[lbo-talk] Capitalism on Derivatives? (Was: Responsibilities)

Ted Winslow egwinslow at rogers.com
Sun Feb 28 10:06:35 PST 2010


Jordan Hayes wrote:


>> The crisis happened because the fundamentals of the securities
>> (the mortgage-backed securities) were defective.
>
> Of all the issues involved in this highly complex subject, I think I can state categorically that this one is incorrect. Mortgage-backed securities are not to blame in this, even in the slightest. MBS (and more generally CDO) I think are uncontroversially a net win for banks and consumers alike.

http://www.wired.com/techbiz/it/magazine/17-03/wp_quant?currentPage=all

“Using some relatively simple math—by Wall Street standards, anyway—[David] 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. … 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).”


> [David] Li's trajectory is typical of the quant era, which began in the mid-1980s. Academia could never compete with the enormous salaries that banks and hedge funds were offering. At the same time, legions of math and physics PhDs were required to create, price, and arbitrage Wall Street's ever more complex investment structures.
>
> In 2000, while working at JPMorgan Chase, Li published a paper in The Journal of Fixed Income titled "On Default Correlation: A Copula Function Approach." (In statistics, a copula is used to couple the behavior of two or more variables.) Using some relatively simple math—by Wall Street standards, anyway—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.
>
> If you're an investor, you have a choice these days: You can either lend directly to borrowers or sell investors credit default swaps, insurance against those same borrowers defaulting. Either way, you get a regular income stream—interest payments or insurance payments—and either way, if the borrower defaults, you lose a lot of money. The returns on both strategies are nearly identical, but because an unlimited number of credit default swaps can be sold against each borrower, the supply of swaps isn't constrained the way the supply of bonds is, so the CDS market managed to grow extremely rapidly. Though credit default swaps were relatively new when Li's paper came out, they soon became a bigger and more liquid market than the bonds on which they were based.
>
> 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. It's hard to build a historical model to predict Alice's or Britney's behavior, but anybody could see whether the price of credit default swaps on Britney tended to move in the same direction as that on Alice. If it did, then there was a strong correlation between Alice's and Britney's default risks, as priced by the 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).

http://www.ft.com/cms/s/2/912d85e8-2d75-11de-9eba-00144feabdc0.html

"CDOs built solely out of subprime mortgage debt became the rage. And using the magic of the Gaussian copula correlation model, and some clever off-balance-sheet architecture, high-risk mortgages were re-packaged into triple-A-rated investor gold. The CDO market exploded. In 2000, the total number of CDOs issued were worth somewhere in the tens of billions of dollars. By 2007, two trillion dollars of CDO bonds had been issued."


> By 2001, correlation was a big deal. A new fervour was gripping Wall Street – one almost as revolutionary as that which had struck when the Black-Scholes model brought about the explosion in stock options and derivatives in the early 1980s. This was structured finance, the culmination of two decades of quants on Wall Street. The basic idea was simple: that banks no longer had to hold on to risks. Instead they could value them, using complex maths and modelling, then package and trade them like any other, ordinary security.
>
> Mortgages were the prime example. Rather than make a mortgage loan and gradually collect interest over its lifespan, banks began to bundle the loans together and sell them into specially created off-balance-sheet shell companies. These companies in turn issued bonds to raise cash. And by using the modelling and maths being cranked out by quants, banks were able to tailor the structure of mortgage portfolios to ensure that bonds of varying risks could be issued to investors. The problem, however, was correlation. The one thing any off-balance-sheet securitisation could not properly capture was the interrelatedness of all the hundreds of thousands of different mortgage loans they owned. As a consequence, structured finance had remained a niche and highly bespoke practice throughout the 1990s.
>
> On August 10 2004, however, the rating agency Moody’s incorporated Li’s Gaussian copula default function formula into its rating methodology for collateralised debt obligations, the structured finance instruments that subsequently proved the nemesis of so many banks. Previously, Moody’s had insisted that CDOs meet a diversity score – that is, that each should contain different types of assets, such as commercial mortgages, student loans and credit card debts, as well as the popular subprime debt. This was standard investing good practice, where the best way to guard against risk is to avoid putting all your eggs in one basket. But Li’s formula meant Moody’s now had a model that enabled it to gauge the interrelatedness of risks – and that traditional good practice could be thrown out of the window, since risk could be measured with mathematical certainty. No need to spread your eggs across baskets if you knew the exact odds of your one basket being dropped. A week after Moody’s, the world’s other large rating agency, Standard & Poor’s, changed its methodology, too.
>
> CDOs built solely out of subprime mortgage debt became the rage. And using the magic of the Gaussian copula correlation model, and some clever off-balance-sheet architecture, high-risk mortgages were re-packaged into triple-A-rated investor gold. The CDO market exploded. In 2000, the total number of CDOs issued were worth somewhere in the tens of billions of dollars. By 2007, two trillion dollars of CDO bonds had been issued.

Ted



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