Risk management’s perpetual-motion machine: Part 3, the epidemic
[Continued from last week's Part 2 and Part 1.]
Thus far in our story, via a terrific Wired Magazine article, mathematician David X. Li had introduced to the all-too-credulous world a risk management formula predicated on the beguiling notion that what the implied historical correlation among a class of risks – say, the correlation between Alice defaulting on her loan and Britney defaulting on hers – that correlation was enduring and invariant despite changing economic climates.
Don’t worry, Merlin, correlation is constant
As reader Matthew Healy, who sent me the link to this article, observed in his email:
In a previous life as an engineer I learned to dread what in engineering is known as a “common-mode failure” where the failure of one component in a system is so drastic that it takes out other components that you had thought were unrelated. Common-mode failures blow reliability calculations into shreds, and are behind most spectacular technological disasters.
I’m familiar with common-mode failures. In the early 1980s, my then-company (Boston Financial) decided that, to compete for the good properties to be syndicated, we needed to create a predevelopment fund whereby we lent money to developers in exchange for the right to syndicate the equity at a pre-negotiated price. The first eleven or twelve loans we did worked like a charm.
Li’s copula function was used to price hundreds of billions of dollars’ worth of CDOs filled with mortgages. And because the copula function used CDS prices to calculate correlation, it was forced to confine itself to looking at the period of time when those credit default swaps had been in existence: less than a decade, a period when house prices soared.
The last loan we did wiped out our whole fund. Healy again:
This global repricing of risk is the mother of all common-mode market failures.
Back to Wired:
Naturally, default correlations were very low in those years. But when the mortgage boom ended abruptly and home values started falling across the country, correlations soared.
Worked great until the end
“Everyone was pinning their hopes on house prices continuing to rise,” says Kai Gilkes of the credit research firm CreditSights, who spent 10 years working at ratings agencies. “When they stopped rising, pretty much everyone was caught on the wrong side, because the sensitivity to house prices was huge. And there was just no getting around it. Why didn’t rating agencies build in some cushion for this sensitivity to a house-price-depreciation scenario? Because if they had, they would have never rated a single mortgage-backed CDO.”
The rating agencies’ will to believe – and the enormous profits that belief brought them – overcame their judgment.
Bankers should have noted that very small changes in their underlying assumptions could result in very large changes in the correlation number. They also should have noticed that the results they were seeing were much less volatile than they should have been—which implied that the risk was being moved elsewhere. Where had the risk gone?
Risk? What risk?
They didn’t know, or didn’t ask.
What you don’t know lets you keep making money on other people’s risks
No one knew all of this better than David X. Li: “Very few people understand the essence of the model,” he told The Wall Street Journal way back in fall 2005.
“Li can’t be blamed,” says Gilkes of CreditSights.
If not Dr. Li, then who?
After all, he just invented the model. Instead, we should blame the bankers who misinterpreted it. And even then, the 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.
If Dr. Li isn’t to blame, then who is? Follow the money.
Nassim Nicholas Taleb, hedge fund manager and author of The Black Swan, is particularly harsh when it comes to the copula. “People got very excited about the Gaussian copula because of its mathematical elegance, but the thing never worked,” he says. “Co-association between securities is not measurable using correlation,” because past history can never prepare you for that one day when everything goes south. “Anything that relies on correlation is charlatanism.”
I rely on the correlation between my treatments and your wallet
All was well until the market topped and cracked in 2007 and 2008:
Cracks started appearing early on, when financial markets began behaving in ways that users of Li’s formula hadn’t expected.
By then it was partly too late – trillions of dollars of risk had been written, and could not be unwritten.
The moving finger writes down your assets,
and having written them down, moves on
The cracks became full-fledged canyons in 2008—when ruptures in the financial system’s foundation swallowed up trillions of dollars and put the survival of the global banking system in serious peril.
The rest we all know.
Li has been notably absent from the current debate over the causes of the crash. In fact, he is no longer even in the
Can you blame him?
Or dollars …
– and said he couldn’t talk without permission from the PR department. In response to a subsequent request, CICC’s press office sent an email saying that Li was no longer doing the kind of work he did in his previous job and, therefore, would not be speaking to the media.
In the world of finance, too many quants see only the numbers before them and forget about the concrete reality the figures are supposed to represent. They think they can model just a few years’ worth of data and come up with probabilities for things that may happen only once every 10,000 years. Then people invest on the basis of those probabilities, without stopping to wonder whether the numbers make any sense at all.
For nearly a decade, we all benefited from the magnificent illusion, and we’re all paying for the magnificent illusion.
Nash was not in equilibrium … and neither were we
As Li himself said of his own model: “The most dangerous part is when people believe everything coming out of it.”
There’s no fountain of youth; there’s no perpetual-motion machine; and there’s no way of making money without taking risk.
“Small print equals large risk.” Ferengi Rule of Acquisition 8
“Satisfaction is not guaranteed.”
[Hat tip: Matthew Healy.]
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