Computer Models and the Global Economic Crash
Anti-Globalism passes along a review in Ars of some recent speculation on the role of interconnected computer models in the global economic crash. "If Ritholtz, Taleb, Mandelbrot, and the rest of the computer modeling and financial engineering naysayers are correct about the big picture, then we really are arguably in the midst a bona fide computer crash. Not an individual computer crash, of course, but a computer crash in the sense of Sun Microsystems' erstwhile marketing slogan, 'the network is the computer.' That is, we have all of these machines in different sectors of the economy, and we've networked all of them together either directly (via an actual network) or indirectly (by using the collective 'output' of machines in one sector as input for the machines in another sector), and like any other computer system the whole thing hums along nicely... up until the point when it doesn't."
I am not an economist but I have owned a couple businesses and consider myself a reasonably practical person.
I have always believed that the vast majority of today's financial instruments have been invented out of thin air for no reason other than to ultimately ensure the employment of bankers and brokers.
For example, lots of people have a checking account, savings account, credit card, poersonal line of credit, HELOC, brokerage account, and more. I see absolutely no reason why a single account could not offer all those features. The only reason you "need" all that is because the banks created all these funny rules so that they could introduce more and more products and services. This is done so they can charge you more for each of those things, and also to differentiate them from their competitors.
Besides consumer banking, can somebody explain to me why we NEED "commercial paper"? Yes, I've read the wikipedia page and I know how it's used, but I don't understand why it's needed. If you can't make payroll then you're pulling from your credit one way or another - why do we need separate instruments for a 2 week loan versus a longer term loan, or a credit card, or whatever?
And don't even get me started on real estate lending...
It's like freaking starbucks - you can get your banking services just as special as an upside-down triple no foam half calf non fat 160 degree two splenda mocha. But it's one thing for a coffee company to cater to every individual snowflake's desire, and quite another IMHO for something as important as our financial system to become as absurdly complex and fragile as it is.
As for the people who are really benefitting from all this complexity - well, it's only during recession that we all collectively take a good hard look at who's making a contribution to society and who isn't. Unfortunately the powers that be think they can beat a recession by tweaking some rates, stealing from taxpayers, or shuffling money from one hand to the other. That's just going to hurt us more in the long term. We need to clean this shit up now - get rid of unnecessary products and overhead, and let the unproductive companies go bankrupt. Let the UAW strangle themselves to death. Just get it done.
Two words: "emergent behaviour".
No one group of programmers programmed all these computers, there was no single set of specs for the whole network. All the components may well be "functioning exactly as they should be" (although in reality I'm sure there are a few bugs in the systems, but that's irrelevant here), but the system overall may behave in an unexpected way.
(That said, I don't think that's the whole problem either -- too many people playing a bit fast and loose and less than honestly with other people's money is also part of the problem.)
-- Alastair
What is tightly regulated? Half the Quant algo trading models get thought up in the evening, coded overnight and activated in the market the next morning.
If you try and slow them down they just run to the head of the desk bleating that the "nasty IT man stopped me making $1000,000,000 for the bank with his silly QA nonsense" and whoosh, its in production. It is prop trading so its their risk.
How can you model in greed - corruption - and the ever popular human trait of freaking out ?
Tech bubble - Real Estate bubble ... next time I even see/hear the word bubble in the markets I'm cashing out for a while
Its not the years, its the mileage
And I agree with that datas: The problem isn't the computer/mathematical models. It's how they were used. In particular, people were using models designed to evaluate one kind of mortgage asset, and plugging in an entirely different kind of mortgage, etc.
The author grants that conclusion, but then makes the claim that although the problem wasn't caused by the computers themselves, that it was somehow exasperated by them. - I don't see how that's the case.
Computers and computer modelling makes it easier to create advanced derivatives and such. But it doesn't make us do it. Just look at the engineering world; We don't choose technically advanced solution just because we can. In fact, the tendency is to go for the simplest possible solution. ("KISS rule")
There's only one reason why you would create advanced, incomprehensible derivative structures: To con people, essentially. To obfuscate the risks. To create money out of nothing. (the most profitable way to make it)
That's not a new problem. There's a reason we created financial regulations, why we have book-keeping, demand financial transparency, auditing, etc. This happened because it was allowed to happen. Because nobody stepped in and stopped this obfuscation from happening. I don't blame the computer models. If someone cons you into signing a bogus, misleading contract - the problem isn't with the paper it was written on or the language that was used. The problem is with the law allowing such contracts to have legal force (which is a regulatory problem from another century).
To extend that analogy, this is a bit like standing in that situation and asking whether or not written contracts are a bad thing, and whether we shouldn't go back to simpler, oral contracts. The bottom line is: As long as it's profitable, there will always be people trying to obfuscate and hide information for economic gain, and there will always be a need for regulation and oversight to stop people from doing that. But blaming the methods by which it's done is pointless.
I was actually pretty involved in automated trading systems until a few months ago. The over-arching problems with the systems is they can either be tactical or strategic. Tactical systems make trades in milli-seconds and make decisions based on a dozen or so parameters. There is no human intervention. The money is made getting your trades in faster than the other guy. The problem is there are a lot of reactionary traders out there who see this movement and then react... without really determining what caused the movement. They just see a large percentage of stock moving and follow the lead.
