(1997), Odean (1998), and Wang (1998) provide specifications of overcon-
fidence as overestimation of information precision, but do not distinguish
between private and public signals in this regard (see also Caballé and
Sákovics 1996). Odean (1998) examines overconfidence about, and conse-
quent overreaction to, a private signal. As a consequence there is excess
volatility and negative return autocorrelation. Because our model assumes
that investors are overconfident only about private signals, we obtain un-
derreaction as well as overreaction effects. Furthermore, because we con-
sider time-varying confidence, there is continuing overreaction to private
signals over time. Thus, in contrast with Odean, we find forces toward pos-
itive as well as negative autocorrelation; and we argue that overconfidence
can decrease volatility around public news events.^1
Daniel, Hirshleifer, and Subrahmanyam (1998) show that our specifica-
tion of overconfidence can help explain several empirical puzzles regarding
cross-sectional patterns of security return predictability and investor behav-
ior. These puzzles include the ability of price-based measures (dividend yield,
earnings/price, B/M, and firm market value) to predict future stock returns,
possible domination of βas a predictor of returns by price-based variables,
and differences in the relative ability of different price-based measures to
predict returns.
A few other recent studies have addressed both overreaction and underre-
action in an integrated fashion. Shefrin (1997) discusses how base-rate un-
derweighting can shed light on the anomalous behavior of implied volatili-
ties in options markets. In a contemporaneous paper, Barberis, Shleifer, and
Vishny (1998) offer an explanation for under- and overreactions based on a
learning model in which actual earnings follow a random walk, but individ-
uals believe that earnings follow either a steady growth trend, or else are
mean-reverting. Since their focus is on learning about the time-series process
of a performance measure such as earnings, they do not address the sporadic
events examined in most event studies. In another recent paper, Hong and
Stein (1999) examine a setting where under- and overreactions arise from
the interaction of momentum traders and news watchers. Momentum
traders make partial use of the information contained in recent price trends,
and ignore fundamental news. Fundamental traders rationally use funda-
mental news but ignore prices. Our work differs in focusing on psychologi-
cal evidence as a basis for assumptions about investor behavior.
The remainder of the chapter is structured as follows. Section 1 describes
psychological evidence of overconfidence and self-attribution bias. Section 2
develops the basic model of overconfidence. Here, we describe the economic
setting and define overconfidence. We analyze the equilibrium to derive
implications about stock price reactions to public versus private news,
464 DANIEL, HIRSHLEIFER, SUBRAHMANYAM
(^1) A recent revision of Odean’s paper offers a modified model that allows for underreaction.
This is developed in a static setting with no public signals, and therefore does not address is-
sues such as short-term versus long-term return autocorrelations, and event study anomalies.