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Paul Wilmott Wants To Retrain and Reform Wall Street's Quants

theodp writes "What if an aeronautics engineer couldn't reconcile his elegant design for a state-of-the-art jumbo jet with Newton's second law of motion and decided to tweak the equation to fit his design? In a way, Newsweek reports, this is what's happened in quantitative finance, which is in desperate need of reform. And 49-year-old Oxford-trained mathematician Paul Wilmott — arguably the most influential quant today — thinks he knows where to start. With his CQF program, Wilmott is out to save the quants from themselves and the rest of us from their future destruction. 'We need to get back to testing models rather than revering them,' says Wilmott. 'That's hard work, but this idea that there are these great principles governing finance and that correlations can just be plucked out of the air is totally false.'"

16 of 198 comments (clear)

  1. Wow! by viyh · · Score: 4, Insightful

    What a concept! Basing conclusions on experimental evidence from testing via trial and error rather than warping reality to fit your business model. That's incredible!

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    "I have never let my schooling interfere with my education." --Mark Twain
    1. Re:Wow! by dov_0 · · Score: 4, Insightful

      What a concept! Basing conclusions on experimental evidence from testing via trial and error rather than warping reality to fit your business model. That's incredible!

      It will never last in the 'real' world...

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    2. Re:Wow! by rtfa-troll · · Score: 4, Insightful

      I'm glad you got insightful not funny. You are right. This is one of the case where experimentalism actually breaks down in the real world.

      The problem is that the quant's model is in its self an input to the reality and the processes aren't statistical and stochastic. When I know (or even partly correctly guess) what model you are using for investing, then I can gain several benefits from altering my behavior. I can create false investment opportunities which match well with your model. I can predict when you will need to buy something and push up the price just before hand. I can guess when you will become over exposed to some asset and force you to sell too cheap.

      The models are useful, but in the end lots of business stuff just has to come down to gut feelings and judgement. You also just have to do analysis which goes beyond the empirical (nobody has ever tricked us before) into risk control (what can we do to make sure nobody can do that in the future; how would we tell if they were trying to).

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    3. Re:Wow! by BlackSabbath · · Score: 4, Insightful

      > I reject your reality and substitute my own!
      > /mythbuster
      > or /Wallstreet broker

      Disdain for the "reality based community" is nothing new.

      > In all seriousness, this does not sound like a field that needs saving from itself.
      > ...
      > Something doesn't get to be common practice unless a good portion of the field believes that it is good to do so, or at the very least, not harmful.

      I agree with your last statement in application to almost any discipline other than economics and (more specifically) finance. I must disagree with your first though. The ability of greed to short-circuit the mind's ability for critical thought is unparalleled as is the obstinate willingness of great swathes of people to swallow snake oil by the gallon on the merest suggestion of the slightest whiff of profit. My memory may be hazy, but I can recall at least two occurrences of a "new economy" in the last three decades. And of course each "new economy" marks a break with "outdated" beliefs/dogma/tradition (you know - like that outdated belief that you can't make something out of nothing, or that other one about a "turd by any other name would smell as sweet").

      I don't doubt that given another fifteen years or so, we'll have forgotten the "hard lessons", the sincere abjuration of pernicious practices and every other skerrick of common sense. The new "new economy" will have arrived. Only a fool would fore-go the chance to make real money. May I suggest however, that you watch this infotaining interview before you invest in the new "new economy".

    4. Re:Wow! by richg74 · · Score: 4, Informative
      The problem is that the quant's model is in its self an input to the reality

      You are right, this is one important source of problems. I started out in quantitative finance back in the 1970s. (I worked as a research assistant for Fischer Black when I was in grad school.) The initial application of many of the quants' techniques were in markets like US equities, or listed options, where the assumptions that one participant couldn't affect the overall market much and that there were reliable sources of information were probably reasonable.

      But if you look at one of the key "villains" in this last mess, the credit-default swap [CDS] market, it's an entirely different story. I have read Li's paper on the Gaussian copula function, and had a look at an implementation. What it is essentially doing is using a statistical sampling function to estimate the expected lifetime to failure (= default) for a population of debt instruments. Now, there is nothing wrong with the math per se; similar approaches are used in manufacturing for quality assurance. However, there is big difference: estimating the failure rate of, say, light bulbs does not in itself have any effect on that rate. But in the case of the CDS, the failure rate is being used as an input to the model that is used to price the swap. If the default rate estimate is too low (too optimistic), the prices will be too high -- and that, in turn, will lead to lower estimates of the default rate. In essence, there is a built-in feedback mechanism that can act as an error amplifier, a problem that is exacerbated by the lack of transparency and liquidity in the CDS market.

