There is a great interview with an anonymous Hedge Fund manager in n+1 magazine. The interviewee is obviously a really smart person, and explains some of what just went on in the subprime commercial paper bubble and meltdown of the last while. There are a lot of great quotes here.
The problem is that the DNA of a lot of these [computerized statistical arbitrage] models is very, very similar, it’s like an ecosystem with no biodiversity because most of the people who do stat-arb can trace their lineage, their intellectual lineage, back to four or five guys who really started the whole black box trading discipline in the ’70s and ’80s. And what happened is, in August, a few of these funds that have big black box trading books suffered losses in other businesses and they decided to reduce risk, so they basically dialed down the black box system. So the black box system started unwinding its positions, and every black box is so similar that everybody was kind of long the same stocks and short the same stocks. So when one fund starts selling off its longs and buying back its shorts, that causes losses for the next black box and the people who run that black box say, “Oh gosh! I’m losing a lot more money than I thought I could. My risk model is no longer relevant; let me turn down my black box.” And basically what you had was an avalanche where everybody’s black box is being shut off, causing incredibly bizarre behavior in the market.
But we had a loss over the course of like three days that was like a ten-sigma event, meaning, you know, it should never happen based on the statistical models that underlie it. Why? Because the model doesn’t assume that everybody else is trading the same model as you are. So that’s sort of like a meta-model factor. The model doesn’t know that there are other black boxes out there.
Takeaway: The ridiculously unlikely may be more likely than you think. Especially when automated systems are involved.
The interview also explained what was at the heart of the problem: heavy demand for rated paper:
So what happened is this machine—let’s call it, it’s a big machine that wanted to gobble up, you know, rated paper—needed to be fed. So there were people who could make a lot of money feeding the machine, and they were like, you know, “We need to keep originating mortgages, and feeding them to the machine,” and if you have a robot bid, you tend to get a bubble. Someone is hungry for paper, paper will be created. And that’s almost never a good thing that lending decisions are being driven by the fact that many, many steps down the chain there’s just someone who wants to buy paper.
[H]ere was a guy who knows the market really, really well, who is a real expert in the nuts and bolts of mortgage lending, and really knew the collateral really well—but he was a true believer ... And there were other people at the firm, say, at the middle of last year, who were not mortgage experts, who were saying, you know, “I see the run-up in housing prices in some of these geographies, and I just don’t really get it. I go down to Florida and see the forest of cranes, and I just really wonder, who’s going to be in all those apartments? ... and I see these commercials on TV, you know, about low-doc, no-doc mortgages—and there is no way, there is no way that this is not going to end badly. And I see that these mortgages are being created by this massive demand for CDO paper, by this robotic bid, and this is the perfect example of a bubble—and we should be short, we should be short sub-prime paper." ... But he’s the expert, right? It’s a tough thing. If you have somebody who’s really trained in the mortgage business, he’s been in the mortgage business for fifteen years, in equilibrium he’ll do a great job. ... But in terms of detecting the paradigm shift, the guy who’s just buried in the forest... he’s not going to see the big picture, he’s not going to catch the paradigm shift.