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The Formula That Killed Wall Street
Posted by
kdawson
on Tue Mar 03, 2009 08:10 AM
from the easy-go dept.
from the easy-go dept.
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."
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Science: The Perils of Simplifying Risk To a Single Number 286 comments
A few weeks back we discussed the perspective that the economic meltdown could be viewed as a global computer crash. In the NYTimes magazine, Joe Nocera writes in much more depth about one aspect of the over-reliance on computer models in the ongoing unpleasantness: the use of a single number to assess risk. Reader theodp writes: "Relying on Value at Risk (VaR) and other mathematical models to manage risk was a no-brainer for the Wall Street crowd, at least until it became obvious that the risks taken by the largest banks and investment firms were so excessive and foolhardy that they threatened to bring down the financial system itself. Nocera explores the age-old debate between those who assert that the best decisions are based on quantification and numbers, and those who base their decisions on more subjective degrees of belief about the uncertain future. Reliance on models created a 'false sense of security among senior managers and watchdogs,' argues Nassim Nicholas Taleb, who likens VaR to 'an air bag that works all the time, except when you have a car accident.'"
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Future of Financial Mathematics? 301 comments
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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the formula that killed wall street: (Score:5, Insightful)
G+R+E+E+D
Nothing wrong with models. (Score:5, Insightful)
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.
Parent
Re:Nothing wrong with models. (Score:5, Insightful)
However, there are some models that are just bad. If we take your climate change model example, simply going outside and measuring the temperature, and then comparing it to a temperature you took one the same day three years in a row and then plotting the statistical trend is a very poor model. Using that model, one might assume that we have drastic global cooling going on. It doesn't matter how much you rely on that model, if you rely on it all, you're going to be dead flat wrong.
Parent
Re:Nothing wrong with models. (Score:5, Interesting)
Parent
Re:Nothing wrong with models. (Score:5, Funny)
In Nazi Germany, global warming Godwins you?
Parent
Re:Nothing wrong with models. (Score:5, Informative)
Parent
Re:Nothing wrong with models. (Score:5, Insightful)
Parent
Re:Nothing wrong with models. (Score:5, Interesting)
it does not matter what model you use. Apparently they all created virtual worlds in big numbers (total value of derivatives and such is few times more than summed up gross domestic product of all countries on our planet) - this had to crash independently of the model - problem being that they used the same one. in other words: if all sheeple use the same model of reality then to make profit you need to use different one. Or to say it yet differently: if all sheeple do the same they create the bubble. nature of bubbles is that they burst when they reach physical limits of the stuff of which they are made. In our case it was human gullibility.
Parent
Preposterous! (Score:5, Insightful)
Preposterous! Human gullibility is one of the few things that has no limits.
Parent
Re:Nothing wrong with models. (Score:5, Interesting)
>>>they all created virtual worlds in big numbers - [the real world] had to crash independently of the model
Maybe we should invent a game for these bankers. World of Real Estate - where the goal is to get as many poor people into as many houses as possible, without investors learning the real housing value is only half the retail value. That way they can watch their virtual bubble go "boom" without affecting the rest of us in the real world.
Parent
Re:Nothing wrong with models. (Score:5, Informative)
Maybe you should get the facts before opening your mouth. Less than 5% of the mortages failed.
The banks however over extended themselves with the hope of using future profit to pay past due debt. Think of it this way. Balance your budget so you can pay all your bills. Now go max out your credit cards, take a second mortage and buy a couple more cars. Does it make sense? If so you have a future in banking, or government.
Parent
Re:Nothing wrong with models. (Score:5, Interesting)
Exactly. EVERY model that only sees rising house prices during it's data collection phase WILL assume that house prices will keep rising, and therefore tell bankers that dodgy mortgages are ok.
After all, as long as house prices keep rising, there is NO risk whatsoever in dodgy mortgages. Either you get the stated intrest (buyer pays mortgage) or you get the price rise of the house since the buyer bought it with your money (in the case of default) ... the risk of losing money in the deal is EXACTLY the chance that house prices drop. And house prices never dropped (significantly) in over 50 years ... obviously any statistical algorithm would have told you the risk was minimal.
Parent
Re:Nothing wrong with models. (Score:5, Informative)
This is why you can't build a model by looking at a list of numbers. You have to actually understand the source of the data. For example, to go back to the weather example: you can't forecast temperature by looking at a temperature log. You have to actually know something about the sun and oceans and wind and stuff. ;-)
It is foolish to look at investments abstractly. They're not just numbers. They're businesses (or houses or whatever) and they exist in the real world.
