The problem is that most people are simply overconfidentin their
own abilities. To put it another way, the average individual—whether a
student, a trader, a driver, or anything else—believes he or she is better
than average, which of course is statistically impossible.^12
Dave:What causes this overconfidence?
IC:Overconfidence comes from several sources. First, there is what we
call a self-attribution biasthat causes one to take credit for a favorable turn
of events when credit is not due.^13 Remember in March 2000 bragging to
your wife about how smart you were to have bought those Internet
stocks?
Dave:Yes. And was I wrong!
IC:Your early success fed your overconfidence.^14 You and your friends
attributed your stock gains to skillful investing, even though those out-
comes were frequently the result of chance.
Another source of overconfidence comes from the tendency to see
too many parallels between events that seem the same.^15 This is called
therepresentative bias. This bias actually arises because of the human
learning process. When we see something that looks familiar, we form a
representative heuristic to help us learn. But the parallels we see are
often not valid, and our conclusions are misguided.
Dave:The investment newsletters I get say that every time such-and-
such event has occurred in the past, the market has moved in a certain
direction, implying that it is bound to do so again. But when I try to use
that advice, it never works.
IC:Conventional finance economists have been warning for years about
finding patterns in the data when in fact there are none. Searching past
data for patterns is called data mining, and it is easier than ever to do
326 PART 4 Stock Fluctuations in the Short Run
(^12) B. Fischhoff, P. Slovic, and S. Lichtenstein, “Knowing with Uncertainty: The Appropriateness of
Extreme Confidence,” Journal of Experimental Psychology: Human Perception and Performance, vol. 3
(1977), pp. 552–564.
(^13) A. H. Hastorf, D. J. Schneider, and J. Polefka, Person Perception, Reading: Mass.: Addison-Wesley,
1970.
(^14) For reference to a model that incorporates success as a source of overconfidence, see Simon Ger-
vais and Terrance Odean, “Learning to Be Overconfident,” Review of Financial Studies, vol. 14, no. 1
(2001), pp. 1–27.
(^15) For references to models that incorporate the representative heuristic as a source of overconfi-
dence, see either N. Barberis, A. Shleifer, and R. Vishny, “A Model of Investor Sentiment,” National
Bureau of Economic Research (NBER) Working Paper No. 5926, NBER, Cambridge, Mass., 1997, or
Kent Daniel, David Hirshleifer, and Avandihar Subrahmanyam, “Investor Psychology and Security
Market Under- and Overreactions,” Journal of Finance, vol. 53 no. 6 (1998), pp. 1839–1886.