Good Bubble, Bad Bubble

In the future, historians will stop using the word “bubble,” because it refers to two opposite phenomena:

• In an equity bubble, investors have limitless optimism about the future. They expect many of the companies they invest in to fail, but believe that the 95th- or 99th-percentile performers will more than make up for this.

• In a credit bubble, investors have limitless faith in the status quo. They expect volatility to decrease, and they believe they can estimate returns with increasing accuracy. If they want higher returns, they know they can use leverage—but for the most part, investors celebrate the middle of the bell curve, and expect the tails to cancel each other out.

The only thing these bubbles have in common is that they involve collectively bad decisions with money. The kinds of decisions are vastly different, and the consequences are, too.

Equity Bubbles Considered Not-So-Harmful

In an equity bubble, resources get distributed towards whatever investment is the most levered to optimistic outcomes. These don’t have to be the same outcomes—AOL’s walled-garden got a high valuation at the same time that Yahoo’s anything-goes approach did, for example.

Because of this, they attract capital (and talented people) to anything sufficiently unusual that fits into the bubble narrative. This entails lots of investments in bad ideas ( and lots of investments in necessary ideas (online brokerages, which automated the most automatable part of investing).

It’s a huge subsidy for creative destruction, with an emphasis on the creativity. Unlike the usual economic process of local optimization (making a factory marginally more efficient, reducing inventories a little bit at a time, finding a new customers), it represents a massive change in the process (creating a completely new sales channel, revamping the entire inventory management process, creating a financing model that’s based on venture funding plus a negative cash cycle).

There’s a lot of malinvestment during these bubbles, but they also lead to lasting companies. They also create new infrastructure (bad telecom investments in the 90’s made Myspace and Youtube possible in the 00’s). And they help illustrate the ineffectiveness of older companies, though it’s often not until the bust that these companies go under.

Of all of the ways that the market can overshoot itself, equity bubbles appear to be the most beneficial. In the short term, they subsidize creativity; in the long term, they subsidize creativity tempered by sanity. And if “creativity tempered by sanity” doesn’t describe the best parts of the world economy since the industrial revolution, I don’t know what does.

Credit Bubbles: Doubling Down on the Status Quo

Credit bubbles are toxic. They rely on ignoring possibilities, rather than embracing them. They allocate human capital away from analyzing uncertainty, and towards creating artificial certainty. Credit bubbles are more self-perpetuating than other kinds of bubbles, and they leave behind an inflexible economy.

A credit bubble is a bet on the continuation of the status quo. Since lenders have limited upside and lots of downside, they don’t have any reason to care about best-case scenarios; instead, they look at average scenarios. That requires historical data, which can best be obtained from older and more static industries.

The most pernicious effect of credit bubbles is that they tend to be self-perpetuating. In the 00’s, the dominant investment thesis might be summed up as follows:

• Our economy is stable, financial markets are liquid, and information is freely available, so volatility should gradually decrease.
• This liquidity and information also means we won’t have huge economic dislocations; future change will be gradual.
• We can use historical data to model prices, and our models keep improving.
• Thus, the way to make money is to buy what you can most effectively model, treat it as an asset class rather than a claim on specific cash flows, and lever as much as your volatility permits—after all, you have historical data on exactly how markets will behave under any circumstances.

This results in smooth returns with low (and declining) volatility for people who buy into the thesis. And if they’re competing with other investors for funds, that means more money gets allocated to investors who buy into the bubble thesis—pushing prices further in the same direction.

All else being equal, skeptics get priced out. During the mortgage bubble, the skeptics who profited the most were the ones for whom all else was not equal—value investors who got into real estate as a sideline (like Michael Burry and John Paulson), or unusually talented traders who subsidized their negative bets with their market-making profits (like Greg Lippmann).

Meanwhile, the bubble believers see their ideas constantly confirmed. Everyone’s returns are in line with predictions—unlike equity bubbles, there aren’t any sudden gains. In a credit bubble, it’s possible to do what Bear Stearns’ internal hedge funds did, and show consistent returns of about 1% per month with no down months.

All this means more resources allocated towards precision, rather than accuracy: if prices converge on what the model says they should be, a more refined model will create more incremental profits than a different understanding of what’s being modeled. Over time, this simplification leaves room for the underlying assets to change: the capital for mortgages from 2006 was allocated based on the returns from years beforehand, which made that capital less sensitive to declining credit standards.

In the terminal phases of a credit bubble, investors are precisely wrong—whatever they’re most bullish on and most certain about is bound to be the asset declining in quality the fastest, and the one whose future pricing is thus the least predictable.

What to Do About a (Bad) Bubble

Investors in the 90’s were overconfident about the power of technology to change their lives in the near term. They were also overconfident about the power of financial models to predict sovereign debt prices and equity volatility—in the latter case, the collapse of LTCM scared them straight, while the Fed’s subsequent liquidity injections kept that collapse from flattening the broader economy.

This illustrates the fundamental problem: given enough liqudity, good and bad bubbles can last indefinitely. And identifying them can be tricky: a large component of the “tech” bubble was the “IT bubble”&madsh;a huge increase in the demand for people with otherwise obsolete skills, who could update systems ahead of Y2K.

You can ask yourself a simple question: “Is what these people are throwing money at, fundamentally, boring?” If it is, buy puts: you know they’ll be cheap.

If you’re a money manager, you’re out of luck: the more effectively you short the bubble, the worse your returns will look. And since credit bubbles appear quite conservative (they are, after all, based entirely on historical precedent), you’ll look bad and imprudent. Worst of all, if you bet on the bubble as a manager and short it (or even deride it) as a private investor, you’ll probably end up in court.

So your best bet is to quit your job and start a blog or something. (Then, buy puts.)

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| May 1st, 2010 | Posted in economics |

One Response to “Good Bubble, Bad Bubble”

  1. Higher Education: The Next Big, Bad Bubble | Byrne's Blog Says:

    […] is a bubble like any other bad bubble (i.e. a credit bubble). It ultimately rests on the twin mistakes of extrapolating based on bad data, and assuming that […]

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