Between these two deals, the differences in risk profiles were huge. But Moody's declared the upward range of estimated loss on the MASTR collateral to be 4.4%, while the upward range on the SASCO collateral was 4.5%. Again, there are hundreds of examples that show how the risk variables within a mortgage pool had almost no impact on the eventual ratings or capital structure.
Ignoring Signs of Fraud, or Garbage-In/Garbage-Out Analyses
The MASTR deal illustrates how the subprime industry invited fraud. You cannot model fraud, because it never occurs in a random predictable manner, though it's a safe bet that dishonest people take the path of least resistance. The rating agencies' attitude toward fraud was the same as it was toward second liens: We don't know what we don't know, so let's assume there's no problem. Except it was impossible to follow the real estate industry and not know that it was a major problem. The epidemic of fraud in the subprime industry was highlighted in major reports published jointly by The New York Times and 20/20, by HUD and Treasury, and by The Los Angeles Times. And based on the data likely to have been corrupted by fraud, consider how the rating agencies presumed to slice risk in the MASTR and SASCO deals as finely as cheese at a deli counter.
Glossing Over Prepayment Risk
If you look at the capital structures of enough subprime deals, you'll soon notice that the unrated, or equity, tranche is almost always smaller than the expected loss. The difference would be made up with interest income earned over the life of the deal. But calculating the net present value of that interest income is a very dicey proposition. By definition, it's a matter of counting your chickens before they hatch.
With any credit portfolio, the only cash offsetting the credit losses from nonperforming loans is the interest income from the performing loans. And in a mortgage securitization, the total interest income is driven by the rate of prepayment, which is never according to a fixed schedule. Only a tiny minority of homeowners repay their loans over 30 years. Almost all of them prepay when they refinance, when they sell their homes, or when they allow the property to be liquidated in a foreclosure sale. If the loans in a mortgage securitization prepay much faster than originally projected, any shortfall in interest income is lost forever. Again, these deals aren't like banks, which can book new loans to offset the loans that roll off.
Different investors in the same mortgage securitization have a different sensitivity to prepayment risk, since there's a predetermined sequence of which investors get repaid first and which get repaid last. This sequence of repayment is called the cash-flow waterfall. The tranches that are hypersensitive to prepayment risk are near the bottom, like those rated triple-B. But they don't recover principal out of interest income; they get repaid out of excess spread, which is something else altogether. The way the waterfall invariably works, the subordinate tranches do not receive a nickel of principal until after all of the tranches are fully paid on their interest coupon, and after all of the senior tranches are fully repaid on their principal. Whatever is left over is used to cover the credit losses, which are first absorbed by the lowest rated tranches. So a faster-than-expected prepayment rate means that excess spread can be wiped out in a heartbeat.
Another credit truism is that, with any hyperleveraged investment, if some unexpected happens, an investor can get wiped out quickly. That's what happened in 1999 and 2000, when ratings agencies learned that their subprime models simply didn't work. A drop in interest rates in 1998 triggered faster-than-expected prepayments on subprime mortgages, and the investors in the most subordinate tranches, which happened to be mortgage lenders, lost their shirts and went out of business. The leader in the subprime industry in the late 1990s was Contifinancial, which issued 12 tranched securitizations, totaling $14 billion, during 1997, 1998 and 1999. Investment grade tranches on all but one of those deals defaulted during the height of the real estate boom, largely because of faster than expected prepayments. Anyone at the agencies who says that the losses on subprime bonds were unforeseeable is feigning amnesia
Collateralized Debt Obligations: The False Equivalency Between Corporate and Structured Defaults
The scam behind CDOs is simple, or definitional. It's based on the superficial similarity between CDOs and CBOs or CLOs. Before getting lost in the alphabet soup, let's clarify the definitions:
CBOs, aka collateralized bond obligations are comprised of corporate bonds;
CLOs, aka collateralized loan obligations, are comprised of corporate loans; and
CDOs, aka collateralized debt obligations, are, in this context, comprised of investments in structured finance entities, most notably residential mortgage bond securitizations.
All three entities are investment portfolios of debt instruments tailored around rating agency claims that they can measure the diversification of credit risk. More specifically, the agencies profess to be able to measure default correlations, the likelihood that, if one bond defaults, a second bond will also default. CDOs are also based on a false equivalency, the notion that a triple-B is a triple-B is a triple-B, that statistically, the risk of default in all triple-B debt obligations increases at the same rate over time . In this alternate universe, the rating defines the reality.
The difference between a corporate bond default and a structured finance default is like the difference between a very sophisticated human being and a very stupid machine. An investment grade corporation is actively managed people who are constantly responding to an ever-changing business environment. A structured deal is supposed to operate like a dumb machine; it never restructures its balance sheet, or spins off nonstrategic assets, or increases the budget for new product development.
Investment grade companies have professional people whose overriding goal is to forestall a payment default, which triggers a fairly predictable and rapid chain reaction of events. Once it becomes apparent that a company is insolvent:
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