To be a Derivatives Quant, Stats quant, etc.
Most quant jobs require a PhD, so I would say yes.
I don't know what a quant is. (Seriously, I don't.)
90% of the people in finance with "quant" in their title are high end computer programmers. About 60% of the people I work with have Ph.d.'s and the other 40% have masters in some technical field with a lot of work experience before they got hired in finance.
Also if your main interest is finance or to make money, do *NOT* get a Ph.D. in physics. It's silly to get a Ph.D. in physics if your main interest is either to work in finance or make money, for many reasons, not the least of which is that no one has a clue what the world financial situation will look like in five years.
Now if your main interest is physics and finance is just a way of paying the bills, that's a different issue.
Ah, I had no idea. I thought they mainly worked with finance, and the programming was minimal.
I read this blog entry: http://getonthedesk.blogspot.com/2008/01/day-in-life-of-quant.html
And I don't know how accurate it is, but it seemed like the programming was consisted of short coding periods (I can write up small programs [which might even be just considered scripts] too, though I wasn't aware how heavily programming was integrated in these types of careers).
So a Physics PhD would not be versatile at all in case of financial emergency (if, God forbid, a terrible calamity occured with the economy in which a particular degree might be rendered null or something)?
Can you suggest more suitable degrees aside from, say, a Physics undergrad + Physics PhD?
I'm just looking over some general job descriptions/qualifications as examples here:
Quantitative Finance Analyst
Quantitative Finance Analyst 2
CIG Quantitative Analyst
They require PhDs in "Quantitative" fields, which I'd presume includes Physics as well (Physics is just the first thing that comes to mind when "quantitative" is mentioned; I think they do list Physics as an example)
I feel so discouraged when I view the CVs of students like these:
Will I even have a shot in this field with people like these running the show? Their resumes seem padded, but they also look very related and impressive, not to mention all the other hot shots that will be graduating from other top schools...
Most jobs in finance don't require much programming, but quantitative jobs make up a tiny, tiny fraction of jobs in finance.
It's reasonably accurate for someone doing front desk support, but that's only one type of job, and it's not a job that's in much demand now. Most of the hiring that I've seen has been in risk management and infrastructure programming.
Also, the fact that someone spends only a two hours coding means that you have to be an extremely, extremely sharp programmer. In a production support issue, you are expected to go through a system with several hundred thousand lines of c++ code, diagnosis the problem within ten minutes, and then come up with a fix within an hour.
Those situations are a lot like being an emergency room doctor. If you look at the schedule of an ER doctor, they might spend only an hour trying to deal with someone with a heart attack but........
On the other hand, if the world economy collapses, than no degree is going to help you. Then again, being smart and curious can help you in extreme events.
This really is a personal decision, and any advice that I give is inherently self-defeating. If I tell everyone to get a degree in X, then soon there is going to be a glut in X. If you love physics, and are willing to go through a fair amount of pain to learn physics, then a physics Ph.D. is decent. If you don't care about physics, then there are *thousands* of better options.
For the type of work that I do, those resumes are very unimpressive, and there are only two or three of them that my group would even consider calling in for a phone screen. There is no evidence of any sort of deep mathematical or programming ability. The type of resume my group would be more interested in is someone who has worked for five years at Microsoft or Google or someone with deep applied mathematics, statistics, or engineering experience.
Among the people that I work with, you have a few people with masters of finance engineering or financial mathematics, but no one with a straight masters of finance, and we are more likely to hire a mechanical engineer than someone with a finance masters, because people that go the masters of finance route are generally not too interested in the "geek work" that my group does.
Now there are other groups in which programming and mathematical skills are not so important, and if one of those resumes came across my desk, I'd likely forward the resumes to them.
Also for the work that I do, "top schools" don't matter. Physics graduate schools are not strongly tiered, and the fact that finance is a second choice for physicists means that the resumes that come across tend not to come from a big name school.
