Collective wisdom about the location of Ground Zero for the credit crisis seems to be coalescing around AIG’s Financial Products Unit (AIGFP), which basically invented the credit default swaps at the center of the whole mess. TPMmuckraker provides an excellent history of AIGFP: its inception, rise, and eventual downfall (taking AIG and the economy with it).
I want to focus on one small nugget from that history, under the heading “The Seed Of Ruin Is Planted”. It documents the very first credit default swap deal AIGFP made, in 1998…
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Collective wisdom about the location of Ground Zero for the credit crisis seems to be coalescing around AIG’s Financial Products Unit (AIGFP), which basically invented the credit default swaps at the center of the whole mess. TPMmuckraker provides an excellent history of AIGFP: its inception, rise, and eventual downfall (taking AIG and the economy with it).
I want to focus on one small nugget from that history, under the heading “The Seed Of Ruin Is Planted”. It documents the very first credit default swap deal AIGFP made, in 1998:
JP Morgan approached AIG, proposing that, for a fee, AIG insure JP Morgan’s complex corporate debt, in case of default. According to computer models devised by Gary Gorton, a Yale Business Professor and consultant to the unit, there was a 99.85 percent chance that AIGFP would never have to pay out on these deals. Essentially, this would happen only if the economy went into a full-blown depression.
(Emphasis mine.) I’d guess that 0.15% under-estimated the risk that AIG would have to pay out for these deals, possibly by a significant margin (but hey, that’s easy to claim that with the hindsight we now have). That 99.85% figure is almost certainly an estimate of probability given that the assumptions of the model are upheld. Now, I don’t know anything about the underlying model per se, but I’m willing to bet that the data used to estimate it didn’t go back at least 70 years, to cover the period of the last full-blown (aka Great) depression. Credit Default Swaps are complex instruments, and it’s likely that much of the data needed to build and estimate the model simply doesn’t exist with more than a 10-20 year history at best. So it may be fair to say that there’s a 0.15% chance of failure if a series of fairly unusual things happen, and by “unusual” I mean in the context of the last 20 years. But if a full-blown depression does occur, the model is no longer valid, because it’s never seen data relevant to a depression occurring. In that case, when it comes to estimates of risk and probability, all bets are off.
