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Math Pure math to financial math (quants) questions

  1. Jul 5, 2012 #1
    I'm an undergrad in college and I've been studying pure math for some time now. I do not really like the job outlook that this path is taking me. My school offers a Masters program in Math Finance (Stochastic Calc and all that). It seems that this more applied field has a greater job outlook (with the economy and markets being all in limbo and whatnot).
    With no prior experience with finance, I was wondering how fascinating will I (do you) find this subject? Does anyone have experience with this switch, or any advice?

    Also, if I choose this track, am I doomed to work in an office the rest of my career??
  2. jcsd
  3. Jul 6, 2012 #2
    If I were you, I'd go for a masters in applied mathematics, masters in statistics, or if you really love the subject a mathematics Ph.D. rather than something that focuses on mathematical finance. The problem with mathematical finance programs is that they are very narrowly focus, and it's very easy for them to be very out of date (e.g. no one cares about stochastic differential equations right now).

    The only situation which I'd even consider a mathematical finance program is if it happens to have excellent career placement. For that, I'd insist on talking to a live alumni. Statistics are dodgy.

    I think it's cool. The most annoying thing is that I can't really talk about what I'm doing right now.

    Offices are for senior executives. You'll get a cubicle or a desk. Imagine rows and rows of school cafeteria style tables, and you'll get a seat at one of them.
  4. Jul 6, 2012 #3


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    twofish-quant, how common are cubicles vs the interconnected desks for quants at financial firms in NYC? Personally, in my entire work experience (ranging from engineering, finance, health care, and pharma) I have always had at least a cubicle (in a couple of cases I shared an office).
  5. Jul 6, 2012 #4
    My school offers a Masters in mathematics with a track in Risk Manegement and Analysis. I'm assuming these are general courses related to finance..
    Besides being a "quant," (which seems dreadful since programming is probably my least favorite thing to do) what are some math related job opportunities in finance?
    Preferably high paying...

    Are there people that work in creating models so OTHER people program them?
  6. Jul 6, 2012 #5


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    To the OP:

    Besides studying pure math, have you taken any additional coursework in statistics? If you are interested in this area, I would advise you to consider pursuing either a MS or a PhD in statistics, as the job outlook for those with a MS or PhD in statistics looks very promising. I would add that a graduate degree in this field will open opportunities beyond just finance -- including work in the pharmaceutical/biotech sector, market research analysis, health-care consulting, etc.

    Another field you may want to consider would be in the actuarial field. Since you already have a solid background in math, you could start writing some of the preliminary SOA or CAS exams; you can also speak to your school about the opportunity to either take further courses in actuarial science or study the material on your own to write further exams.
  7. Jul 6, 2012 #6
    I haven't taken that many courses besides Stat 1 and Mathematical Statistics. Just by these two classes though, it seems boring! So far, I've been most interest in Algebraic Structures and Geometry. But I'm mostly interest in having a good paying job after I complete my masters.

    But if I continue studying Algebra, say Homological Algebra, I'm afraid I won't be marketable to companies where I could be making big bucks, then forced to stay in academia.

    SO that's why I've been looking at new directions to steer my math career to. I'm just hoping that there is a high paying job, that is NOT an office or cubicle job, that allows me to be mathematically creative.

    Maybe I'm asking for too much?
  8. Jul 6, 2012 #7


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    First of all, I'm not sure what the content of your statistics are like at your school, but there is much more to statistics than what you are getting out of it in your undergraduate classes, e.g. generalized linear models, applied statistics, multivariate analysis, time series analysis, probability theory, stochastic processes, etc.

    I might add that research in algebraic geometry has recently been applied to statistics, including the study of point-cloud data; see the Wikipedia article below.


    Also check out this link from the University of Minnesota:


    My point above is that statistics can be far more interesting than what you may think the field is about, and is a legitimate area to consider (since earlier you had already ruled out software development/programming as a career area -- you'll still have to program in statistics, but not to the same extent as a software developer or quant).

    All that being said, trying to find a career outside of academia that is not an office or cubicle job is frankly unrealistic, since practically all jobs that doesn't involve some form of hands-on labour will require working out of a cubicle or office (or a desk of some sort), unless you are working from home (in which you are sitting at a desk at your home office).

    Even in academia, part of working there involves sitting at a desk. So I'm not sure what exactly you are looking for.
  9. Jul 6, 2012 #8
    Yeah, I'd say you are asking too much. I can think of a few high paying jobs that are not desk jobs or cubicle jobs (union stuff like UPS driver - though you have to work your way up - or assembly line guy at an American car manufacturer) and I can certainly think of high paying desk jobs that let you do math (and high paying desk jobs with no math) but I can't think of non-desk math-intensive job. I mean, math isn't exactly a go-outside-and-get-your-hands-dirty kind of thing, ya know?
  10. Jul 6, 2012 #9
    True. What are some of those high paying math desk jobs are then? And what are some good preliminary classes?
  11. Jul 8, 2012 #10
    Trading floors are all desks. Cubes are more common in middle office and back office work. One curious thing is that given a choice, people prefer to work on desks because it means that you are "closer to the money."

    It's quite educational to listen to the conversations that go around. Also from time to time, you see "drama." The head traders all have loud speakers which they you to issue orders to their people. From time to time (about once a month), someone will "lose it" and you'll hear screaming expletives. They aren't screaming at you (and sometimes they aren't screaming at anyone in particular), but they are screaming (literally).

