Beliefs, Not Companies, are “Too Big to Fail”

What makes a company “too big to fail”? The traditional answer is “size”: if a company as big as Bear Stearns or AIG suddenly needs to liquidate, the market will miss their unique role in clearing transactions or making a market. Then, as they dump their extra-special assets, it will cause widespread panic and needless disruption.

I believe that this is entirely wrong. A company becomes too big to fail when it’s a leveraged bet on a universally agreed-upon belief that happens to be false.

In the mid-2000’s could look at the data on housing and find reasons to be optimistic: house prices always went up year-over-year, housing was a tax-advantaged investment, there was an explicit government policy in favor of raising home ownership, and an increasingly liquid market for mortgage-backed financial products meant that it would always be easy to borrow.

These reasons, of course, were also the reasons that the housing market collapsed. It was easy to make inductive judgments based on the immediate past, without reaching to make the deductive judgment that circumstances had changed, largely due to an overreliance on their staying the same. (You can never have a true bubble until the bubble itself is part of the story: you had to buy Internet stocks, because they were going up so fast; a house was a safe investment, because housing prices had never seriously dropped.)

Back to Bear and AIG: both companies were, among other things, highly leveraged bets on that same real estate status quo. Letting them unwind would mean further damaging the housing investment thesis, which itself would lead to further failures, more doubts about the future of housing, etc.

It’s a major distinction: the current doctrine is that a company is too big to fail if it will make prices lower than they should be; in practice, a company is too big to fail if its failure means that prices will get closer to where they should be—and we’ll get closer to rethinking the way we’ve been pricing things in general.

This is a little more clear when looking at an asset class that started having trouble at the same time that subprime mortgages did: equity statistical arbitrage. The basic idea behind stat arb was that you could determine the expected correlations between different stocks, and bet that anomalies would revert. So if steel stocks are up 1% today, and one steel stock is up .5%, it’s a buy. Multiply the process many thousands of times over, and add a whole lot more complexity, and you have a highly profitable strategy—but it’s a strategy contingent on the idea that past trades and current trades provide information about future prices beyond the profits captured by those traders. (If someone buys a stock, and it rises, the information that they bought may indicate that it should rise—but does that information indicate it should rise past the point at which they bought it?)

There wasn’t a single stat arb firm. But, as it turned out, they were all using roughly the same strategies. When some firms started selling what they’d been buying and buying what they’d been selling, it signaled to the other firms that they should do the same, leading to the classic rush for the exits that characterizes a panic.

Many hundreds of billions of dollars had been invested in variants on this strategy. No one company dominated the market. No one failure would have made a difference. But the market dislocation did lead to a collective realization: that when everyone ran the same statistical tests over the same data, returns would be good whether or not there was any validity to the results, simply because they’d all make the same trades and push prices in the same direction. The funds that didn’t go under have a much healthier attitude, now.

As more assets get ‘financialized’, it’s a lot easier to construct a temporarily profitable consensus. In fact, as more assets get marked-to-market, it becomes easier to temporarily lose money by being right. The credit default swap is, among other things, a way to guarantee that you’ll lose money and everyone will think you’re wrong, continuously, until you end up right. Or bankrupt.

Fortunately, this financialization offers a solution to the restated too-big-to-fail program. You can find a way to bet on anything, whether it’s overpopulation, demographic decline, peak oil, the Singularity, China as the next superpower, China as the next Japan, etc. It’s easier than ever to articulate a divergent opinion by making the appropriate bet.

This gives you a very simple obligation: you need to seriously consider at least a few things that society holds sacred, and start actively disbelieving in them (and investing like you do). It’s probably safest to take a belief that could get you excluded from polite company, and look for less harmful beliefs that correlate with it. (People on the extreme left and extreme right were talking about the real estate bubble long before it popped.)

It’s your civic duty: do your part to make sure mainstream beliefs aren’t Too Big to Fail.

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| April 4th, 2010 | Posted in economics |

3 Responses to “Beliefs, Not Companies, are “Too Big to Fail””

  1. hga Says:

    Hmmm, any discussion of “too big to fail” that ignores counterparty risk (at least in my quick read of the above) strikes me as somewhat lacking.

  2. byrneseyeview Says:

    Counterparty risk is a problem if it causes prices to be irrationally low.
    But if prices are too high, it's just another mechanism for introducing
    corrective effects.

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