      There's plenty of blame to go around. The managements, who should have known better, were bedazzled by the dollar signs floating out of their economic perpetual-motion machine. The quants knew the math, and their hubris led them to think that nothing else was needed. And the investors, while proving the truth of P.T. Barnum's Law of Applied Economics, forgot that there ain't no free lunch.

  2. How about... by blahplusplus · · Score: 4, Insightful

    ... getting back to the real economy? Many financial products don't add anything to the real economy at all.

  3. You can't blame it all on the qunats. by tjstork · · Score: 4, Informative

    Quants only produce models that act in the way that traders expect, and traders do not want bad news. I've done a small bit of modelling before and you always reach a point where there's this one number that is completely made up, and you kinda set things up so the trader makes the call. In this sense, all these models that everyone talks about are not so much as analysis tools as they are communications tools - you sorta code the insight of the trader as to how he or she thinks the market will move. It's a very human business, not one of a bunch of computers run amok. Quants that say otherwise are just full of themselves...

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    1. Re:You can't blame it all on the qunats. by florescent_beige · · Score: 5, Interesting

      ...you always reach a point where there's this one number that is completely made up...

      ***Try a sensitivity analysis using Monte Carlo techniques. That sounds hard but it isn't. Take the parameter that you have doubts about and give it a distribution (Gaussian or rectangular or something) with the mean at your best guess and the std deviation chosen to be big enough to cover the range it might reasonably vary over.

      ***Use Gaussian if you have an idea of what the parameter probably is but aren't exactly sure, rectangular if you really have no idea. A rectangular distribution says "I have no idea, the parameter could be anywhere within this particular range."

      ***Then run your analysis a million times with the parameter selected randomly from it's distribution for each run.

      ***That gives you a stochastic dataset of results. You can run simple stats on that data set to find the mean and std dev of the result value. You will then know how sensitive your results are to your poorly understood input parameter. If your 2-sigma output tells you the expected rate of return on a particular investment varies between -50% to +50% then you will know your model is pretty much useless and you will be doing a better job than the vast majority of professional analysts.

      ****Monte Carlo is great for those of us who don't care to learn the arcane minutiae of stat math. If you have a working model it takes an hour or two to extend it so you get stochastic results. Note that it's no harder to give a distribution to all your input parameters not just one. In which case you will be doing the kind of work that people who make 500 grand a year do.

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      Equine Mammals Are Considerably Smaller
    2. Re:You can't blame it all on the qunats. by tjstork · · Score: 4, Funny

      ***Use Gaussian if you have an idea of what the parameter probably is but aren't exactly sure, rectangular if you really have no idea. A rectangular distribution says "I have no idea, the parameter could be anywhere within this particular range."

      Guassian : So, make up three numbers, and assume that the middle number is -really- most likely.

      Rectangular : make up two numbers, assuming that any number in between them is good.

      In which case you will be doing the kind of work that people who make 500 grand a year do

      ROTFLOL. Yes, but they dress more nicely.

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      This is my sig.
  4. Hang on... by grcumb · · Score: 5, Interesting

    I'm a long way from New York, so someone correct me if I'm wrong[*], but I've always understood the problem to lie more with the people feeding data into the equations, rather than with the equations themselves.

    Now, I accept that risk calculations consisted of a great deal of voodoo because, as Taleb tells us, they tended to ignore 'Black Swan' events (where the 1 in a million catastrophe wasn't going to happen just yet) and saw patterns where only chaos existed, but as I understand it, the core of the problem was simple greed: money-hungry mortgage and securities dealers deliberately feeding bad data into the system.

    So-called quants may be decidedly imperfect, but if someone's willing to game the system to make a buck, nothing the quant does can stop it.

    If Wilmott doesn't have an answer to that, I fear that his efforts will only obscure the real problem.

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    Crumb's Corollary: Never bring a knife to a bun fight.
    1. Re:Hang on... by Guil+Rarey · · Score: 4, Interesting

      You're not wrong, but I think the author referenced in the original post and you are addressed different parts of the whole problem of financial markets. The willingness of financial services salespeople - mortgage brokers, stock brokers, etc - to basically lie their asses off because there's so much money on the line is one problem.