Some people say if you diversify enough, then you add so much noise that the sum becomes abstract, and you can start to treat it as a statistical problem rather than an intell problem. *sigh* Yeah, I guess you might get away with that.
For a while.
Parent
Re:Nothing wrong with models. (Score:5, Interesting)
Even more important that the limitations of a model are the assumtions taken in developing the model and/or feeding the data into the model, these should always be made clear to whomever the user of the model is, and it is then up to the user to decide if those assumtions are reasonable for their use of it.
The problem with this is most people's "just give me what I need to get the job done today" attitude. I've taught statistics in community college for a number of years, and I grapple with this a lot. Difficult enough to get people to perform the calculations for z-interval/test. Almost impossible to get them to consider the meta-analysis on whether the test is legitimate (simple random sample, assessment of normal population if sample size small, known standard deviation, etc.)
If most days they can get away with ignoring the model's assumptions, then folks wind up doing so, and then that knowledge degenerates. Ultimately the exceptional day that they need that skill, they don't have it. People function very, very poorly in relation to very infrequent (once a generation?), catastrophic events.
Parent
Re:Nothing wrong with models. (Score:5, Informative)
Here's a link to Taleb's views on the financial crisis:
http://www.edge.org/3rd_culture/taleb08/taleb08_index.html [edge.org]
It's an easy read with nice quotes like " The banking system (betting AGAINST rare events) just lost > 1 Trillion dollars (so far) on a single error, more than was ever earned in the history of banking."
and "I have nothing against economists: ... But beware: they can be plain wrong, yet frame things in a way to make you feel stupid arguing with them. So make sure you do not give any of them risk-management responsibilities."
I can't find the quote (I think it is in "The Black Swan" or "Fooled by Randomness") but I'm pretty sure that Taleb's comment on Li's Cupola is that it is a pretty piece of mathematics whose essential problem is that it never worked for what people were trying to use it for.
Parent
Re:Nothing wrong with models. (Score:5, Interesting)
>>There is nothing wrong with using a model. Models are good.
Not in economics, they're not. The book Black Swan, which should be read by anyone interested in this topic, says that the hideous lie is that people claim that "they're better than nothing", when, in fact, they're worse than not having any model at all.
The LTC crash was caused by the founders (Nobel Laureates in Economics) having a model to quantify risk. IIRC, they used some sort of guassian model, taking the standard deviation of price movement as "risk". (http://en.wikipedia.org/wiki/Black-Scholes#Black.E2.80.93Scholes_model) This of course looked good until, quite suddenly, it wasn't and there was an event that their model predicted shouldn't have happened within the lifetime of the universe (that's the problem with using gaussians instead of cauchy curves or other fat-tailed distributions) and the company crashed and burned, and did a lot of collateral damage as well.
From the wikipedia article on LTC (http://en.wikipedia.org/wiki/Long-Term_Capital_Management): Merrill Lynch observed in its annual reports that mathematical risk models, "may provide a greater sense of security than warranted; therefore, reliance on these models should be limited."
Parent
Re:Nothing wrong with models. (Score:4, Insightful)
Considering how much impact human emotion and irrationality has on the markets I would tend to agree. Is today's bubble burst any more significant because of their use of models? Not really. The simple fact is they used a tool incorrectly and in their job, instead of sawing a finger off, they lose billions. But what drove this? Human emotions. Perhaps one day we can accurately model this, but I'm not so sure.
Parent
Re:Nothing wrong with models. (Score:4, Funny)
And it is a big but. You must know the limitations of your model.
Is that you, Sir Mix-A-Lot?
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Re:Nothing wrong with models. (Score:4, Funny)
Parent
Re:Nothing wrong with models. (Score:5, Insightful)
I disagree. A model defines a static or pseduo-static system. It takes the non-linearities out of a system to make them as close to a linear, 1st order or 2nd order system as much as possible, such that you can produce matrices of inputs to outputs. All models also are accompanied by regions of legitimacy.. Namely the non-linear (or super non-linear) components press close to zero in these regions. Outside the regions, those non-linearities become too much 'error' for the model to be valid. Ideally, you can use separate models for different regions, and you have a nice continuum. But for that, you need to be able to first measure a region parameter.
