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The Almighty Buck Math

Future of Financial Mathematics? 301

Posted by kdawson
from the it-has-none-get-over-it dept.
An anonymous reader writes "Nassim Nicholas Taleb, a famous 'Quant,' has long been a strong critic of the use of mathematics and statistics in the financial markets. He has been very vocal in his books The Black Swan and Fooled by Randomness. In his article on edge.org, he says 'My outrage is aimed at the scientist-charlatan putting society at risk using statistical methods. This is similar to iatrogenics, the study of the doctor putting the patient at risk.' After the recent financial crisis, wired.com ran an article titled 'Recipe for Disaster: The Formula That Killed Wall Street' in which the quant David Li and his Gaussian Copula were crucified — we discussed it at the time. Now, I've recently been admitted to a graduate program of good repute in Computational & Applied Mathematics. There is a wide range of subjects in which you can pursue your PhD, one of them being Financial Mathematics. I had a passing interest in it for quite some time. In the current scenario, how advisable it is to pursue a PhD in this topic? What would my options be five years down the line? Will the so-called 'quants' still be wanted by the banks and other financial institutions, or will they turn to more 'non-math' approaches? Would I be better off specializing in less volatile areas of Applied Mathematics? In short, what is the future of Financial Mathematics in light of the current financial crisis?"
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Future of Financial Mathematics?

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  • by Tamran (1424955)

    ... given that people want to see subjective numbers. See:

    http://www.amazon.ca/How-Lie-Statistics-Darrell-Huff/dp/0393310728 [amazon.ca]

  • by chillax137 (612431) on Saturday April 25, 2009 @04:24PM (#27716175) Homepage
    Don't pick your research area based on profitability or popularity. There are always "hot" areas of research but these things are usually cyclic. Pick something interesting that excites you, and that you can spend the next 4 (or 5 or 6 or 7) years working on.
    • by Narpak (961733) on Saturday April 25, 2009 @04:46PM (#27716333)
      or the next twenty-forty-sixty years for that matter. Depending on how long you live or when Cthulhu raises from the sea.
    • by reporter (666905) on Saturday April 25, 2009 @05:12PM (#27716519) Homepage
      If you love financial mathematics, then you should definitely study that subject. Do what you love. Life is short. Enjoy your time on earth.

      Do not be concerned about "restricting" your future options. The applied mathematics in financial mathematics involves all areas of probability, random variables, and stochastic processes. These topics in applied mathematics have wide application in many diverse areas: digital image processing, gambling (e. g., card-counting techniques in the casinos of Las Vegas), computer simulations of warfare outcomes, etc. A degree in financial mathematics will enable you to work in many fields outside finance.

      Mathematics, in general, does not restrict anyone's options -- if you are smart and hardworking. Just ask William Perry [stanford.edu]. He received graduate degrees in "only" mathematics and eventually became Secretary of Defense of the United States. His most recent accomplishment was authoring an essay published in "The Washington Post". In the essay [stanford.edu], he advocates using military force to destroy North-Korean military facilities. Mr. Perry is a smart person with the right solution for dealing with North Korea.

    • Re: (Score:2, Insightful)

      by averner (1341263)

      Don't pick your research area based on profitability or popularity. There are always "hot" areas of research but these things are usually cyclic. Pick something interesting that excites you, and that you can spend the next 4 (or 5 or 6 or 7) years working on.

      There's another reason for this: if you find something interesting to do, it also helps with motivation, and you'll end up doing better in it. Succeeding in a highly competitive field is almost always better than doing average in a field for which there is a lot of demand.

    • Re: (Score:3, Informative)

      by Ruie (30480)

      Don't pick your research area based on profitability or popularity. There are always "hot" areas of research but these things are usually cyclic. Pick something interesting that excites you, and that you can spend the next 4 (or 5 or 6 or 7) years working on.

      I generally agree with this. I would like to add a few more points from personal experience:

      • Financial mathematics booms when hedge funds or similar businesses proliferate. I remember financial mathematics being depressed after LTCP [wikipedia.org] blew up, then wen
      • Re: (Score:3, Insightful)

        by urbanRealist (669888)

        I have a master's degree in financial math. I currently write software used to value structured financial transactions such as mortgage backed securities. I am over qualified for my job, but one of very few people in the world that is not under qualified for it.

        So I second Ruie. Get the degree, people will realize you know something useful, but don't be surprised when you don't really utilize everything you learned in school during the course of your career.

        • by bsane (148894)

          I currently write software used to value structured financial transactions such as mortgage backed securities.

          Have you been doing that long? Are you any good at it? Care to differentiate yourself from your colleagues?

    • by PopeRatzo (965947) * on Saturday April 25, 2009 @06:05PM (#27716927) Homepage Journal

      Listen to chillax137, he's got it right.

      My wife's a mathematician researcher. She's remarked to me several times lately that some of the big financial outfits have been picking people from the non-financial math areas, such as fluid dynamics, predictive analytics, combinatorics, etc.

      They're looking for sharp, dynamic people more than a particular course of study or area of research. The secret is out that a lot of second-tier mathematicians went into financial math because they thought that would be their ticket to vast wealth and like a famous capitalist said, "First you get the money, and then you get the power, and then you get the woman."* In the current environment, people who strive to get a certain type of degree because they think it's going to make them rich are not so eagerly sought.

      My first rule of preparation for career advancement: Don't learn how to do anything that you don't want to be doing. I figured that out long ago when I was trying to learn how to program SQL during a time when I was sick of my job. One night I realized that I would hate programming SQL all day, so I dropped it and put that energy into the stuff that I find fun.