      "Quant" analysis of financial markets is, really, another, related problem. The same moral hazard of too much money to make cutting corners worth it exists, but the basic problem here is that many "quant" models are bullshit. Quantitive models for derivative securities can be realistically valued -- if and only if the risk of the underlying primary asset has been properly assessed (along with several other critical assumptions about the marketplace for the security -- but that's the JUDGMENTAL assumption fundamentally inherent in the models.)

      Risk assessment is not actually that difficult -- insurance is built on the ability to do risk assessment. The real problem with the current financial problems were that NO ONE KNEW WHAT THE UNDERLYING PRIMARY ASSETS WERE and everyone operated on the belief that Nothing Could Ever Possibly Go Wrong (because no one could prove otherwise, because no one knew what the hell was actually going on).

      This is and was every bit as monumentally stupid an assumption in the financial realm as it is engineering, computer programming, science, or any other real-world discipline.

      I think what Wilmott is proposing is the development of models that are more reactive to real-world inputs, models that are much more Bayesian in nature in their ability to refine and revise their predictive nature based on actual events.

           

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  5. The elephant in the room by owlnation · · Score: 5, Insightful

    You know, this is just tinkering. It's a way of passing the buck. It's a way of devolving blame. It MUST be the equations, or the software, or some geek or some technological prblem that caused the economics failures.

    It wasn't. It isn't.

    The reason why we have economic problems is the same old one from the beginning of time -- good old fashioned human greed.

    Equations, and new software isn't going to change that. What you need to do is ensure that the people operating systems and processes are ethical and honest. It's really that simple, and also, unfortunately, that difficult.

  6. The problem with economics is by RichMan · · Score: 4, Insightful

    The problem with economics is that is probably more a sociological study than a idealized science.

    Economics talks of supply and demand and perfect markets.
    Yet we all know the advertising and social herd behavior affect purchases much more than any real needs or demands.

  7. The One True Law of Finance by dplentini · · Score: 5, Insightful

    Nice idea, but Wilmot seems to have forgotten the most basic law of finance---nothing matters so long as you're making lots of money. Does he really think that the Quants on Wall Street and in London care about robust models and statistical significance? No! We're talking about used car salespersons in $5,000.00 suits. The financial industry is completely amoral. The only law is the law of the jungle. You can't confuse greed with a lack of quality control.

  8. Theocracy of Quants by Baldrson · · Score: 4, Insightful
    Wilmott suffers from the same thing that plagues all social scientists: They can't run controlled experiments to extract causation, yet they influence public policy as though they could.

    In another time, this would have been called what it is: theocracy, rule by theory.

    Oh sure, they can try to be inductive, but there is always that old "correlation doesn't imply causation" gotcha isn't there?

    The real solution to this problem with the social sciences was almost addressed by the Protestant culture that founded the US -- the Laboratory of the States -- but the incorporation of the slave states in the 1700s, with the resulting Amendment from Hell, the 14th, in the 1800s killed off that option entirely when "social science" sunk its fangs into the body politc in the 1900s.

    "The Union" means everyone is a slave to the theocrats posing as theoreticians.

    So now we're running uncontrolled experiments on nonconsenting human subjects in the guise of "public policy" of "liberal democracy" -- tyranny of the majority limited only by a vague laundry list of selectively enforced human rights.

  9. Picking up nickels in front of a bulldozer by turing_m · · Score: 4, Interesting

    The reason why the quants ignore Black Swan events is that they are not financially impacted by them to any real extent. They make their living from making small amounts of money using lots and lots of leverage. But I prefer Buffett's metaphor for this sort of practice: picking up nickels in front of a bulldozer.

    As long as "quants" can pick up "nickels" in front of a bulldozer for a few years, they can retire and never have to work again, even if their parent companies (and the companies they borrow from) go bankrupt. Those "nickels" are many millions, their percentage of those "nickels" are still high enough to retire on. Of course, they risk billions in the process.

    I suspect the only way to really curb the practice would be to either limit amounts of leverage or cause complete bankruptcy/imprisonment/physical harm somehow to those responsible when the bulldozer (the black swan) eventually comes along. Of course, these laws can't really be applied to those responsible for the GFC. Laws can and probably will be created, and then after a few generations those laws will be repealed as the creation of a few old fuddy duddies who didn't understand whatever "new economy" comes along, and the cycle will repeat.

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