The problem here is that you're talking about a model for an investment strategy that is inherently non-deterministic, non-linear and more importantly recursively adaptive. The region you're operating in, is part of the outcome variables.
Consider 3 investors each with equivalent information systems (including risk modeling, present-valuation, and product-viability forecast, whatever).
In a vaccum, a model, assuming a static system might be appropriate. Balance-sheets, due-dilligence, market trends, geo-politics, etc. are all valid. But consider that the other two investors have the power to effect the system. Consider that they can manipulate, propping up an industry, or willfully collapsing it (over-buying, or short-selling). By acting irrationally in the short term, they can sufficiently distort all the measureable parameters to your equation to force you to act inappropriately.
Thus by taking a short-term hit, one of your competitors can gain a much greater long term advantage.
Thus, KNOWING that you use certain models, allows your competitors to game the system.. Note they need to have significant resources in which to do this.. But the old addage that you need money to make money exactly applies here. Why would a wealthy person only accept 3% to 15% ROI when they can control certain markets and earn 500%.
Now explicit market manipulation is illegal. But there is nothing illegal about gambling (sadly). Thus betting against the 'known wisdom' is perfectly legal.
So now you have two camps.. Conservatives that trust their models (blind to the fact that people can manipulate them in the long-run). And advanced speculators who bet against the market. Over time, if one is considered unbalanced, then more and more itchy investors will switch from one side to another.. Until an equilibrium is reached where any and all metrics become meaningless - An equal proportion of investors will honor measureable data as there are people betting against the data. The raw data therefore has no material impact as to the future valuation of an asset. Note, as such a system evolves, the 'measureable' data will change over time. Namely instead of measuring the viability of a company, you measure the prospects for news and bet based on historical trends of the news outlets, not whether the news is good or not.
This can only happen if you have a gaussian distribution of strategies. Namely a massive pool of investors operating independently with an equal liklihood of choosing one of an infinite number of strategies, such that an equal ration of buy/sell decisions could be produced.
You can think of it as the classic "Is the poison in your drink or mine" attempt at gaming the system. Any number of strategies can be employed to decide which action is best, but the more you employ, the greater resemblance to random-decisions is created.
The short is, no formula can adequately valuate a market that is based on such a recursively adaptive system. Determining the risk of a car accident, a plane accident, a flood, etc. These are deterministic to a large degree (short of global warming and legalizing pot). But the college that first advocated investment strategies based on such finite metrics should be unaccredited in my view. A car owner isn't trying to game the insurance market, but a stock holder or company seeking stock value is.
Parent
Re:Nothing wrong with models. (Score:5, Insightful)
You also don't need an MBA to know that there is a limit to the number of balls a juggler can keep in the air at any time before he drops one. And when one ball drops, the whole thing falls apart. As the truism goes, those who don't learn from history are doomed to repeat it...
Parent
Re:Nothing wrong with models. (Score:5, Insightful)
As most of the people responsible walked away with a fat profit, one could posit that they did learn from history. Why should they care that they screwed over the rest of us? Our economic system ignores externalities on that scale. Burn down a house, go to jail. Burn down the economy, get a fat bonus.
Parent
Re:Nothing wrong with models. (Score:5, Insightful)
Burn down the economy get a big fat check is about right.
The problem with slow justice, is that it gives the appearance of no justice. Bernie Madoff will, in all likelyhood, die without spending a day in PMITA Prison.
And his family will keep the benefit of all the Billions that disappeared, because all the assets in trusts and such are untouchable by the law, even if they are ill gained. That is what a trust was created exactly to protect. Trusts are nothing more than legal money laundering.
And there is nothing wrong with making a profit. The problem isn't profit, or even greed. The problem is that people will use the rules in place to screw others and hide the loot. It doesn't matter what the rules are, and the more complex the rules, the easier it is to hide malfeasance. More rules don't stop it. People will do evil regardless of the rules.
Bad people don't follow the rules, and will use the rules as an excuse to do bad. They use the rules to take advantage of others. Once people realize that rules are for the law abiding, not the law breakers, then we can get rid of all the stupid rules which don't prevent anything.
Parent
Re:It wasn't Li's fault. (Score:5, Insightful)
>The managers making the decisions didn't know what it all meant and the guys using the model didn't adequately explain the model's limitations.
Or the managers didn't understand their explanations -- or more likely yet, didn't *want* to understand their explanations.