    • by Meneguzzi (935620) on Saturday April 25, 2009 @06:29PM (#27717087) Homepage Journal
      Besides that, one thing you will have to have in mind is that you are expected to create novel research in the area, so going into a "hot" area also means that there will be a lot of people doing research in the same area, putting you in a position where it is very likely that someone will scoop your research, or more precisely, creating the thing you thought was brilliant and original before you. So not only you may end up doing research on an area you hate, but the novel thing you thought you had might not be novel anymore by the time you have to defend your thesis.
    • by b4upoo (166390)

      Your reply was well thought out. Enjoyment means a lot.

    • by Sycraft-fu (314770) on Saturday April 25, 2009 @08:17PM (#27717625)

      Don't go getting a masters or PhD if money is the objective. I see WAY too many people who are just hoop jumpers. They are going on to get a higher degree to get a better job. Some of these people get their PhD and then do post doc work not because there's still research they want to do but because they still can't get the job they want. Never occurs to them maybe education isn't the problem, it might be their complete lack of problem solving skills or the like.

      A masters and more so PhD are NOT for everyone, they are not even for most people. They are supposed to be when you really want to specialize in an area and do new research on the topic. If that isn't what you are about, then don't go for it. Unless you are going in to a field that has a specific minimum, and most don't past a bachelors, then there's no reason to go for a higher degree just for its own sake.

      Any time a friend or family member talks about wanting to get a masters my question for them is always: Why? Not as a petulant "Don't do it," thing but as a challenge. I want them to give me the reason they want to do it. If they can't, or the reason is "To make more money," then I'm going to tell them it is a bad idea. If the reason is "Because this interests and excites me," then I think it is a great idea, even if there isn't going to be a return on the money spent. Education for the sake of learning about what you want is wonderful. Just make sure that is really the reason you are doing it.

  • I always found it troubling that one of the computational algorithms [wikipedia.org] they relied on was also the name of where James Bond liked to gamble.

    • by stox (131684)

      Even scarier, the term was coined by someone working on nuclear weapons as Los Alamos.

    • Re: (Score:2, Informative)

      by hoytak (1148181)
      Yeah, well, there's no reason to be troubled there. Monte Carlo is great, and great in this situation, because it expands the possible models that people can work with, and if done with any intelligence will give reliable answers and error bounds on those answers. Throw Monte Carlo out the window, and you're back to conjugate distributions and low dimensional models that have far more restrictive and unrealistic assumptions.
  • by russotto (537200) on Saturday April 25, 2009 @04:28PM (#27716189) Journal

    Reading up on the Wikipedia article on this guy...

    "Taleb appeared to be vindicated against statisticians in 2008, as he reportedly made a multi-million dollar fortune during the Financial crisis of 2007-2008, a crisis which he attributed to the failure of statistical methods in finance "

    But his thesis is that such events are fundamentally unpredictable. If he made a fortune, it means _he_ was able to predict it, well enough to profit for it. Which argues not that the events are unpredictable, but rather that his model is better.

    • by Jane Q. Public (1010737) on Saturday April 25, 2009 @04:35PM (#27716247)
      Distortions in the market, like over-leveraged corporations and too many risky investments hanging out, tends to make things predictable. After all, if you KNOW that the market for some commodity is over-priced, then you KNOW that sooner or later there will be a "market correction".

      By and large, though, markets are unpredictable, and they need to stay that way. If markets were predictable, they would cease to exist... some one or a few would run off with all the money. To the extent that it has been "predictable" and made some corporations lots of money recently... as we have seen, that was largely due to manipulation and corruption, not the effects of free markets.
      • by peragrin (659227) on Saturday April 25, 2009 @05:18PM (#27716569)

        Actually markets are very predictable. every 10 years they go boom. Which part goes boom is varies but every ten years since Nixon they go boom.

        The trick is that wall street likes unlimited growth. if you don't expand your business by 10% every year then you are a failure and your company should be punished. After 10 years at 10% growth you have over saturated the market by 100% and every company that got there with unstable books and balances collapses.

        I forget exactly who and when but a walmart exec once stated. If we stop building new Walmarts we will go bankrupt. As they leveraged one walmart to build the next in a terrible endless pyramid scheme. Once the bottom bursts there is nothing holding up the top.

        Indeed if you look closely to all the news reports on what happened to the banks that is exactly what happened. 5% failure of loans should be expected. However a handful of banks ended up holding that entire 5% as their portfolio. As they collapsed the rest of the banks were suddenly forced to cover them, and since they over extended themselves by laying off bad loans on a small group the rest of the banks couldn't take the weight.

        the housing market the past 8 years was the same way. You can't have massive growth without massive contraction.

        The dot com burst. was the same. unparalleled growth but questionable accounting.

        Oh and I saw the housing market ready to burst 18 months ahead of time. Just look for massive growth over 5 years in any given market. a Seller's market for a long enough time leads to collapse. timing exactly when is the trick.

        • No, you missed the point. The only reason they go boom every ten years is because they are manipulated... as you then go on to point out. The essential nature of a free market is still unpredictability.
        • by Bigjeff5 (1143585) on Saturday April 25, 2009 @06:28PM (#27717077)

          It wasn't so much the 5% failure rate that was the problem. That and probably more was expected. It was the fact that when those loans failed, they could not be recovered because house values had actually slipped in a lot of places - that had never happened before on any kind of wide scale. But you're right that it could be predicted, and I'd expect your formula for predicting a market collapse of some kind is probably pretty acurrate in a general "rule of thumb" sense.

