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Home arrow Business & Finance arrow Frequently Asked Questions in Quantitative Finance

Name and Shame in Our New Blame Game!

(In late 2008 we ran a survey asking members of wilmott.com who or what they thought was to blame for the 'crisis. Here are some of their responses together with comments from me.)

We now have the results for which are the worst quant models according to the contributing members of wilmott.com! Here I reveal these worst models and concepts (etc.), and other interesting bits and pieces mentioned by members. I will also give you a few words, condensing my thoughts on each culprit.

In alphabetical order, the guilty parties and ideas are below. The * means that I disagree.

Auditors: They are generally considered clueless. And that s also true of governments and regulators generally speaking. How can they hope to stop the determined big brains at most investment banks? (Even if those big brains did cause their own banks to collapse they did so while taking home enormous bonuses, this doesn't demean the size of those brains in any way! Au contraire.)

Basel: Committees! Effectively a little bit of public sector mentality infiltrating the private sector. Except that such committees are actually deceptively self serving and destructive.

Complete markets: See below for risk neutrality.

Collateralized Debt Obligations, etc. ABS, MBS: Probably among the stupidest, most naive, and yet most complicated quantitative finance modelling can be found behind these instruments. I warned you they were dangerous, the two main reasons being they are credit instruments, see below, and because of correlation. All correlation instruments are dangerous because correlation is such a simplistic tool for modelling the subtle relationships between financial assets. At least they are dangerous unless there is a large inbuilt profit margin (margin for error) and unless they are traded in small quantities. Large quantities and small profit margins lead to disaster, but you know that now.

Credit modelling: Burn all credit books, except those that say that the modelling is rubbish. (Which I do in my books, so don t burn those!) Default is not a probabilistic event, a coin toss, it is a business decision.

Copulas: An abomination. Such abstract models that only a few people, mostly with severe emotional intelligence problems, really understand. (One often gets the impression when speaking to certain types of mathematician that 'they are not all there.' I think you know what I mean! And if you don't ... oh, dear, you are one of them!) Quote from the section on copulas in PWOQF2 written in 2005: ''I have to say that some of these instruments and models fill me with nervousness and concern for the future of the global financial markets.''

Efficient Market Hypothesis: Hypocrisy of the first magnitude. ''You can t make money from the markets, but give me a million-dollar bonus. Either hypocrisy, or material for a psychiatric journal s article about lack of communication between left and right sides of the brain.

French Polytechniques: I interpret this entry as meaning generally education that is too abstract and lacking in practicality, i.e. those who think that 'maths is both necessary and sufficient for finance' when clearly it is only necessary! As someone who has devoted the better part of two decades trying to educate people to be responsible quants it has always annoyed and frightened me that universities have churned out so many 'quants who are both over educated and under experienced. That universities often prey on young people just out of a first degree is therefore not surprising. It is pleasing to see at last a wider recognition that such people are better suited to academia than to banks.

Gaussian distribution*: (Note, this does not mean Gauss is to blame!) - I disagree about Gaussian distributions. See standard deviation.

Insurance methods: Presumably this means using the Central Limit Theorem in conditions where the CLT doesn't hold. An example of a great theory being misused. Actuaries have long felt a bit jealous of quants, since they start out with similar skills but actuaries aren't quite as glamorous (am I really talking about mathematicians being glamorous?!) and certainly don't earn as much. It goes back to quants' relationship with hedging, a trick that actuaries feel they ought to have spotted. Quants could learn a lot from actuaries, including the proper use of insurance methods. But I expect the 'education' will go the other way, actuaries will learn quant methods ... does this mean a collapse of the insurance industry next? Oh, how could I forget AIG?!

Mathematics: Well, you know my strong views on this! Dumbing down is bad because then you can't price sophisticated instruments and you don't know all the risk. Making things too complicated may be even worse, people fool themselves into believing the models, they are blinded by the maths (see Copulas and CDOs, and especially French Polytechniques, above). All is not lost ... from my blog: ''Ok, the big secret ... Quantitative finance is one of the easiest branches of mathematics. Sure you can make it as complicated as you like, and plenty of authors and universities have a vested interest in so doing. But, approached correctly and responsibly, quant finance is easy.'' In a Phil. Trans. article published in 2000 (The use, misuse and abuse of mathematics in finance) I warned that ''a major rethink [of financial modelling] is desperately required if the world is to avoid a mathematician-led market meltdown.'' Good, huh? We may have just about avoided this, at possible medium- or long-term cost to the taxpayer (but who could still profit if the accountants and the government get their acts together) and to the economy (which is definitely screwed for a while). If banks, funds, regulators, governments don't see the light now then lord help us!

Media*: Shoot the messenger! I disagree. When short selling was banned people said it s necessary for price discovery. In that case we need the media as well. (I m in favour of short selling but I thought the argument about price discovery was silly. Go to a supermarket you ll see the price of products falling if no one wants them, and you can t short baked beans. Or maybe that's too slow a mechanism, perhaps we need short selling to speed up price discovery. What, are the markets too slow for you? Yee-ha!)

Off-balance Sheet Vehicles: Quants + Lawyers + Accountants = Chaos + Disaster + More money for Lawyers and Accountants. Hey, quants, you're getting a bum deal here!

Quants: Unwitting stooges or guilty accomplices? Perhaps even Mister Bigs, the masterminds. Did they get a bonus? Yes. Did they blow the whistle? No. Then guilty as charged, M Lud.

Ratings agencies: As mentioned in my NYT Op-Ed piece, ''moral hazard so strong you can almost taste it.'' Also my favourite contender for defendants in lawsuits, any day now! And I m available for prosecution expert-witness work, very reasonable rates in a good cause.

Risk neutrality: I estimate that about 2% of people working in derivatives and risk management really understand this fundamental concept. Yet probably the vast majority of them use it on a daily basis, knowingly or not. Of course, the validity of this concept depends on certain assumptions, no frictions, perfect hedging, known parameters, i.e. it's not valid. But maybe it still works even if not technically valid, perhaps the idea is somehow robust? Well, sometimes it is, sometimes it isn't, but probably only 0.02% of people in this business know why and when.

Risk Metrics: Making VaR, see below, accessible to the masses. Why not give away handguns while you're at it?

Standard deviation*: I disagree. I see the point that standard deviations may not exist for many/most financial distributions. Thin tails versus fat tails. But the extreme events still only happen relatively infrequently, and throwing away standard deviations would be throwing away the baby with the bathwater! It might add complexity that would actually be worse than the simplicity and transparency that it replaces. For normal (in both sense of the word) markets standard deviations are fine. I advocate using worst-case scenarios for extremes that might cause banks, or economies, to collapse.

Value at Risk: As one of the cartoons in my books says ''I've got a bad feeling about this.'' VaR is used to justify taking risks. Classic unintended consequences territory this. Yeah, right! Funny how ''unintended consequences'' are always rather obvious, even before the fact, but they are always brushed under the (expensive silk) rug. ''Don't rock the boat, dear boy,'' cigar in one hand, Napoleon brandy in the other. Risk managers say there's no risk according to naive VaR models, so management is free to trade in bigger, and bigger, and bigger, amounts. Oops ... it seems that VaR didn't quite capture all the risks ... who'd have considered rising interest rates and increasing mortgage defaults? Answer: Everyone, except those who had a vested interest in hiding the risks.

 
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