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The Formula That Killed Wall Street
We recently discussed the perspective that the harrowing of Wall Street was caused by over-reliance on computer models that produced a single number to characterize risk. Wired has a piece profiling David X. Li, the quant behind the formula that enabled the creation of such simple risk models. "For five years, Li's formula, known as a Gaussian copula function, looked like an unambiguously positive breakthrough, a piece of financial technology that allowed hugely complex risks to be modeled with more ease and accuracy than ever before. With his brilliant spark of mathematical legerdemain, Li made it possible for traders to sell vast quantities of new securities, expanding financial markets to unimaginable levels. His method was adopted by everybody from bond investors and Wall Street banks to ratings agencies and regulators. ... [T]he real danger was created not because any given trader adopted it but because every trader did. In financial markets, everybody doing the same thing is the classic recipe for a bubble and inevitable bust."
G+R+E+E+D
I want peace on earth and goodwill toward man.
We are the United States Government! We don't do that sort of thing.
Enter Li, a star mathematician who grew up in rural China in the 1960s. He excelled in school and eventually got a master's degree in economics from Nankai University before leaving the country to get an MBA from Laval University in Quebec. That was followed by two more degrees: a master's in actuarial science and a PhD in statistics, both from Ontario's University of Waterloo.
He has more degrees than a thermometer!
In financial markets, everybody doing the same thing is the classic recipe for a bubble and inevitable bust.
Citation? Booms and busts are caused by, respectively, expansion and contraction of the money supply (usually in the form of bank credit), often accompanied by manipulated interest rates. The formulas used by lots of investing firms could cause clusters of errors, but the extent of types of companies (and governments) affected points to a more Austrian-style, systemic boom/bust rather than a single-(important-)sector miscalculation.
There is nothing wrong with using a model. Models are good. They help us simplify the world so that we can understand it. For example, we have hundreds of competing climate change models that explain what is going on and predict what we should expect. We model the weather for forecasts. And so on.
But. And it is a big but. You must know the limitations of your model. By definition, a model is a simplification of a complex phenomenon. That does not make it flawed: that makes it a model. Overreliance on the model is your fault, not the fault of the model.
This game will waste your life. Don't clicky!
Diversity.
Life is not for the lazy.
- Don't spend the money you don't have
- Don't do credit unless you absolutely have to
I know I know, Wall Street are these big finance hotshots who do complicated things that have nothing to do with personal finances, but what is it they do apart from speculating and playing with money they don't have, or other people's money? They just hide that simple fact under abconce financial constructs, but that's all they do in the end.
Bring back some morals sanity in the credit business and there won't be anymore crisis of this magnitude. No need for math here...
"A door is what a dog is perpetually on the wrong side of" - Ogden Nash
It isn't killing Wall Street. Those jokers are getting $billions$ in free money.
It's killing us, the people who work for a living and have to provide all those $billions$ or suffer the inflationary consequences when the Feds just print it.
That Gaussian curves are a poor model for unlikely events has been known for quite some time. This is best explained by Nassim Taleb in the following books:
His main thesis is that the markets are essentially random and are basically impossible to predict in any meaningful way. Further there are unlikely unknown unknowns can cannot be predicted until the they occur, usually with disastrous consequences.
---- It won't be as bad as you fear or as good as you hope, but it will take twice as long as you plan.
A BIG part of the problem is Washington's tendency to reward economic losers at the expense of the people who know what they're doing, and I'm NOT just talking about the poor. There are plenty of the high-salary types who have some sort of governmental loophole or backing that saves them when they screw a big company up.
It's one reason we don't need to be bailing out bad companies, and instead rewarding or backing up the good ones with incentives and tax cuts so that they can really succeed and push forward.
This brings me to the crucial issue. Unlike the position that exists in the physical sciences, in economics and other disciplines that deal with essentially complex phenomena, the aspects of the events to be accounted for about which we can get quantitative data are necessarily limited and may not include the important ones. While in the physical sciences it is generally assumed, probably with good reason, that any important factor which determines the observed events will itself be directly observable and measurable, in the study of such complex phenomena as the market, which depend on the actions of many individuals, all the circumstances which will determine the outcome of a process, for reasons which I shall explain later, will hardly ever be fully known or measurable. And while in the physical sciences the investigator will be able to measure what, on the basis of a prima facie theory, he thinks important, in the social sciences often that is treated as important which happens to be accessible to measurement. This is sometimes carried to the point where it is demanded that our theories must be formulated in such terms that they refer only to measurable magnitudes.
It can hardly be denied that such a demand quite arbitrarily limits the facts which are to be admitted as possible causes of the events which occur in the real world. This view, which is often quite naively accepted as required by scientific procedure, has some rather paradoxical consequences. We know: of course, with regard to the market and similar social structures, a great many facts which we cannot measure and on which indeed we have only some very imprecise and general information. And because the effects of these facts in any particular instance cannot be confirmed by quantitative evidence, they are simply disregarded by those sworn to admit only what they regard as scientific evidence: they thereupon happily proceed on the fiction that the factors which they can measure are the only ones that are relevant.
Hayek. Nobel Prize Lecture, 1974.
Preposterous! Human gullibility is one of the few things that has no limits.
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