          This housing market collapse was predicted over a decade ago. The recipe for disaster was there, the only question was exactly how long it would take.

          Heavy-handed incetives to take risky loans that were first implemented 20 some-odd years ago, but greatly ramped up by the Clinton administration, created a climate where it was quite profitable to take on bad loans, and then shift, move, and otherwise hide that they were bad. The housing market itself was able to hide the risk of taking on so much bad debt, for as long as house values went up faster than interest rates, even extremely high risk loans (like fixed payment loans, and second and third mortgages) would almost always be covered when a house was sold. Homeowners who can't pay their bill just sell, banks get their money back, and nobody loses. Even when forclosure was necessary banks could reliably recoup most of their money, though forclosure is less than ideal.

          However, as soon as housing prices stagnated the model became tenuous, and when it slipped, even a little, the model collapsed. You ended up with thousands of loans that could not be covered by the sale of the home, and forclosure was the only option.

          This is BAD. Forclosures are expensive anyway, and only cover the balance left on the house for the initial bank, the secondary balance if there is one, or the homeowner if there isn't gets what's left. Forclosures that can't even get the primary loan balance back are a financial nightmare. What's more, the homeowners that tended to default were also more likely to get second and third mortgages to stave off forclosure. Houses went from being "guaranteed income" for banks to a massive liability. Companies like CountryWide - which embraced the Government's high-risk low income loans and who either Fannie May or Freddie Mac, I don't remember which, touted as the "model" for lending - was the first company to fail (no bailout for you! too bad so sad!). AIG, by the way, profited by shifting the risk of these loans via a special insurance type. Obviously that worked out well for them.

          I personally think the healthiest thing to do would have been to let the market collapse and allow other companies to fill the voids. Definitely more painful in the short term, but in the long term I think it would be better. We'll be suffering for a long time with the current bailout plan. Though of course, I'm no economist, but they haven't done so hot anyway so...

          • I personally think the healthiest thing to do would have been to let the market collapse and allow other companies to fill the voids. Definitely more painful in the short term, but in the long term I think it would be better. We'll be suffering for a long time with the current bailout plan. Though of course, I'm no economist, but they haven't done so hot anyway so...

            That seems to be what nearly everyone with a brain thinks (including most experts), but neither this administration nor the previous had any interest in doing what is best for the economy - instead, it's all about making people feel like something useful is being done. If there's a path that involves massive job loss and disruption today but better long-term health, and another path that means even BIGGER disruption and chaos but five or ten years down the road - they can be relied upon to put it off every

      • by BlackSabbath (118110) on Saturday April 25, 2009 @05:25PM (#27716621) Homepage

        By and large, though, markets are unpredictable, and they need to stay that way. If markets were predictable, they would cease to exist... some one or a few would run off with all the money. To the extent that it has been "predictable" and made some corporations lots of money recently... as we have seen, that was largely due to manipulation and corruption, not the effects of free markets.

        A few have run off with all the money. Who was on the other side of those massively leveraged positions that the banks lost on? It seems to me that the fact the losers are now being bailed out by the government means that effectively there has been a massive transfer of wealth from taxpayers to the "winners" of those bets.

        Manipulated, corrupt and un-free markets indeed.

        My suggestion to the submitter is to try a more honorable career, like record-company executive or drug-dealer.

        • by jmv (93421)

          The ones who "ran away with the money" in this case are affectively the ones who sold properties just before the crash. Just like when a bubble or a pyramidal scheme busts, the ones that run with the money are those who got out just before the crash.

      • by DriedClexler (814907) on Saturday April 25, 2009 @05:49PM (#27716797)

        Unfortunately, you can only exploit your knowledge that X is overpriced, if you also know *when* the correction will occur (or you already own X, in which case you can sell). Otherwise, you'll end up bankrupting yourself by being stuck in a "short squeeze"[1] or buying worthless puts.

        IMHO, the problem is not the risk; it's the coupling. That is, if everyone actually bore the full cost of their investment, and knew all of the ultimate counterparties, then it wouldn't be possible for one screwup to cascade to the entire system. If some investment lost, the direct investors would be out money that they themselves put up, and maybe those who lend them the money. It wouldn't be a complex web of leverage on top of unknown leverage on top of unknown leverage, all hidden in "safe" savings accounts.

        [1] that's when your short-sell X -- borrow it and sell it -- and then it rises too much, forcing you to close out your position unfavorably.

        • But again, that's only a problem if you are leveraging. If your assets have been paid for, then a deal can go bust and it doesn't topple a whole chain of borrowing.

          Short selling is really way on the outskirts... unless you can influence the market (against the rules), then it is a pure gamble, and has as often as not been done with someone else's money.

          Naked short selling should be an automatic prison term.
    • Re: (Score:2, Insightful)

      by maxume (22995)

      He believes that they are inevitable and uses strategies that work well during them and are mediocre the rest of the time. That doesn't mean he knows when they are going to happen, or what they are going to look like.

    • by the_other_chewey (1119125) on Saturday April 25, 2009 @04:44PM (#27716317)

      But his thesis is that such events are fundamentally unpredictable. If he made a fortune, it means _he_ was able to predict it, well enough to profit for it.