Strategic trading is data-mining and looking at hundreds of factors and incorporating expert opinion into and making decisions based on long term movements and not singular announcements.
A very good example is Enron. Tactical trading systems would have always bought it because it meet or exceed it's numbers. A through analysis such as the one done by Daniel Scotto would have seen through the fraud.
Unfortunately ... tactical trading is fast and sexy and attracts the Gordon Gecko/Boiler Room types. Very few college grads aspire to be Warren Buffet.
Don't worry, I'm sure Congress will audit the Federal Reserve and we'll get to the bottom of this mess!
The Federal Reserve recently refused to disclose $2 trillion in loans requested by a FOIA request citing "trade secret" clauses.
http://www.bloomberg.com/apps/news?pid=20601109&sid=aGvwttDayiiM
In response to Bloomberg's request, the Fed said the U.S. is facing "an unprecedented crisis" in which "loss in confidence in and between financial institutions can occur with lightning speed and devastating effects."
In other words, we'll tell you when we're ready to finally destroy the economy!
No wonder Congressman David Scott said we've "been bamboozled!"
The real number of the bailout is actually $8.5 trillion (as of two weeks ago and is probably closer to $10 trillion now.
http://www.sfgate.com/cgi-bin/object/article?f=/c/a/2008/11/26/MNVN14C8QR.DTL
If you have something that you dont want anyone to know, maybe you shouldnt be doing it in the first place -Eric Schmidt
There are two equally valid descriptions of markets. One is by Adam Smith, with the "unseen hand" guiding the markets. Smith markets are well behaved, efficient, and amenable to analysis by what amount to small-signal statistics.
The other description is by Charles Mackay in his book "Extraordinary Popular Delusions and the Madness of Crowds." In that book he describes the Dutch tulip craze and other bubbles in history prior to the mid 1800's. This economic crash is more of the same.
The models, probably because of "free market" ideology, assume a market where Adam Smith's "unseen hand" is at work. The modelers don't consider the kinds of markets described by Charles Mackay. Most of the models are based on the Black-Scholes option pricing theory. If you look at the assumptions underlying that theory, they describe good behavior, efficiency, and changes describable by what amount to small-signal statistics.
Mackay markets are boom and bust, with greed and lies and herd behavior all around. That's what we had. The underlying mathematics has been studied, but not for markets. If you have a pre-LCD TV, an electronic circuit that is non-statistical but related to boom-and-bust market behavior creates the sawtooth sweeps that paint the picture onto your screen.
Absolutely not.
The individual quantitative analysts ("quants") built redundancy into their individual company's systems by counting on external "randomness" (approximately), insuring against possible losses emanating from their highly leveraged transactions through insurance contracts (credit default swaps).
However, All the other quantitative models were built on essentially the same set of assumptions: That their insurers had sufficient capitalization to cover the CDS contracts. The triggering event, a loss in home valuations is particular markets, started an avalanche consisting of lots of finance companies invoking the CDS contracts, all at once. That's when they found out that the insurer (AIG, for example) was just as undercapitalized as everyone else. (There's way more to this sordid tale, so this is a necessarily compressed synopsis.)
Unless one counts "we got ours, you're fucked" as implying "working as advertised", then it didn't work by any stretch of the imagination.
Read Nassim Nicholas Taleb's comments on the Black Swan Event for a properly thought and documented analysis.
BTW, The Edge is a great resource for the intelligent and curious reader. I have no financial interest in these guys, but I've found their insights to be highly informative and balanced.
...and I don't think this is the first time financial modelling has been blamed for provoking or exacerbating a crash.
In 1987, it was a simple product called 'Synthetic Portfolio Insurance'. Sounds complicated? It isn't.
Basically, I have a portfolio of risky (stocks) and riskless (bonds) assets, and I want my portfolio to benefit from the greater upside performance of the risky asset, but at worst, I want my portfolio to perform no worse than the riskless. Everyday, the seller of the product rebalances the portfolio according to a set of rules.
So, when the stock market is good, most of my portfolio is in the stocks, and when it's bad, most of my portfolio is in the bonds. This is much like how you or I might behave if we were investing our own money.
However, this is assuming that the instruments don't influence the market. If the holding of the instruments is great enough, there is an unfortunate feedback loop. Should the market suddenly crash, the writers of the instruments are obliged to rebalance their portfolios (i.e., sell stock, buy bonds), which then causes further depression in stock prices, causing further rebalancing, and so on.
This brings me to a second point. True, quantitative modelling makes assumptions about how the market behaves. Good risk management should be taking reserves against the 'known unknowns' due to the model assumptions.
We know that crash events are inherently unpredictable, so we're supposed to be constantly checking the books to ensure that we know our worst-case exposures and that our hedges work.
On the other hand, we then calibrate these models against prices we see in the market.
It's my very strong feeling that the models weren't necessarily entirely terrible (although CDO, CDO^2 and CDO^3 does seem to be pushing it a bit), but that the market was also significantly underpricing risk, particularly credit risk (both default and counterparty default risk) and correlation between credit events, because of the benign market conditions we have had for so long.
So, some of the 'garbage-in' were the market observables used to calibrate the models.