The problem is that the financial elites don’t have even a layman’s grasp of the rocket science that underlies the models they use to gamble billions and to encourage their even more ignorant customers to throw money away.

Last week I described Nicholas Nassim Taleb’s explanation for the failure of the models used on Wall Street. In The Black Swan, he explains that all Wall Street models depend on the normal distribution, the bell curve, the Gaussian distribution. The problem is that top management felt justified in ignoring the events at the tails of the bell curve, the very thin parts at each end of the bell curve.

I have to disagree. IMHO, these are very smart guys who knew damn well what they were doing. Per Upton Sinclair: “It is difficult to get a man to understand something when his salary depends on his not understanding it.”

IMHO, these guys knew exactly what they were doing. The models assume that defaults on mortgages are not statistically correlated, which they would be if the housing bubble were to burst, and everyone knew that it had to burst eventually — what can’t go on forever won’t.

Also, in response to your statement at 13, there are non-linear systems that do not look like linear systems over a part of their range.

Also, to no one in particular, Axiom A attractors (a type of chaotic dynamical system) have gaussian statistics.

Finally, a question: Am I correct in believing that what this ‘multifractal analysis’ consists of is putting together simulated data using generators and multifractals, and using that, rather than a random number generator, to run Monte Carlo simulations to determine what a derivative instrument is going to do? If so, one can both be in favor of dumping the gaussian models and in favor of using derivatives, no?

And are people aware that computer random number generators are just chaotic dynamical systems that are sampled to produce different kinds of distributions?

Sorry for all the questions and comments, I get very muddled sometimes reading these things, about the fat tails especially since it seems to me that a distribution with fat tails (kurtosis) isn’t gaussian in the first place and the events in the tails are more probable than they would be in a gaussian distribution, check — but I can’t understand how anything in the distribution itself predicts the effect assigned to the event occurring (as in masaccio at 6).

I’m not that good at statistics, though.

I think what happened is the world changed (law and ideas) and they kept playing the same game with the same stupid ideas (ratings agencies paid for by debt salesmen) and the idea that if they just insured everything SOMEBODY would pay it off…meaning the taxpayers (who are already stretched to the limit) through the federal government.

They gambled, took all the winnings (for over a decade) and handed the losses to the public!

Beware of geeks with formulas

– Warren Buffet

He used to be over at RGE Monitor.

These are just the ones that I can think of off the top of my head. The fact is that markets and the financial system are being perturbed every couple of years. The idea that there is some golden equilibrium or Gaussian distribution is hogwash.

You mention the gold bugs. I have invested a bit from time to time. I have never found one that didn’t sound like a carnival barker.

I get the feeling that those you referenced are afraid of the word gold, afraid of sounding alarmist, or being tainted by the hustlers. Are there legit goldbugs?

I read somewhere that David Li, who showed how to use the Gaussian Copula to value collateralized debt obligations, also tried to explain their limits, but was ignored. Can’t find it now.

I blame top management anyway. They should have known those limits. Instead, they all used it with sheep-like intensity, and went down together, until they were buoyed up by taxpayers.