As you may know, credit default swaps are largely responsible for the financial crisis.
Yesterday, Wired wrote an article explaining how CDS actually formed the very heart of the risk model used by the big banks and investment houses, ratings agencies, bondholders, and just about everyone else in the financial world. That model was fundamentally flawed, and so the financial house of cards built upon it has come crashing down.
Here are excerpts providing the basics of the article (the article is worth reading in full):
[David] Li’s formula, known as a Gaussian copula function … was adopted by everybody from bond investors and Wall Street banks to ratings agencies and regulators. And it became so deeply entrenched—and was making people so much money—that warnings about its limitations were largely ignored.***
In 2000, while working at JPMorgan Chase, Li … came up with an ingenious way to model default correlation without even looking at historical default data. Instead, he used market data about the prices of instruments known as credit default swaps.***
When the price of a credit default swap goes up, that indicates that default risk has risen. Li’s breakthrough was that instead of waiting to assemble enough historical data about actual defaults, which are rare in the real world, he used historical prices from the CDS market…. Li wrote a model that used price rather than real-world default data as a shortcut (making an implicit assumption that financial markets in general, and CDS markets in particular, can price default risk correctly).***
The effect on the securitization market was electric. Armed with Li’s formula, Wall Street’s quants [i.e. math wizards] saw a new world of possibilities. And the first thing they did was start creating a huge number of brand-new triple-A securities. Using Li’s copula approach meant that ratings agencies like Moody’s—or anybody wanting to model the risk of a tranche—no longer needed to puzzle over the underlying securities. All they needed was that correlation number, and out would come a rating telling them how safe or risky the tranche was.
As a result, just about anything could be bundled and turned into a triple-A bond—corporate bonds, bank loans, mortgage-backed securities, whatever you liked. The consequent pools were often known as collateralized debt obligations, or CDOs. You could tranche that pool and create a triple-A security even if none of the components were themselves triple-A. You could even take lower-rated tranches of other CDOs, put them in a pool, and tranche them—an instrument known as a CDO-squared, which at that point was so far removed from any actual underlying bond or loan or mortgage that no one really had a clue what it included. But it didn’t matter. All you needed was Li’s copula function.
The CDS and CDO markets grew together, feeding on each other. At the end of 2001, there was $920 billion in credit default swaps outstanding. By the end of 2007, that number had skyrocketed to more than $62 trillion. The CDO market, which stood at $275 billion in 2000, grew to $4.7 trillion by 2006.
At the heart of it all was Li’s formula. When you talk to market participants, they use words like beautiful, simple, and, most commonly, tractable. It could be applied anywhere, for anything, and was quickly adopted not only by banks packaging new bonds but also by traders and hedge funds dreaming up complex trades between those bonds.
“The corporate CDO world relied almost exclusively on this copula-based correlation model,” says Darrell Duffie, a Stanford University finance professor who served on Moody’s Academic Advisory Research Committee. The Gaussian copula soon became such a universally accepted part of the world’s financial vocabulary that brokers started quoting prices for bond tranches based on their correlations. “Correlation trading has spread through the psyche of the financial markets like a highly infectious thought virus,” wrote derivatives guru Janet Tavakoli in 2006.***
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 article makes it clear that people warned against the use of Li’s CDS-based formula, but – due to greed and stupidity – the warnings went unheeded.