhDs also have a track record. They are "somewhat" proven.

Also consider how far up the ladder can you go up without a PhD. Most quants are just extremely well-paid grunts. Some become senior researchers, then PMs or heads of research or whatever,... Would you put some guy without a PhD as a head of research? What credentials does he have? Can he do all the work that a PhD can do? Most likely, there are some things that a smart person with a Masters or just a bachelor's cannot.

This seems a good response to both the article and replies. Nearly all the listings for quant jobs I'm actually interested in list "PhD in x, y, or z" as a required qualification. Not "nice to have", not "MS, MFE, or PhD", they very explicitly state they want someone with a PhD. I apply anyway, and get rejected every time. Indeed, the employers are looking for skills, but someone has convinced them that only a PhD recipient could have those skills.
 
Most quants are just extremely well-paid grunts.

This is actually fine (for the time being). You will be very lucky to be a well paid grunt if you possess just a bachelors. Can go back to school later on. As someone applying to quant jobs at that level, lots of specific coding questions and the math is actually pretty basic. It's kind of a tell on what they want from you.
 
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