This doesn't look fundamentally different than the Challenger explosion: the technical staff knows there's a problem, keeps saying that there's a problem, but their upper management is invested in there not being a problem. It's really difficult to explain something to someone whose job depends on ideas that conflict with what you're explaining.
Parent
Re:the formula that killed wall street: (Score:4, Interesting)
Greed is a motivator. Greedy people will work hard to acquire money. Capitalism & free enterprise allow a society to harness greedy people for positive ends like the creation of jobs to produce valuable goods and services. This is a good thing. Unfortunately, greedy people are not necessarily *smart*. And even the smart greedy people are not necessarily *correct* when they do things a particular way.
The story sums it up nicely - this formula oversimplifies a complex market creating a classic bursting bubble. There's an economist named Taleb http://www.fooledbyrandomness.com/ [fooledbyrandomness.com] lecturing about how the market will basically always be more complex than you think.
The best part about his message is in not trusting your data too much. I think of this every time people start talking confidently about geoengineering. We don't know as much as we think we do.
Parent
Re:the formula that killed wall street: (Score:5, Insightful)
actually, greed is good. it's the great motivator. really, it's the only motivator.
It's a good motivator when it's tempered with wisdom. It's a bad motivator when you blinds you to the long term consequences of your actions. I've been saying for years that it seems like our entire economic system has been tailored to next quarters results at the expense of building/investing for the long term. Who cares if this quarter has record profits if you paid for those record profits with the future viability of your enterprise?
Parent
Re:the formula that killed wall street: (Score:5, Interesting)
yes, i completely agree with you. the focus on quarterly earnings is representative of "short-termism" everywhere, which is usually detrimental to long term value preservation.
i guess what i should have said is that greed is not going anywhere. harness it when you can and don't be surprised when it causes people to do things that harm others.
Parent
Tribute to Huntz Hall... (Score:5, Funny)
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!
Citation, please (Score:5, Interesting)
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.
Re:Citation, please (Score:5, Informative)
Notice any similarities here [stlouisfed.org]? No, it's not a perfect fit, but it's the best I could do on short notice.
No one is saying that these models have nothing to do with malinvestment, but it's likely the inputs to the model are also obfuscated by distorted monetary signals
Parent
Re:Citation, please (Score:5, Insightful)
With respect, classical economics and Austrian economics are not quite the same thing
Sorry, I'm not an economist. Therefore if I said something incorrect through ignorance I apologize. I merely wished to emphasize that truly we live in interesting times. I think it's when the world (and especially the consumer intensive US) finds out we've bumped into the limits of our resources on this planet. We can't all have an SUV. We can't all waste electricity. We can't all have a worry free life, and independence, and a nice house, and a big screen tv, and eat in good restaurants, etc. The boom in commodity prices - in part fueled by massive demand from the BRICIT countries that are also expanding their middle classes and trying to adopt an "American" standard of living - has another side to it. Not only was demand increased - but supply is at or near maximum. There IS no more copper, there IS no more gold, platinum WILL run out in 20 years or so, etc.
Therefore commodities (including petroleum) priced themselves right out of the market. This triggered, and is triggering, financial default from everyone who was living "the dream" on credit. And now the cards keep tumbling. Oh, we will reach a new equilibrium some day - but our population keeps expanding, and those resources keep getting more scarce.
Parent
Re:Citation, please (Score:5, Informative)
You didn't LOOK at the graph, did you? That's my citation.
This [msn.com] is the last 2 years, with that "almost completely VERTICAL" drop.
This [msn.com] is a 2 year span at 1929, that little tiny blip on the left of your zoomed out chart. Notice how it's actually more vertical than the current drop?
This [msn.com] is your chart, redrawn to have a log scale vertical axis instead of linear. It looks like "now" is roughly comparable to 1938 or the early 1970s.
Parent
One word (Score:5, Insightful)
Diversity.
Or there's my financial formulae (Score:5, Insightful)
- 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...
Not Wall Street. Us. (Score:5, Insightful)
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.
Re:Not Wall Street. Us. (Score:5, Insightful)
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.
Parent
Re:Economic Stimulus (Score:5, Interesting)
In China, they're using this slack time to upgrade the infrastructure, closing down old inefficient factories and building new ones with government CASH. Who's winning this round?
Not the millions of migrant chinese workers who have lost their jobs, which will probably also cause civil unrest. Also, the Chinese holding trillions of dollars in U.S. treasuries will also be slightly annoyed when the U.S. government inflates away their debts.