There are a ton of MFE programs out now. Maybe two-fish can comment on weight of a MFE from NYU or Columbia vs NCstate or Kent. In the early days a lot of PhD's would be hired because the field was blossoming and academic positions for physicist were becoming more rare post wartime. I believe the entry level quant positions are programming dominant, mainly in c++ and matlab, if I'm not mistaken. I also feel like the main goal of the entry level quant is to eventually obtain a position as a trader (where the real money lies). From what I've read most people in finance burn out within 5 years, so you need to decide if it is something you are really interested in.
I think I read that a lot of people who start as "quants" never really make it "big," and are really just coders.
From what I've heard most quants with the sole goal of becoming a trader burn out within 5 years. Most people who shoot for the money don't make it too far.
So does this naturally bring the focus back to something like a computer engineering degree, as opposed to something like a degree in physics? Which would actually be more preferred in your line of work?
Speaking of which, I'm not exactly sure what you do besides programming. Do you have a link to one of your posts which describe your job in detail?
This is actually what I'd like to concentrate on more. I'm by no means the most natural of abilities when it comes to problem solving, but I'd like to learn and improve my breadth of knowledge by expanding my vision to see outside of the box. Again, speaking of versatility, I thought maybe physics would help me achieve this as well as being able to land me a decent job where I can put my learned theories into practice.
Maybe going into the field of mathematics might perform similarly? Though I'm not sure how viable that would be in comparison to physics or engineering...
Personally, if I was going to try and be a quant, I would pick my favorite engineering and pursue a BS (just not civil), maybe minor in math or cmsc at the same time. Work your tail off and get over a 3.5, graduate, get over a 750 on the math portion of the GRE, and hope to get into one of those Ivy league MFE programs.
Here are Cal Berkley's prereq's:
Successful candidates for the MFE Program will have a strong background in
High-level math and statistics
Statistical and econometric applications (Sas, Gauss, RATS, S-Plus, or Garch)
Mathematical tools (MatLab, Mathematica, or MathCad)
Before the program you are applying to is scheduled to begin, you should:
Have taken—or have a plan in place to take—the prerequisite courses listed below for a grade of "B" or higher
Plan to take all of the pre-program courses in addition to the prerequisites to reinforce your understanding of the basic concepts
Please note that you do not necessarily need to complete all of the coursework prior to submitting your application, but you do need to have a clear plan in place to complete the coursework between the time of application and the time the program begins.
For students who have not taken a math course in more than 5 years, we do recommend some type of refresher course in order to excel in the program.
Prerequisite Course List
Computer Programming Experience
Prior experience in computer programming (C, C++) and familiarity with computers as a computational and management tool.
C, C++ Programming
1 course OR equivalent work experience
[Back to top]
A strong quantitative background including multivariate calculus, linear algebra, differential equations, numerical analysis and advanced statistics and probability.
Training in Finance
They want like 2 classes in finance or economics.
With the engineering degree all of the maths would be done except analysis, you could take some econ and finance classes as electives, and c++/matlab you could probably semi-learn in your engineering classes and your own time.
Now, the benefit of the engineering BS, if the financial world tanks again, you can get an engineering job.
http://www.quantnet.com/ this website has a lot of information, and if you're really interested you can pick up Emanuel Derman's "My Life as a Quant."
Nah just a borderline criminal mindset
This is actually what I was most likely considering...I wanted to take MSE @ NC State and then work on my PhD, but it seems getting an MFE first would be more sound going into the finance sector. If I can finish an MFE within a year, maybe I can still continue my PhD education afterwards?
Thanks, I've checked out that site and it would seem it's pretty helpful. Also makes me feel like the market is pretty saturated, but I'm gonna go for it anyway.
Personally, I'd avoid MFE programs and go for either a masters in computer science/statistics/MBA/finance or anything else. The problem with MFE programs is that you are dead if quantitative finance falls apart, whereas if you have a masters in something else, you have options other than Wall Street.
Which works great for physics Ph.D.'s with computational skills.
This is wrong. There is the occasionally quant that moves into trading, but it's rather uncommon since the skill sets are different. Also, there is less money in trading that you may think. It's true that head traders make a ton of money (if the market works) but you aren't going to be a head trader immediately, and you need to spend several years as a trading assistant, which makes a decent but not spectacular, amount of money.