    One odd thing is that "financial panics" don't correlate with "emotional panics." Typically someone starts screaming expletives because of some local technical breakdown (i.e. an order that wasn't placed correctly). When the entire world is on fire (i.e. in the days after Lehman fell), people are quite calm. They were (rationally) selling everything and we were all headed for total global chaos, but people were quite emotionally calm.
  12. Jul 9, 2012 #11


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    That's very interesting. I had thought that most "quant" positions (i.e. most PhD-level technical positions at financial firms, of the type you are involved with) tend to be based in the middle or back office, and thus didn't work directly with the front-line traders.

    I also find it interesting that the traders were quite emotionally calm during the Lehman collapse and the subsequent financial panic. Perhaps the traders were in too much shock to react emotionally?
  13. Jul 9, 2012 #12
    Wow, really? I thought Ito SDEs were still a huge deal - but I'm not working in finance, so my information is probably out of date. What kind of problems are quants working on now? Binomial models? Risk measures?
  14. Jul 9, 2012 #13
    There's not an absolute correlation between the job title and the physical location of the office. For example, "risk" is considered a "back office" function, but there has been a quite conscious effort to put risk managers in the trading desk, since people have figured out that it's a bad thing for risk managers not to see what the traders are doing. Similarly, "babysitting supercomputers" is normally thought of as a back office function, but you often want a sysadmin at the trading desk so that the traders can instantly deal with the issue if something goes wrong.

    Being at the desk gives you visibility, which means that fights over seating location can become *very* vicious.

    The one movie that gives a good idea of what the inside of a investment bank looks like is "Margin Call." People dress slightly more formally than the people that I'm familiar with, but that's a firm issue. There are some firms that dress very formally, and some that don't.

    No. This is one of those things that you learn just "being there" and it's something that lots of people (even famous economists) get totally wrong. People assume that because people are taking about a "market panic" that people are actually emotionally panicking when in fact everyone is acting very calmly and very rationally.

    In a market panic, you end up in a situation where people are heading for the fire exits, and dumping everything, but they are making calm and rational decisions in doing that. If you sell now you might make it to the fire exits. If you wait, you are dead. You realize that everyone else is thinking the same way, and that if you sell, you are making the situation worse, but there's nothing you can do. So when you execute an order under those conditions, it's a perfectly rational, logical, and calm situation, and there is nothing to get emotional about. The *system* is panicking and going crazy, but the people inside of it are not.

    This has impact toward things like behavioral finance. Something that I'm interested in (and which can be modeled quite well with statistical mechanics techniques) is how rational actors can lead to irrational systemic behavior.

    The interesting thing about this is that reading about what happened in October 1929, people made the same observation. People were quite calm and rational, and from the point of view of the traders, it was a rather busy day. The other common thing with October 1929, is that people were in a surprisingly good mood. When things are blowing up, there are too many things to do to be depressed about what is going on. The time when it gets bad is after things have calmed down, and you notice lots of empty desks and nothing is happening.
  15. Jul 10, 2012 #14
    All of the important results in SDE's were worked out a decade ago, and there is no new work in them. One thing about current models is that for the most part they are "phenomenological". In the late-1980's, it was believed that you could take some basic economic principles and calculated prices and SDE's were involved in that. People for the most part don't believe that, so most of the new models are merely to quantify how the market behaves. Data mining and statistics.

    Regulatory compliance and counterparty risk.

    You have a government regulator that wants to know how your portfolios will behave in a crisis situation. "I don't know" is not an acceptable answer. "It will take us three months to figure out" is also not acceptable. "I'll have those numbers for you in an hour" is what they want to hear.

    Also, if you want to do anything new, it will have to go through *tons* of signoffs and permissions. Trying to streamline processes so that you can get the necessary data to make sure that you aren't going to blow up the world (again) in a matter of days rather than weeks is where the game is at right now.

    The "cowboy era" of Wall Street is over, and now if you want to do anything, you have a dozen people looking over your shoulder. This may not be a bad thing since it means lots of jobs for physics Ph.D.

    As far as counterparty risk goes. There was a time in which one bank could lend money to each other without worrying that the bank they are lending to would go under. For some reason, people aren't assuming that any more so there is a lot of work trying to figure out exactly what happens if the bank you let to defaults, and what the pricing aspects are.

    Example situation: I borrow $1M from a bank and then I put up $800K in collateral. The bank goes under. No problem!!!! I'm borrowing money from the bank so I don't have to worry about anything. Oh wait, I gave them $800K in collateral, well since it's my money, I can head over to the bank and get that money back, right? (At that point you have a lawyer nervously looking at the loan agreement and shaking their head). Oh, but if I can't get that collateral, I can just subtract it from the the amount of money that I owe the dead bank (and then you have another lawyer looking over the fine print of the loan agreement and then shaking their head.)

    Well, I guess I'm screwed....

    Fast forward a few years. You have two loan agreements with different collateral conditions. The bank is offering different interest rates for the different conditions (suppose one condition is that you can take back your money, and one that says you have to want in line at the bankruptcy court). The lawyers tell you the conditions, and you ask them what the difference in value of those contracts are. The lawyers then say "we're lawyers, we don't know how to numerically model stuff, you need a numerical modelling expert". Hmmm...

    Here are some recent papers


    Last edited: Jul 10, 2012
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