Finally, the vast majority of China's stimulus package was already announced before this major recession. You have the order backwards.
Parent
Picking up pennies in front of bulldozers (Score:5, Interesting)
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.
Re:Picking up pennies in front of bulldozers (Score:4, Insightful)
Except that the current economic woes don't fit into Taleb's "Black Swan" category. It was obvious that his was going to happen to anyone with one brain cell 5 years ago, and to anyone with two brain cells a decade ago.
I'm pretty sure I heard an interview with Taleb in which he mentioned this. Of course his strategy of investing to break even in the expected conditions and make out like a bandit when a black swan appears would have done very well as risk was repriced.
Parent
Re:Picking up pennies in front of bulldozers (Score:4, Interesting)
Otherwise, it's all just blind gambling (which it isn't far off, anyway).
The advent of full on algo trading means that random events in the market have the ability to wipe out tons of capital because the models predict (e.g.) a global crash when it's just a blip. (Extreme example)
The other part of the problem is that traders are nowadays just glorified clerks in that all (well, 90%+) of the actual calculation and predictive work is done by complex platforms (or Excel), so they don't really care or have exposure to the real risks behind their trading.
Coupled with the huge bonuses they used to get (I'm in London where bonuses are being denied; is it the same elsewhere?) as long as they showed *quantity* of trades, it was always a recipe for disaster.
Parent
Re:Picking up pennies in front of bulldozers (Score:5, Insightful)
If they are random then why do they predict economic change with 100% accuracy?
HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA!
*gasp gasp*
HAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHAHA!
*pant pant*
HAHHAHAHA, oh God that's rich. Seriously, you meant that? HAHAHAHAHAHAAHAHAHAHAHAHAHA!
*wipes tears from eyes*
No other reaction is possible for such a statement. Is this a delayed posting from 2007? Not that it wouldn't be equally laughable, but at least it was conceivable to maintain the self-delusion that it isn't. Today? You're saying the economy is 100% predictable, and you're saying this today.
HAHAHAHAHAHAHAHAHAHAHAHAHAHAHA!
Parent
yeah...not so good (Score:5, Informative)
An interesting article, for sure. The issue with the Gaussian Copula model for pools of mortgages in CDOs is how sensitive they are to the assumptions of the model. If, for example, the annual growth rate of home prices is 2% instead of 10%, things look tremendously different. If correlations between housing prices in different cities is 50% instead of 10% -- disaster. The lack of stress testing of these models (checking what the results are for different inputs into the model) was a huge issue. Even if a model is decent (which in principle, copula models are), if they are too sensitive to inputs, then the prices it produces are not trustworthy. If the proper uncertainty was taken into consideration, then perhaps everyone would have been a little less gung-ho about CDOs.
Like the (worthless) Value-at-Risk figure, the (also pretty worthless in the end) Gaussian Copula was "easy" to understand. Given that the dynamics of financial markets are not simple and easy to understand, reliance on simple models that are easy to explain to the MBAs is probably not the best idea.
Thou shall not calculate behaviour (Score:5, Insightful)
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.
Don't Blame the Equation (Score:5, Insightful)
This seems to be a popular story for the past few weeks, but it is a mistake to blame the statistical method used. The problem wasn't that they were all using the equaton, it is that they were all mis-using the equation. All statistical tools can fail to be sensitive to certain aspects which may be critical to an application.
People in finance applied these statistical tools believing that they would be able to master risk with them. Unfortunately, they made assumptions that certain things would continue to be the same in the future, plugged the information into the equation, and now science was telling them that everything would be alright. If everybody on Wall Street was making decisions based on the Magic 8 Ball would we blame the ball or the foolishness of those misapplying it?
Yeah right. (Score:4, Insightful)
Complete BS. The Wall Street knew all along the bubble would burst, and cashed in all the time while knowing it. In essence, they kept milking while perfectly well knowing it would come to a disaster.
There's a crisis every 10-15 years. Huge crisis in every 30 years. How can some one be that gullible as to believe the economics would NOT see this coming? Of course they did, but saying and doing something about it would be bad business. It would scare off the suckers... who end up paying the bill.
Happy square root day! (Score:5, Insightful)
The love of money is the square root of all evil.
This formula may have and probably did help crash the world's stock markets (yesterday's Dow Jones was HALF of its worth at its high last June), but the reality is that high energy prices drained everyone's wallets.
