Humans aren’t rational. So why should financial theories assume that they are? That’s the question writer Chelsea Wald posed in Crazy Money, in the Dec. 12, 2008 issue of Science. It’s a reasonable question, she explains.
Even the experts seem bewildered by the current economic crisis. Quantitative analysts (quants)–the whiz-kid financial engineers whose algorithms have dominated Wall Street trading in recent years–have watched those algorithms fail. Former Federal Reserve Chair Alan Greenspan acknowledged in October that there was “a flaw in the model that I perceived … defines how the world works.”
The problem: the classical theory of finance does not address human psychology. Computers expect people to behave rationally, which they frequently do not. It’s a reality that any real estate professional knows–but one many apparently overlooked during the heady days of the real estate boom.
In retrospect, it seems like everyone should have predicted the pending collapse of the real estate market. But somehow, most did not. Were they so blinded by technology that they abandoned common sense?
As Wald notes, mathematical models were increasingly used to determine whether someone deserved a loan, bypassing individual judgments. “In the end, there was very little sound credit judgment going into making these credit calls,” says Bjorn Flesaker, a senior quant at Bloomberg in New York City. Then, quant models were used to rate the riskiness of financial instruments, including the CDOs. “We never necessarily viewed the rating agencies as having the greatest rocket scientists around,” says Flesaker, yet investors accepted those ratings, taking on more risk than even they realized.
The still unanswered questions: Why did so many people take on mortgages that they would not be able to pay? Why did the best minds of Wall Street ignore warnings about a housing bubble? Did anybody know that the risks were so great and, if so, why did they continue investing?
Classical finance contends that rational investors will always have the best possible portfolio, so they will not buy or sell unless they have extra money to invest or need to cash in their investments. However, researchers have observed that people buy and sell much more often than that during a bubble–with the rate of transactions becoming increasingly manic the bigger the bubble gets.
In other words, the best statistical models fall short of understanding the quirks and impulsivities of average investors. “Looking to make money off others’ crazy opinions, investors would be willing to pay more than they think an asset is actually worth because they believe that they will be able to sell it in the future to an overeager buyer,” Wald states. “This process would inflate prices and cause a trading frenzy.”
Since human behavior is unlikely to change, the only option is to rethink technology. Modelers are incorporating elements from evolutionary theory and neuroscience. One new model, the Adaptive Market Hypothesis, treats investors as “species” that evolve to compete for limited financial resources. And behaviors like overconfidence can be treated like survival strategies.
But how accurate can any technology predict human behavior, given that one of the key features of human action is its unpredictability?