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This may not be a suitable question for this but I wanted to seek some advice from some of you out there. I came into Florida State University as a PhD student in Financial Mathematics and I am finishing my second year here. I passed my qualification exams and started exploring in areas of Monte Carlo simulation for pricing American options. Although, I have considered putting my PhD on hold and getting some work experience within the field of Quantitative Finance, but I do not have any work experience.

I talked to the director here and he said that I could come back and finish my PhD after if I desired to get some work experience. I am wondering what the difference is in applying as a PhD student or applying as a Masters student since from what I was told working for a 3-5 years coming out of the Masters program would make you just as prepared as a PhD student coming in to the job market depending of course on the experience you get.

Is a PhD really necessary to get a job in the quantitative finance field? Or is a Masters with PhD level training good enough?

I am interested in what you all think. Any comments are greatly appreciated.

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From my math profs that have done some pioneering work in the field:

1) back in the days, PhD was required because there weren't MFEs around. now the PhD is no longer viewed as a "requirement" and many mfe's get hired for roles that used to require a PhD.

2) having said (1), the PhD trains you for a research position in quant-finance. The MFE will not. So, different skill sets and different career paths. Which do you want? Research / PhD roles, not as many exist today, are very hard to get. FSU PhD may not open many doors for you to top quant shops or top banks - check this, though. MFE + programming may be better for you to land at a top place to do quant finance.

3) whatever you do, try to train in lots of numerical methods. apparently people move up very fast (managing director or similar) because there just aren't enough strong math people in quant-finance. For instance a prof told me that tons and tons of people at Top Investment Bank X can't actually use optimization correctly. Strongest math talent go elsewhere - primarily somewhere in academia, so if you claim you're strong in math, you could move up fast.

4) from a head trader on an algorithm trading desk: having interviewed thousands of candidates, he says that there is a stigma attached to PhD candidates, and they are screened, interviewed and assessed more carefully to find out whether he or she even has any relevant skills aside from his PhD thesis work.

5) MFE programs usually have recruitment / networking opportunities

That's all :)

  • Thanks for your insight. Since I started as a PhD student but most likely just going to walk away with a masters I was trained as a PhD student (PhD students have a different set of classes they have to take then masters). Anyways thank you for your insight. – Wolfy Jan 21 '17 at 15:16
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I have taught graduate courses and done graduate advising for many years at a place that offers MS degrees, but not PhDs. Most of our students go into pharma/biotech and insurance/finance with an MS degree and maybe 10% go elsewhere to get PhDs. The population of people I'm talking about in this post is probably about 300.

A few of them change jobs now and then because of the company downsizing, etc. But most change every few years deliberately and strategically to gain experience in a broader range of applications (sometimes, not always, at an increased salary). At some point employability and salary depend much more on what a person can do than on whether their highest degree is MS or PhD. People with a history of success in a broad range of applied work are very much in demand in our local job market.

Also, there are a few people who have started up their own hugely successful companies, either right out of the MS program, or after several years of employment. Some of these I might have predicted, and some not. Some mystical combination of a bright idea, self-confidence, salesmanship, timing, and luck seems to be involved. 'Hugely successful' includes years of making a lot of money, or getting bought out by one of the tech giants.

There are several situations, particularly in pharma/biotech, in which a PhD is important. Division leaders, people who make initial contacts with high value clients, and people who may need to testify in court are usually PhDs. From my perspective, it looks as if this is mostly a matter of the prestige that may attach to having a PhD.

After several years away from studies, the probability of going on for a PhD falls off greatly. If someone has a family to support, it is really hard to live on savings and graduate student funding long enough to finish a PhD. There is also a feeling that there is more certainty of success being employed than in doing thesis research. However, there are a few people who go on for PhDs even after being away from university life for long time; they have a specific academic or personal goal that they feel cannot be reached otherwise.

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I have a master degree in quantitative finance and regularly headhunted for quantitative positions in finance. I should share with you my experience.

No, it's not necessary to be a PhD to get a job in the quantitative space. But that depends on what you want to do and your career path.

If you want to be a researcher or someone doing advanced mathematics, you may need a PhD. Even if you were able to get a job, it'll be difficult to advance your career any further.

As a quantitative researcher, you might be asked to:

  • Try recently published new methods and algorithms
  • Develop mathematics for a new financial product
  • Model validation
  • Publish papers to high-quality journals

You really need a PhD, possibly good papers to succeed in research environment.

Fortunately, most of the quantitative jobs don't require a PhD. Financial institutions just want someone to help them making more money. They want someone to implement their trading strategy, pricing engine, backend database etc.

Possible job titles:

  • Quantitative developer
  • Financial analyst
  • Product specialist
  • Quant trader
  • Quant application support

You should still understand:

  • Black Scholes and option pricing
  • Term structure modelling
  • Fixed-income
  • Stochastic calculus

What exactly you need to know is job specific, but you are not expected to be a mathematician. It's a high-paid but very competitive field, you will compete with candidates who do have a PhD.

Summary: You don't need a PhD, but it's a good idea.

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