This tends not to happen to physics Ph.D.'s. Part of the reason that banks hire physics Ph.D.'s is that if you haven't burned out getting the Ph.D., you are unlikely to do so in a banking environment.
The stress is high, but no worse than graduate school.
95% of quants are glorified coders, but good coders make a lot of money.
No major preference. It's in fact a good thing to have a mix of people. Physicists learn a different set of techniques than mathematicians, statisticians, econometrics, and/or CS people, so within the scope of technical people, it's desirable to keep a diverse mix.
Applied mathematics is a good way into the field. One thing to remember is that for the jobs that are of interest to people in this board, you aren't looking at a "job in finance" you are looking at a "job in applied mathematics or physics that happens to be in a financial institution."
I wouldn't. MFE programs aren't particularly a good way of getting into "geek jobs" and they are extremely risky if the economy changes. Also *big name* MFE's aren't necessary worth their tuition. The one thing that you get from an MFE is career placement and there are "no name" MFE's with wonderful placement and "big name" MFE's with horrible placement.
Which is a bit silly. If you have all of this background then what the heck are you getting out of the MFE program? One thing that you have to be careful is the "placebo degree" which is a degree in which you pay massive amounts of money to get a job that you probably would have gotten anyway.
You have to be careful about some of the information. Derman's book is a great book provided that you read it as *history* and realize that a lot of the information in that book is quite out of date.
If you are going to get a Ph.D. get a Ph.D. If you get an MFE first it's going to be totally useless by the time you finish your Ph.D. The big thing that you get from the MFE is career placement and internships, and if you aren't intending to get hired very quickly, those are useless.
I have a generally bad impression about that site. The information is not particularly useful, and it seems more like ads for MFE programs.
One problem with MFE is that things change too quickly. If you pick up a book on business administration or applied math that was written in 2005, then most of it would still be useful today, but if you pick up any book on quantitative finance that was written in 2005 then most of it is either wrong or useless.
Ah, I was actually planning a trip to the library on Tuesday to borrow some books off that list on the quantnet website. Thanks for the precautionary heads up.
Are there any specific texts that you'd personally suggest?
I was looking for something cross between applied mathematics and statistics, and I've recently discovered something called "actuarial science..." This might be the best option I've found so far because I wanted to go into something like applied statistics (which I don't think exists) and actuarial science seems pretty close.
Start with Hull's Options, Futures, and other Derivatives and Paul Wilmott's book.
80% of both books are wrong or irrelevant, but it's useful to know the terminology so that when someone explains to you want a three factor interest rate bond model isn't useful or why a local volatility model won't work, you know what a three factor interest rate or local volatility model are.
The really cool problems don't have textbooks.
Statistics is one of the most applied fields out there. It's almost an oxymoron to have statistics not be an applied fields (and yes I am aware of theoretical results in statistics and associated research).
If you want to do any kind of "applied" statistics, just major in it and do some post-graduate work in it along with as many projects as you can. Actuarial work is statistics applied to risk management, but there are other applications of statistics which include to the sciences (including the area of health) as well as other things like business and government.
I was actually warned by several other people that any degree (especially a PhD) which is too "general" might not be such a good idea, and that I should specialize in a certain field. Does this apply to statistics as well, or will a general statistics degree be fine on the market?
I have always been facinated by the number of people who seem to want do physics to become 'quants'. Everyone should realise that 'quant' work is not physics and never will be, so don't do physics just because you want to become a quant. The attraction is the money, but this is not going to last much longer.
Future job prospects are also not great, certainly, across europe now most organisations are deleveraging, getting rid of the complicated stuff and going more 'vanilla', the result of this will be less need for high end quant people.
Mind you, the quant who comes up with a derivative that avoids the proposed eurpoean financial transaction levy will have a secure job......
There are different kinds of quants. Quantitative research usually wants people with a PhD in math or physics, because of:
1. High level math involved (stochastic processes, numerical analysis, PDE)
2. Research experience
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