There was a telling moment yesterday on the NYTimes.com website. It was just after 10:30 in the morning and the top of the site featured a breaking news article about the S&P 500 heading into higher territory. The article offered the usual litany of explanations, from better than expected news on housing starts to a surprising uptick in retail sales. But here’s the catch: by the time I glanced at the article it was already obsolete, with the Dow and S&P down by a significant amount. A few hours later, a new article made its way to the top of the NYTimes site, explaining why the market was now in negative territory. (It had something to do with spiking oil prices and investors “waiting to see tangible evidence of economic recovery.”)
Similar stories appear on every single news site (and fill 12 hours of airtime on CNBC), as reporters and talking heads deftly try to explain the erratic movements of Wall Street. I think such explanations are especially popular in times of rampant uncertainty, which is where we are now. After all, if we understand the movement of the financial markets then we have a modicum of control – we know when to buy and sell – and people love control. In one classic 1975 study led by Ellen Langer, male undergrads at Yale were asked to predict the results of coin tosses, a cliched example of a random event. Nevertheless, a significant number of the men believed that their performance improved through practice – they got better at calling heads or tails – and that distraction would detract from their performance. How did they justify this wishful thinking? As Langer notes, the men engaged in some sly cognitive filtering and consistently “overremembered past successes”.
Is Wall Street any different? The market, after all, is a classic example of a “random walk,” since the past movement of any particular stock cannot be used to predict its future movement. Given this inherent stochasticity, it’s silly to attempt to explain the daily movement of the market: such an endeavor is like analyzing a series of flipped coins, or trying to explain the payout patterns of a slot machine. We can construct theories – and some of these theories might even sound intelligent – but they’re ultimately futile attempts to stave off the flux.
What’s even more disturbing is that such errant explanations might actually cost us money, since they lead, inevitably, to over-confidence. (Those Yale undergrads vastly overestimated their ability to predict coin flips.) We become so convinced that the logical-sounding explanations are true that we forget we’re dealing with a random, inherently unpredictable system. The end result is too much trading. Consider this experiment, which I describe in How We Decide:
In the late 1980′s, the psychologist Paul Andreassen conducted a simple experiment on MIT business students. (Those poor students at MIT’s Sloan School of Mangament are very popular research subjects. As one scientist joked to me, “They’re like the fruit fly of behavioral economics”.) First, Andreassen let the students select a portfolio of stock investments. Then he divided the students into two groups. The first group could only see the changes in the prices of their stocks. They had no idea why the share prices rose or fell, and had to make their trading decisions based on an extremely limited amount of data. In contrast, the second group was given access to a steady stream of financial information. They could watch financial news on television, read The Wall Street Journal and consult experts for the latest analysis of market trends.
So which group did better? To Andreassen’s surprise, the group with less information ended up earning more than twice as much money as the well-informed group. Being exposed to extra news was distracting, and the “high-information” students quickly became fixated on the latest rumors and insider gossip. (Herbert Simon said it best: “A wealth of information creates a poverty of attention.”) As a result, these students engaged in far more buying and selling than the “low-information” group. They were convinced that all their knowledge allowed them to anticipate the market. But they were wrong.