Why do "bubbles" occur in the financial markets?

Virginia Postrel, writing for the Atlantic magazine, discusses experiments some economists have been running that seek to provide insight into the behaviour of financial markets.

The basic idea is simple. You offer the subjects investments which provide 15 regular dividends of $0.24 during the course of the experiment (alternatively you offer a range of possible payments that average $0.24). The subjects then trade those investments with each other. There are 60 rounds of trading, with dividends paid every fourth round.

In theory, no one should pay more than the expected value of the investment at each round of trading, namely the amount of money that is still left on that dividend. At the start, this is $3.60. After the first payment, it falls to $3.36 and so on. This is not what happens. Postrel writes:

Here, finally, is a security with security—no doubt about its true value, no hidden risks, no crazy ups and downs, no bubbles and panics. The trading price should stick close to the expected value.

At least that’s what economists would have thought before Vernon Smith, who won a 2002 Nobel Prize for developing experimental economics, first ran the test in the mid-1980s. But that’s not what happens. Again and again, in experiment after experiment, the trading price runs up way above fundamental value. Then, as the 15th round nears, it crashes. The problem doesn’t seem to be that participants are bored and fooling around. The difference between a good trading performance and a bad one is about $80 for a three-hour session, enough to motivate cash-strapped students to do their best. Besides, Noussair emphasizes, “you don’t just get random noise. You get bubbles and crashes.” Ninety percent of the time.

So much for security.

Why should this be? Postrel suggests:

Experimental bubbles are particularly surprising because in laboratory markets that mimic the production of goods and services, prices rise and fall as economic theory predicts, reaching a neat equilibrium where supply meets demand. But like real-world purchasers of haircuts or refrigerators, buyers in those markets need to know only how much they themselves value the good. If the price is less than the value to you, you buy. If not, you don’t, and vice versa for sellers.

Financial assets, whether in the lab or the real world, are trickier to judge: Can I flip this security to a buyer who will pay more than I think it’s worth?

Why can’t I do the same thing with non-financial goods and services?

My suggestion is as follows. Obviously, for some cases, it is simply not possible (I cannot sell my haircut onto someone else!). In most cases people will buy something in order to use it (rather than to sell it on) and what they will pay for a good limits what anyone else will pay for the good in order to sell it on. In markets where people regularly sell things second hand (books, computers, cars, etc) they do not expect to get the price they got for the new product.

In these cases a used product has less value than an unused product – it may be less shiny, it may have developed some faults, and its lifetime will be shorter than for a new product. The same cannot be said of financial products such as shares or futures. The fact that someone owned a share before I did does not, by itself, devalue the share.

Postrel continues:

In an experimental market, where the value of the security is clearly specified, “worth” shouldn’t vary with taste, cash needs, or risk calculations. Based on future dividends, you know for sure that the security’s current value is, say, $3.12. But—here’s the wrinkle—you don’t know that I’m as savvy as you are. Maybe I’m confused. Even if I’m not, you don’t know whether I know that you know it’s worth $3.12. Besides, as long as a clueless greater fool who might pay $3.50 is out there, we smart people may decide to pay $3.25 in the hope of making a profit. It doesn’t matter that we know the security is worth $3.12. For the price to track the fundamental value, says Noussair, “everybody has to know that everybody knows that everybody is rational.” That’s rarely the case. Rather, “if you put people in asset markets, the first thing they do is not try to figure out the fundamental value. They try to buy low and sell high.” That speculation creates a bubble.

Thus bubbles seem to be an inherent feature of financial markets. Those who profit most buy early and sell midway through the bubble:

In fact, the people who make the most money in these experiments aren’t the ones who stick to fundamentals. They’re the speculators who buy a lot at the beginning and sell midway through, taking advantage of “momentum traders” who jump in when the market is going up, don’t sell until it’s going down, and wind up with the least money at the end. (“I have a lot of relatives and friends who are momentum traders,” comments Noussair.) Bubbles start to pop when the momentum traders run out of money and can no longer push prices up.

Does this mean that no one is to blame for the “credit crunch”?

Well there’s more to this story. After a few repeats of the experiment with the same subjects, you no longer get bubbles. This is not because the participants learn the true value of the dividends though:

But work that Noussair and his co-authors published in the December 2007 American Economic Review suggests that traders don’t reason that way.

In this version of the experiment, participants took part in the 15-round market four times in a row. Before each session, the researchers asked the traders what they thought would happen to prices. The first time, participants didn’t expect a bubble, but in later markets they did. With each successive session, however, they predicted that the bubble would peak later and reach a higher price than it actually did. Expecting the future to look like the past, they traded accordingly, selling earlier and at lower prices than in the previous session, hoping to realize a profit before the bubble burst. Those trades, of course, changed the market pattern. Prices were lower, and they peaked closer to the beginning of the session. By the fourth round, the price stuck close to the security’s fundamental value—not because traders were going for the rational price but because they were trying to avoid getting caught in a bubble.

“Prices converge toward fundamentals ahead of beliefs,” the economists conclude. Traders literally learn from experience, basing their expectations and behavior not on logical inference but on what has happened in the past. After enough rounds, markets work their way toward a stable price.

There is a twist here. The traders end up with behaviour that is optimal for a given environment. Change this environment and their experience may no longer apply. Indeed further experiments confirmed this:

In research published in the June 2008 American Economic Review, Vernon Smith and his collaborators first ran the standard experiment, putting groups through the 15-round market twice. Then the researchers changed three conditions: they mixed up the groups, so participants weren’t trading with familiar faces; they increased the range of possible dividends, replacing four possible outcomes (0, 8, 28, or 60) averaging 24, with five (0, 1, 8, 28, 98) averaging 27; finally, they doubled the amount of cash and halved the number of shares in the market. The participants then completed a third round. These changes were based on previous research showing that more cash and bigger dividend spreads exacerbate bubbles.

Sure enough, under the new conditions, the experienced traders generated a bubble just as big as if they’d never been in the lab. It didn’t last quite as long, however, or involve as much volume. “Participants seem to be tacitly aware that there will be a crash,” the economists write, “and consequently exit from the market (sell) earlier, causing the crash to start earlier.” Even so, the price peaks far above the fundamental value. “Bubbles,” the economists conclude, “are the funny and unpredictable phenomena that happen on the way to the ‘rational’ predicted equilibrium if the environment is held constant long enough.”

One can draw various implications from this. Postrel mentions two:

  • That people should beware markets where lots of cash chases a few good deals. Presumably she has in mind the research showing that increasing the amount of cash increaases the risk of a bubble occurring.
  • That big changes in the financial markets can cause bubbles even with experienced traders since their knowledge is no longer valid.

I’d add that it follows that if state intervention in financial markets causes an increase in the amount cash in those markets, it risks generating a bubble. There is also an increased risk if state interventions (or anything else) nullify the experience the traders in those markets have, or if such interventions encourage large numbers of inexperienced people to enter the markets.

Both Postrel and Charles R. Morris, author of The Trillion Dollar meltdown, point out that the cutting of interest rates by the Federal Reserve frees up more cash to buy financial instruments. Morris blames Greenspan for cutting interest rates and keeping them low during the 2000s, thus causing a flood of cash into the financial markets. The findings reported in Postrel’s article suggest he might have a point.

However interest rate changes are only part of the story. There are other forms of state intervention in the market and there were other factors feeding into the bubble (e.g. trading in new, complex financial instruments came to dominate the markets for example, as Morris shows). I hope to cover these other aspects in later posts.

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