Market Bubbles and Human Nature

Alan Greenspan seems to have discovered the irrationality of human nature. In his recent appearance on the Daily Show, he lamented the stubborn persistence of financial bubbles, from junk bonds to dot-com stocks to real estate. (For a thorough history of bubbles, from tulips to today, check out this book.) John Stewart confessed that Greenspan's gloomy view of human nature - we are all gullible fools - bummed the expletive out of him. (Greenspan, of course, could also be rationalizing away his own failure to deflate either the dot-com bubble or the real estate bubble.)

But why are bubbles so inevitable? Here are some explanations, all of them rooted in the quirks of human nature:

1. The Nature of Regret. I've written about this before, but it bears repeating. Whenever we make an investment, or receive some reward, our mind automatically figures out the difference between the return "that could have been" and the actual return. This counterfactual calculation - it's called a fictive learning signal - strongly influences our future decisions. The more we regret a decision, the more likely we are to do something different the next time around. In a simple neuroeconomic experiment, scientists showed that when the market was going up, the automatic counterfactuals of investors were persuading them to invest larger and larger amounts in the market. After all, if they'd made a certain amount of money by investing 50 percent of their portfolio in the market, imagine how much money the would have made if they'd invested everything?

Obviously, the ability to learn from counterfactuals is a crucial cognitive skill. It allows us to learn not just from experience, but from hypothetical scenarios. But I think this system goes bezerk during bubbles. The market keeps on going up, and so we are led to make larger and larger investments in the boom. (To not invest everything means that we are constantly regretting the gains we missed.)

2. Information Cascades. Imagine two restaurants that open next door to each other. The first hungry customer doesn't know which restaurant is better, so he flips a coin and hopes for the best. A little bit later, another customer arrives. He also doesn't know which restaurant is better, but he assumes that the restaurant with at least one customer must be better. When the third customer shows up, he sees two people in one restaurant and none in the other, so he also goes to the popular place. The cycle continues in this manner until most customers end up choosing the popular restaurant, even though the other restaurant might serve better food. This is irrational behavior, but it's wired into us. One of the ways we deal with an uncertain situation is to follow the lead of others. We find comfort in numbers.

Economists refer to this process as an "information cascade". Robert Shiller believes that this sort of herd behavior strongly affects the stock market. "The popular notion that the level of market prices is the outcome of a sort of vote by all investors about the true value of the market is just plain wrong," he writes. "Hardly anybody is really voting. Instead people are choosing not to, as they see it, waste their time and effort in exercising their judgment about the market." When people can't decide for themselves, they usually let others decide for them. Unfortunately, information cascades lead to speculative bubbles (and very crowded restaurants), and bubbles always burst.

3. Streak Detection. Could I really write an article about bubbles without talking about dopamine? No way. To put it bluntly, our dopamine neurons are pattern detectors. They sift through the helter-skelter of stimuli and look for causation and correlation. This, of course, is a crucial cognitive tool, except when it goes haywire. The stock market is a classic example of a "random walk," since the past movement of any particular stock cannot be used to predict its future movement. (As the economist Burton Malkiel famously remarked, "a blindfolded chimp throwing darts at the Wall Street Journal" has a 50 percent chance of beating the market in any given year.) The danger of equities, however, is that they sometimes trick our dopamine neurons into believing that the erratic fluctuations of the market are predictable. Bubbles form when people are convinced that they've found some profound underlying trend that defies the randomness of the market. It's not speculation, it's a sure thing.

4. The Suspension of Loss Aversion. Our irrational sensitivity to losses is generally regarded as a bad thing. But it's essential to understand our bias against losses in the context of reality. Look, for example, at a speculative bubble, which is essentially a popular delusion of optimism. Everybody is suddenly convinced that they are going to get rich. While this behavior might seem ridiculous in retrospect, it can also be viewed as perfectly logical. These tech stocks or Florida real estate had always appreciated in the past. Why should the future be any different? Alas, the future is always different. This is why we naturally worry about risky gambles. We know that we don't know what will happen. While most economists think loss aversion is a silly and irrational habit, it also prevents us (in normal circumstances) from sinking our savings into dubious investments. Without a little loss aversion, more of us would lose everything.

Can you think of any other human foibles that make bubbles so irresistible?


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By Tegumai Bopsul… (not verified) on 21 Sep 2007 #permalink

So an information cascade is the other side of the wisdom of crowds?

If so, then it all depends of the average skill of the crowd, right? If the crowd is predominantly skilled at making the given judgment, the consensus view is more likely to be correct, whereas when the crowd is predominantly less skilled(like the stock market), the probability of be consensus view being correct is simply equal to the likelihood of the cascade initiator being correct. For a large enough crowd, the correctness likelihood would depend of the degree to which it is possible to be skilled.

That implies that the worst a consensus view can be is 50% likely to be incorrect, but I guess as time goes on, the chance of the correct view becoming different from the initial view approaches 100%, and inertia would bias the consensus towards less than 50% likelihood of being correct.

That in itself is interesting, because I would expect inertia to be more of an issue in cases where it is possible to be skilled, so the critical parameter affecting consensus correctness likelihood would then be the speed at which the correct position changes.

All of this goes to suggest that if you could take the consensus position, and apply a little conservative skilled interpretation to it, you can hover just over 50% correct consistently.