      No. His "system" is indeed based on the assumption that such events are unpredictable. That's why he for years bet
      simultaneously on a sharp increase and a sharp decrease in stock values - and ran slight daily losses, in the
      anticipation and expectation that once such an event inevitably happens, the profits will more than make up for those
      losses.

      It worked.

      He basically had no idea - and didn't care too much - when this (and what this "this" would be) would happen though.

      • by hitmark (640295)

        in other words, take the zero out of the roulette, put money on both colors and a number, and just wait it out?

      • by jstott (212041) on Saturday April 25, 2009 @11:21PM (#27718567)

        No. His "system" is indeed based on the assumption that such events are unpredictable.

        His system is basically arbitrage. We have an algorithm for pricing options (Black-Scholes) that makes an invalid assumption (it uses Gaussian statistics where it shouldn't). This fault was recognized almost as soon as it was published, but people continue to use it anyway, which means they're mis-pricing their options. Black Swan makes money in the long haul because they know big price swings occur more often than the options are priced for, and they buy based on this knowledge. Exploiting market mis-pricings like this one is the essence of arbitrage.

        Like classic arbitrage, this only works because a) there is a mismatch between price and real cost [risk] and b) there aren't a lot of players making the same purchase. Change either A or B and Black Swan's strategy will become a money-loser, or at least a break-even.

        -JS

    • If he made a fortune, it means _he_ was able to predict it, well enough to profit for it.

      If he were able to predict it, then he would have made a net profit over the long haul. From what I heard, he was betting on a crash for a long time now, and apparently he lost a lot before it happened. It is unclear whether he even made enough off the crisis to get back into the black. Of course when he's interviewed on national television, he doesn't bother talking about the losses. Sort of like a gambler who likes to tell you about his most recent jackpot, but not about all the losing nights at the c

    • You are making the incorrect assumption that profit necessarily requires prediction. As I understand it, he buys cheap CDS's(Credit default swaps are cheap when the risk of failure is perceived to be low) with a small part of his portfolio and puts the rest in something safe that pays off a reliable amount of interest like T-Bills. If the market doesn't fail, he pretty much breaks even. If the market fails his swaps pay out huge. I guess in some sense you could argue that he did predict that eventually
    • by CompSciStud4U (877987) on Saturday April 25, 2009 @06:27PM (#27717073)

      I would suggest reading The Black Swan. His basic thesis is that the gaussian methods used to calculate risk in financial markets underestimate the risk by several orders of magnitude. Crashes that happen every couple of decades are considered to be once in a million year occurrences by these methods. He made his money in the crash by betting against this. He assumes that he has no clue when a crash will happen, only that the risk is much greater than the vast majority of the market thinks. Everybody else thinks it will never happen, overextend themselves, and when the crash comes he takes their money. He did it in the 80's too.

    • by nido (102070)

      But his thesis is that such events are fundamentally unpredictable.

      Taleb has said that the present crisis is not a 'black swan' event. This link [ianwelsh.net], for example.

      Black swans are predictable by some, but not by most. The impact of certain advances in technology which are considered impossible by otherwise-eductated scientists would qualify. Cold fusion became respectable again this month, so that'd be a good Swan candidate, methinks.

      • by nido (102070)

        While I'm thinking about it...

        so that'd be a good Swan candidate, methinks.

        Another would be the impact of House Resolution 1207, Ron Paul's bi-partisan bill to audit the Federal Reserve. It currently has 91 cosponsors, and if/when it passes, it will result in a seismic restructuring of the financial system. Fractional Resrve banking is on the way out. I don't believe Gold == Money like some do - I'm more a fan of The American Monetary Institute's [monetary.org] comprehensive banking reform. Anyways, if monetary reform gets passed soon, the world economy won't have

    • Re: (Score:3, Interesting)

      by ChrisMaple (607946)
      Having recently read Black Swan, I can say with confidence that his main thesis is that the Gaussian distribution (bell curve) does not match much of reality, including the markets. Late in the book he says (without much clarity or any details) that his technique is to bet on changes being larger than most people think they will be, rather than betting that changes will be in any particular direction.
      Taleb undercuts his arguments by disparaging those he disagrees with and using ten paragraphs when one woul
    • Re: (Score:3, Interesting)

      by TheLink (130905)
      Any evidence that he isn't just like one of those lottery winners?

      The losers don't get much press. Once in a while someone wins big and everyone wants to know how that person did it.

      Even if there's a good reason why that person is "winning", often that person might not even be able to tell you how to replicate the success (he certainly can tell you lots of stuff, but that's not the same thing :) ). Apparently there's a finance guy who sells when his back hurts - and it works pretty well. His mind probably g
  • by fuzzyfuzzyfungus (1223518) on Saturday April 25, 2009 @04:28PM (#27716193) Journal
    As long as it is possible to get paid for the short term results of your crazy bets with other people's money, it barely matters whether the math actually works or not, you are fucked either way.

    While I'm all for good mathematical modeling, the notion that our financial problems are caused by bad math is a distraction at best.
    • by lgw (121541)

      While I'm all for good mathematical modeling, the notion that our financial problems are caused by bad math is a distraction at best.

      Nevertheless, after a major market crash people will take any scapegoat they can get, and there's always a market for pdeeling hate of "allegedly smart people in their ivory towers, out of touch with reality or the consequences of their actions". People alwa blame those who predicted the crash, those who profitied from the crash, and really anyone with any mechanical trading system.

      However, 5 years later no one cares.

      Our current financial problems are caused by:

      (a) Financial institutions relying on "expert

      • by lgw (121541)

        Err, that should be "individuals without enough math ..."