When Bush took office, gasoiline here in Springfield was $1 per gallon. At Wall Street's high last summer it was nearly $4.50, over four times as high. We talk about elders living on a "fixed income" but the fact is almost all wage earners' incomes are fixed. We can't demand raises or overtime and have to live within our means. But when that $20 per week gasoline budget quadruples to $80 per week, with heating and electric costs going up as well, that takes money out of other aspects of the economy. Sooner or later people are over their heads and behind on bills, and things spiral out of control.
The result of that and other factors is what you see now.
Happy square root day, everyone.
Diversity is good, 'mmkaay? (Score:4, Interesting)
Any sufficiently complex system should be heterogeneous, so that not all parts of the system can fail due to the same flaw.
Any homogeneous system will inevitably be at greater risk of failure due to a flaw in the common "gene pool" so to speak.
Biology, computers, economics, politics... I could go on.
This Is Their Bullshit Cover Story (Score:5, Insightful)
Yeah, "complex mathematical model". Tell it to the judge.
They did indeed use this model, and the work of many other PhD mathematicians, physicists, and other geniuses. But any of the bankers could have looked at this whole class of derivatives from mortgages and seen the basics that make the model a joke. They sold millions of mortgages and other loans to people using artificially low initial interest, to get people to take the loans, but which ballooned to rates they couldn't afford, so they'd have to default. Inevitably, a large percentage would certainly default. A losing bet overall for banks holding those loans. Meanwhile, each bad loan was "good" because the banks could sell many times the number of derivatives on it. Which was "good" because they got paid for the derivatives they sold, but was much more "bad" because the derivatives would cost the issuing bank many times more when it came due. The derivatives came due when the mortgages defaulted. Which was inevitable.
So whatever "gaussian copula" model they use to convince each other it was good, basic business sense would have insisted that the business was bad, horribly bad. These bankers don't get paid for discovering new math, they get paid for their years of experience and business sense. So they should have laughed this model out of the boardroom, even if they didn't understand why it was wrong. They should have known it was wrong, as the past few years proved beyond any doubt. But they embraced it instead, and centuries old banks like Lehman Brothers have gone down, taking us with them (and no end in sight).
Because ultimately, the model was a way to delay the costs of a business that paid some fat revenue up front. Since bankers are paid in huge bonuses for the initial year of revenue, and then leave before the bills come due , they got paid to make those bad deals, because they paid off up front, before costing many times more their benefit a few years later. By which time the bankers are gone with their early bonuses. Which have a lot more buying power when the economy collapses, and everyone else is holding merely the debt they created.
Nice work, if you can get it. Since they ruined the banking system and everything else, no one can get any work at all.
These people are holding the money. Their bonuses often equal the losses that destroy their bank. The government should take back that money to pay for fixing and repairing some of the mess they made. "Fiduciary responsibility" is a requirement of bank execs, and these violated that by the $TRILLIONS. Make them pay for what they did. That's a simple model anyone can understand. Not just a complex conjob to hide behind.
Oh Please... (Score:5, Interesting)
There's nothing advanced or innovative about a gaussian copula. It's a very simple mathematical trick, it doesn't say anything about finance in itself. It's a programming trick to go from a uniform distribution on a cube (easy to generate, run rnd() for each coordinate) to a multivariate gaussian with a specific covariance matrix. The way to do it is cholesky decomposition. This is OLD stuff.
Li's paper is a clever way to measure default correlation using correlation matrixes from asset returns. It's quite clever, and yes it's a pretty good model (more on that later)
This is not journalism, this is a bit of shit where the author decided having an "evil formula" would be cool. Look there's an "equal" sign, how can they be so sure... pffffffffffffffff.
I said it was a good model, yet it's been proven wrong hasn't it? Well, first of all, what has been shown to be wrong is the guesstimate of correlation that was input into the model. G.I.G.O
Plus, if you price a fixed income product and it produces higher than market return, you will borrow short term funds to invest them in it. In a free market that quickly drains the pool of saving and raises short term interest rate. Sure you end up losing money but no catastrophe. In a federal reserve system, well the short term rate stays what the fed says it should be and everyone piles on the arbitrage, creating sky high leveraged position.
Yeah the formula can be misleading, but for a true catastrophe, you need a federal reserve.
Greed (Score:5, Insightful)
Blaming greed for a financial crisis is like blaming gravity in a plane crash.