        Damn slashcode and it's last-century-forum-can't-edit-posts perl spaghetti!

        • Well, you need both. If nobody understands math, then you'll just get an infinitely long bubble of rising debt... It's those with enough math who ultimately refuse to keep going.
      • by julesh (229690)

        Our current financial problems are caused by: [...]

        You missed the big one: that when something is overvalued, its price tends (in the long run) to correct back down to being undervalued before rising again to somewhere in the region of the correct price, and that these over/underestimates of correct value are cyclic and unavoidable, because they are essentially part of human nature. And that the upshot of the 1990s and early 2000s is that both the housing market and the stock market became a long way overv

        • by lgw (121541)

          Bubbles bursting don't have to cause a wider crises, and I'd argue that they ususally don't. Markets seem to almost continuously pick some sector to overvalue, at the expense of the now-unfashionable previously-overvalued sector. The damage is usually limited to those who fell for it.

          It only takes a little bit of conservative sense to ask "wait, what happens in the 1% worst case - do we at least survive?" You know, the sort of question every competant engineer asks every day. It's not that the large ba

    • While I'm all for good mathematical modeling, the notion that our financial problems are caused by bad math is a distraction at best.

      Do not arouse the wrath of the great and powerful Oz! [amazon.com]
      Pay no attention to that man behind the curtain. [amazon.com]

    • by oldhack (1037484)
      And then there is math and there is math. If I remember correctly, stats are exquisitely nuanced thing, mostly dealing minute details of the underlying assumptions. One thing to master the mechanical math underlying stat, actual mapping to an application in social context is a black magic.
  • by Sprogga (893092) on Saturday April 25, 2009 @04:33PM (#27716233)
    There will always be a quant element in finance. I'd guess there will be fewer quants in five years than there were in (say) 2007, but there was definitely an over-supply then. Having said that, most quant jobs don't require you to have had specific training in finance or financial mathematics. For the best firms, its much more about your mathematical and programming abilities. So you definitely don't need to specialize now in finance to become a quant. You could make a case that focusing on AI would be a bigger draw with quant firms. The other advantage of not doing finance now is that it gives you five years to think about whether you want to be in a career where when you get down to it, you rent out your brain to rich people so that they can get richer. I do work as a quant and find it interesting and competitive etc, but ultimately its a money thaang.
    • Re: (Score:3, Insightful)

      Though arguably this is precisely the root of the problem. As the post above you mentions, many quants build their software around nonparametric statistics or statistical (machine) learning, without deeply understanding the domain. This can lead to an over-reliance on historical data, which in turn leads to a failure to predict rare but significant events, like, say, the current crisis. Now, I'm totally unqualified to pronounce that if only we'd had more quants who richly understood finance and economics w
  • ... then do it.

    Realistically, Financial Mathematics isn't going to go away. If anything, financial institutions will want to improve the formulas and/or realise their limitations in light of what's been going on, so they're going to need Quants more than ever. Look at Taleb, for example. I seriously doubt he would be railing against his own field if it meant an end to employment opportunities. He seems to be advocating a more realistic assessment of what financial mathematics can do, rather than having a bl

    • by Anonymous Coward on Saturday April 25, 2009 @04:51PM (#27716365)
      As a former Wall Street trader turned academic, I can agree that the demand will continue to grow for financial mathematicians. The "old school" trader is a former ivy-league athlete who is good at networking and teamwork, but can't do a lick of math. The D.E. Shaw's and hedge funds are crushing the "old school" traders as trading becomes more about speed (esp. algorithmic trading) and liquidity and less about connections. The large banks still have plenty that follow the old mindset, but they are slowly being replaced by the more successful "quant" traders. Granted, the current crisis was caused by over-reliance on models, but that happened because most traders and managers did not understand the models and their limitations. To rectify that, there will be an even greater need for those trained in financial mathematics.
      • Hmmm, I think connections are worth way more than formulas, so much so that one could say formulas are for people who do not have connections. Having a drink with one guy who just reviewed the innards of a big company and found them interesting in some way can produce immediate profitability.

  • by blahplusplus (757119) on Saturday April 25, 2009 @04:37PM (#27716263)

    ... your passion? Are you the kind of person that gets bored even about things you are passionat about? You can study something if you believe it will bring you more money in the future.

    What people don't understand is you can LEARN to love doing something by looking at it from another perspective - i.e. take joy in solving problems and strategizing in general and then it shouldn't matter what 'speciality' you go into specifically.

  • I would call that the future. But you will need a second foundation, to maintain the predicted events unknown for the people that affect those events, or things will not work.
  • Lots of questions.

    There aren't really any viable 'non-math' approaches to finance these days. However if you want to work in finance, you need to have in mind ideas of risk, profit, and so on. 100 years ago when there was some idea of 'any profit is good' you could hire an expert in mining to advise you on which mine stocks to buy, and that would be all you'd need - these days, small percentage profits are actually bad for your business (your market value is better if you make £100 on a Â

    • On the other hand, something that isn't well-enough realised is that ultimately what banks are playing with is quite close to a fixed-total-reward game. If you make a huge profit then someone has to be making a huge loss to compensate.

      1) It's not really a zero sum game the way you're pitching it. It's not even close. If you're expecting to make money day in and day out on the market, then yes, you are essentially gambling. But for folks who follow an advisable savings plan of gradually moving from a div

      • Wait.. Paper-pushers amount to 22% of the economy? (23, when you add in tax preparers...)

        In the words of Jamie Hyneman, "Well, There's your problem."

    • by xelah (176252)

      On the other hand, something that isn't well-enough realised is that ultimately what banks are playing with is quite close to a fixed-total-reward game.

      No-one should be put off studying such things from a belief that it's a zero sum game, or that it's close to one, though. What's happening now is clearly not zero sum: banks, borrowers, governments, the property industry and whoever else everyone blames this week have cause an avoidable huge loss of beneficial economic output because they made poor investment decisions, backed up in part by poor models. Improving the pricing of stocks is not zero sum, either, because it affects real economy investment, man

  • by thesandbender (911391) on Saturday April 25, 2009 @04:45PM (#27716329)
    I have worked with companies that implement and use "algorithmic" trading. The real problem is that algorithmic trading doesn't try to beat the market... it tries to beat other algorithmic traders. The idea is to get the trades in before anyone else and there is only so much analysis you can do in a given period of time. Honestly, there's no real analysis to it... it's snap judgments based off a few dozen indicators. It's the equivalent of saying you should guess all C's on standardized tests. On average it works... but you should be shooting for better than average.
    • by wootest (694923)

      The problem with beating the market is that you can't base your system on the market and consistently outperform it; definitely not all the time, but probably not most of the time either. My guess is that you have to mix in something else, but then there are the problems of choosing that "something else", and making sure that its benefits are enough to strengthen the model.

      When you say algorithmic trading and "snap judgments", it seems you're referring to the kind of algorithmic trading that lives and dies

  • The economics blogs have been talking about this issue for a while. All of the blogs that saw this coming for years (like CalculatedRisk) are very anti-quant.

    What we are seeing is a push for the study of behavioral economics, as seen in the popular new book Animal Spirits [amazon.com]. This book is being heavily quoted by Obama's Budget Director Peter Orszag.

  • by gadders (73754) on Saturday April 25, 2009 @04:56PM (#27716413)

    1) Taleb has a bit of the stopped clock quality about him. Anyone saying "bad things will happen" is bound to be right sooner or later. Plus, his writing is the most self-indulgent wankfest ever.

    2) I don't know whether you will choose financial maths or not, but Banks will always need people that can do "fancy" maths. Although some maths is out of favour, high-frequency (algo) trading is currently still popular, and making money.

    • by julesh (229690)

      Taleb has a bit of the stopped clock quality about him. Anyone saying "bad things will happen" is bound to be right sooner or later.

      Well, yes. But Taleb wasn't just saying bad things would happen. He was saying that when they did happen, people who thought they were prepared for bad things would find out that they weren't. He was saying risk analysis doesn't work, and that a lot of people were putting too much faith in it.

      • There's nothing wrong with risk analysis. It's what goes into it that matters. Garbage in, garbage out. And there has been a lot of garbage fed into it, as the bank deregulation of the 90s has allowed people to make claims about the riskiness of products which is wildly at odds wiht reality.

        Taleb is playing semantic games to sell some books.

  • I used my skills and turned to the natural sciences. They have really, really big datasets and nobody really knows what is going on there. Salt water intrusion models, various solute transport models are crying out for application. Earthquake modeling and prediction gets big budgets. What is occurring under your feet is really complex.

    I did an interview to go into the financial district about 4 years ago but I rejected it after finding out how much they would cripple me. They don't trust anybody. I ha

  • If math can be used to tell us which stocks/companies will profit, can't math also tell you which outcome is best for you?
  • Mathematical modeling of markets assumes that people in markets behave in a manner that can be reflected in smooth continuous mathematical functions.

    People don't behave like that. They behave in a boolean fashion.

    An example of a boolean function would be something like

    r= ( gaussian random number between 0 and 1)

    if ( marketConfidence gt 1 ) { //bubble
    return yesterday + (.1 * r)
    } else if (marketConfidence lt 1 and marketConfidence gt .95) { //topping
    return yesterday - .05 + ( .1 * r)
    }
    else { //crash
    return yes

    • by ceoyoyo (59147)

      Elementary particles also behave in a quantized fashion, not continuous. If you have a lot of them, their overall activity can be modeled quite successfully using continuous mathematics.

    • When the market is going up, it keeps going up regularly. When the market confidence is broken thend the market is in crash mode, and the markets go down regularly

      This was true until about 2002. Before then you could make nice money buying at the close if the close is up, shorting if it is down. Since then the opposite has been true, but less strongly (based on raw NASDAQ COMPOSITE data ^IXIC from yahoo finance).
      My guess is that the increased use of computers by day traders and others has fundamentally ch

  • by viking80 (697716) on Saturday April 25, 2009 @05:30PM (#27716669) Journal

    In quantum mechanics, you use statistical models because that is the true nature of the underlying physics. In financial analysis, you do not need to use statistics. A borrower ability to pay monthly payments is not some unknown quantum state, but well known (at least to himself or his employer)

    It is a fallacy to estimate risk in lending and then charge interest based on this risk. All borrowers that pay on time should get the best rate and those who don't just should be denied the loan.

    The only reason not to do this, is lack of information or lack of computing power.

    With fast computers and good data all population statistical analysis should be thrown out, and replaced with calculation for each individual and then integrated. This will replace the entire field of mathematics from insurance to lending and investing.

    • by kramulous (977841)

      Hey, that last statement of yours is actually quite insightful. I have a really hard time trying to fit people to curves (as I'm told to by others ... regardless of what I think). People are just not like that ... even large groups. Distributions of large groups are an approximation, at best. Time for these things to be rethought.

      Even data mining techniques, which I normally don't think much of - given that results are not reproducible if you supply the same data but in a different order, yield results

    • by retchdog (1319261)

      Fast computers and good data aren't enough. Lenders and investors tend to be conservative (or at least they demand that from their quantitative models) and thus need strong, trustworthy error bounds. Whatever "calculation for each individual and then integrated" means, it doesn't seem very amenable to error bounds/variance estimates.

    • The risk of a loan depends on a lot more than the borowers current ability to make thier payments. It depends on among other things.

      1: the behaviour of the value of the asset that the loan is secured on. If an asset has risen in value since the loan was taken out then even if the person defaults the bank still gets their money back. If it's fallen in value (or didn't exist in the first place, unsecured loans have high rates for a reason) more than the person has payed off then the bank loses.
      2: the likelyho

    • The problem is that there is no such thing as a model for an individual that you can integrate. The point of a black swan is that nobody saw it company because it is intrinsically unpredictable. You are correct that the reason for this is a lack of information. But neither you, nor me, nor the CIA, or all the quants on Wall Street can obtain the information you would need to predict at the level needed. This is one of Taleb's key points. Hari Seldon only exists in fiction.
    • It is a fallacy to estimate risk in lending and then charge interest based on this risk. All borrowers that pay on time should get the best rate and those who don't just should be denied the loan.

      Banks can look at the data available to them and from that estimate the likelihood that they will make a reasonable return on their money. Within some range, a poorer likelihood that they will get their money back can be compensated by raising the interest rate. You apparently consider it OK that a person be preve

    • by sjbe (173966) on Sunday April 26, 2009 @08:34AM (#27720647)

      In financial analysis, you do not need to use statistics.

      You aren't a financial analyst are you? Statistics is required precisely because financial decisions are almost always made with limited information. You can't model most financial activities including risk without statistics coming into play at some point.

      A borrower ability to pay monthly payments is not some unknown quantum state, but well known (at least to himself or his employer)

      Actually ability to pay in the future IS unknown even to the borrower. Furthermore ability to pay is not and never will be perfectly known to the lender. There is an inherent information asymmetry because the lender can never be sure the borrower isn't hiding something. Furthermore you are leaving out willingness to pay, as well as the fact that life sometimes isn't so kind and circumstances change. People lose their jobs, they invest with Bernard Madoff, their employer turns out to be Enron, etc. These things cannot always be predicted.

      The only reason not to do this, is lack of information or lack of computing power.

      So you are comfortable providing no insurance to people with a high likelihood of disease? How about losing most/all access to credit when you lose your job. Because that's what happens with perfect information. Be careful about the unintended consequences of perfect information. Even if a perfect model were possible (and it is not) there are many social reasons why we limit how much information is available and how it can be used.

      With fast computers and good data all population statistical analysis should be thrown out, and replaced with calculation for each individual and then integrated.

      Except that there NEVER is enough data and it is IMPOSSIBLE to perfectly model future events and actions. Even if I concede that you are right and ignore the unintended consequences, what you are proposing is quite literally impossible. The best you can do in many cases is to make a statistical model of likely behavior based on population models and then seek a portfolio to minimize risk for the desired return. Companies use population statistics because they are the best option available.

  • if the worry is that people don't trust the current models, wouldn't now be the perfect time to pursue studies in that field? Who wants to learn a bunch of things that people are certain of?

    • by Alex Belits (437) *

      The problem is, all those models are self-defeating because they describe behavior of people WHO ARE TRYING TO BEAT THOSE VERY MODELS. So basically the less we pretend to "know" about each other, the less damage players cause to each other while long-term growth is almost completely unaffected by it (wealth has to be somehow PRODUCED).

      It's similar to algorithmic rock-paper-scissors game -- a very sophisticated model may hope to guess the outcome of another very sophisticated model that tries to guess it, ho

  • There will be a continuing need for mathematical analysis in finance. They will continue to need to assess risk and model alternatives. There will also continue to be people who try to get rich quick and want analysis to show that their approach doesn't have the risks that it actually does. So the need for good analysts will continue, as will the risks that you'll be pushed to use your analysis to support incorrect arguments. But that's going to be true of anyone in finance, quantitative or not. It's an are
  • by mario_grgic (515333) on Saturday April 25, 2009 @06:25PM (#27717059)

    Studying math with some concrete career in mind is like marrying for money.

    If you are going to study math, study it for the love of it, and your own soul.

    Your degree will prove useful to you in what ever career you choose for yourself later.

  • Financial mathematics didn't become popular because it isn't effective, and large financial institutions don't get that way for being financially ineffective. They might have to change the job titles to appease minority shareholders, but there's no way they'll get rid of mathematicians who make money with magic.

    The real problem wasn't that the math was done, it's that a lot of people were doing it poorly and with too little oversight because, as with any fad, people forget that they know better and trust ev

  • It is the dumbass MBA managers that do not understand the math that is the problem.
    • One of my professors asked some of his former students (who took their PhDs and went on to use them in the financial world) about the role of math in current economic crisis. Their take on it was this: the quants developed algorithms for financial products based on a set of (apparently reasonable) assumptions. The traders weren't told about some of the assumptions that applied to them, and ended up treating these products in an inappropriate fashion.

      The management supposedly prohibited any kind of interac

  • A perfect subject.. (Score:4, Interesting)

    by meburke (736645) on Saturday April 25, 2009 @06:39PM (#27717131)

    ..for a Ph.D. thesis? How can Mathematics be applied to safely invest without damaging Society?

    Well, first, NNT is "outraged" at the "inappropriate use" of Quantitative Analysis (according to his books and the articles I've read), not the "utility" of Quantitative Analysis. The reality is that investments' values fluctuate. The role of the Mathematician is to limit the losses, therefore the risks, involved in investing. This is a legitimate role. If you had been working for 45 years and were about to retire, wouldn't you want to know that your retirement funds were as safe as they could be?

    Part of the problem comes from the fact that investment value is affected by information other than the worthiness of the investment. This value activity has created an analytical branch of its own, and subsequent buy and sell orders are based on the activity rather than the underlying fundamentals. NNT's argument in "The Black Swan" is based on the idea that since these random events are indeed "random", by definition they are unknowable, unpredictable and un-assessable. So, when these events occur, no contingency plan behaves correctly. Keep in mind, that this is only a problem if the event(s) affect the investment values, or the perception of investment values, in a negative way. Unfortunately, the use of these QA tools creates an aberration in perception, and may be creating it's own perception, and this "perception" may not conform to "reality", therefore leading to aberrant behavior based on an aberrant strategy. (Oooh, the stock market has become psychotic...) Skynet takes over the market and tries to wipe out the humans because its programming tells it that is what humans want.

    Mathematics can tell us a lot about what reality "is", and there is a lot of room for a creative Mathematician to alleviate the downside and limits of financial decision-making. I say, if you like Math and this is an area that interests you, go for it. Try to be the best. Be creative and innovative instead of being a sheep.

    Malcolm Gladwell's book, "Outliers" deals with somewhat the same problem in a different domain, and Ayers, "Super Crunchers" gives a good layman's view of how well Math can work for us in certain areas. Graham and Dodd, "Portfolio Analysis" may still be the best overall book touching on your field. Benjamin Graham's, "The Intelligent Investor" may still be the best basic investment book. If you want to get out there a little ways, try Prector's, "The Elliott Wave Theory." I had a friend working at Lockheed in Artificial Intelligence, who was responsible for the computer analysis of the market for Prector's newsletter. Every year they would run a 3-month test of the application, and it would consistently make money well in excess of the inflation rate (even in '89). It's been 15 years since I talked to him, and I have no idea how well it's done in the last few years, but the field seems fascinating.

    I say go for it, and good luck!

  • by rbrander (73222) on Saturday April 25, 2009 @07:46PM (#27717507) Homepage

    There was an article in Maclean's (our Newsweek) about a pure-science institute having trouble recruiting in the 90's and 00's because "an entire generation of physicists, chemists and biologists went into Finance instead".

    The "quant" maths haven't been proven wrong, exactly; whether heavy mathematical analysis and modelling can make markets more efficient and lower-friction is a separate question from the morals of those managing them.

    The trouble is, baroque complexity of financial instruments and transactions was the primary concealment tool that allowed all the lying in the first place - lying to other institutions, to regulators, and certainly to the public that handed over all their dough at low interest because the institutions were so guaranteed-safe; and I suspect, they managed to lie to themselves. Models - especially complex ones with many parameters - have a way of reflecting all the prejudices of (and pressures on) the developers. A big part of the scientific method is about systematically counteracting that. There is way less pressure to counteract if you are not working for open publication after a rigorous peer-review. If your models will be strictest trade secrets, however, your only reviewer is your boss - who may personally become hugely wealthy if the model says X, and not much, if it says Y. Science (as in, "the search for truth") suffers.

    If nobody, for a generation or two, will trust an institution with opaquely complex business methods, the market for quants is going to stay "plummeted" for a long time. (It has already plummeted because of the contraction in the whole finance industry - I presume you are even asking about this career only because you think there will again be some job openings in 4 years when you complete a degree.)

    I think even 4 years from now, there will still be surplus quants littering the weak market; resumes in the hundreds will flood in for openings.

    So, stay away from THAT career, job-wise. There's a crying need for physicists, chemists, and biologists.

    • There's a crying need for physicists, chemists, and biologists.

      I'll bite. I'm graduating in two weeks with a BSc in Physics.

      The job market doesn't seem to indicate any such need...at least not for anything below the Ph.D level and outside the halls of academia.

      So much for having a "flexible" degree. Employers currently seem to be looking for specialized degrees and/or several years of experience.

      (It would seriously make my day to be proven wrong here...please feel free to jump in and provide evidence to the contrary)

  • Although it's become trendy to blame [wired.com] the Gaussian Copula function for the collapse of the bond market, I wouldn't be so quick to judge.

    The function appears to have allowed investors to "re-package" risky debts to appear less risky by the system that was used to rate the bonds, which (very predictably) blew up in everybody's face when it came time to pay off the loans.

    However, the "white-hat/black-hat" argument comes to mind. Although the exploit was bad, it seems as though somebody should have stepped in a

  • Here are some facts:

    1. All work requires energy. Energy is the capacity for doing work. [gsu.edu]
    2. Oil and gas production is at or near peak, and we get 85% of our energy from it, and Coal is not a "good idea".
    3. Therefore: our capacity to do work will decline if efficiency doesn't meet decline rates, and work can't grow if the efficiencies don't exceed decline rates.
    4. decline rates in major oil fields are extreme - The North Sea, Mexico's Cantarell, are both in double digit decline rates. The USA has been d

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