This paper was prepared for John B. Taylor and Michael Woodford, Editors

14

Lo and MacKinlay (1988) and Lehmann (1990), however, find evidence of negative serial

correlation of individual weekly stock returns between successive weeks.  As explained by Lo and

MacKinlay (1990), weekly returns on portfolios of these same stocks still exhibit positive serial

correlation from week to week because the cross-covariances between returns of individual stocks are

positive.  They conclude that this pattern of cross-covariances is not what one would expect to find

based on theories of investor inertia.  Lehmann, however, has a different interpretation of the negative

week-to-week serial correlation of individual weekly stock returns, that the negative serial correlation

reflects nothing more than the behavior of market makers facing order imbalances and asymmetric

information.

15

Firms’ management appear acutely aware that earnings growth has a psychological impact on

prices, and so attempt to manage earnings accounting to provide a steady growth path.  Impressive

evidence that they do so is found in Degeorge, Patel and Zeckhauser (1997).

16

Modigliani and Cohn (1979) argue that public failure to understand the relation of interest rates

to inflation has caused the stock market to overreact to nominal interest rate changes.

15

for a number of indices of returns on major categories of speculative assets there has been

a tendency for positive autocorrelation of short-run returns over short horizons, less than a

year; see also Jegadeesh and Titman (1993) and Chan, Jegadeesh and Lakonishok (1996).

14

This positive serial correlation in return indices has been interpreted as implying an initial

underreaction of prices to news, to be made up gradually later.  Bernard and Thomas (1992)

found evidence of underreaction of stock prices to changes, from the previous year, in

company earnings:  prices react with a lag to earnings news; see also Ball and Brown

(1968).

15

  Irving Fisher (1930, Ch. XXI, pp. 493–94) thought that, because of human error,

nominal interest rates tend to underreact to inflation, so that there is a tendency for low real

interest rates in periods of high inflation, and high real rates in periods of low inflation.

More recent data appear to confirm this behavior of real interest rates, and data on

inflationary expectations also bear out Fisher’s interpretation that the phenomenon has to

do with human error; see De Bondt and Bange (1992) and Shefrin (1997).

16

Does the fact that securities prices sometimes underreact pose any problems for the

psychological theory that people tend to be overconfident?  Some observers seem to think

that it does.  In fact, however, overconfidence and overreaction are quite different

phenomena.  People simply cannot overreact to everything: if they are overconfident they

will make errors, but not in any specified direction in all circumstances.  The concepts of

overreaction or underreaction, while they may be useful in certain contexts, are not likely

to be good psychological foundations on which to organize a general theory of economic

behavior.

The fact that both overreaction and underreaction are observed in financial markets has

been interpreted by Fama (1997) as evidence that the anomalies from the standpoint of

efficient markets theory are just “chance results,” and that therefore the theory of market

efficiency survives the challenge of its critics.  He is right, of course, that both overreaction

and underreaction together may sometimes seem a little puzzling.  But one is not likely to

want to dismiss these as “chance results” if one has an appreciation for the psychological

theory that might well bear on these phenomena.  In his survey of behavioral finance Fama

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(1997) makes no more than a couple of oblique references to any literature from the other

social sciences.  In fact, Fama states that the literature on testing market efficiency has no

clearly stated alternative, “the alternative hypothesis is vague, market inefficiency” (p. 1).

Of course, if one has little appreciation of these alternative theories then one might well

conclude that the efficient markets theory, for all its weaknesses, is the best theory we have.

Fama appears to believe that the principal alternative theory is just one of consistent

overreaction or underreaction, and says that “since the anomalies literature has not settled

on a testable alternative to market efficiency, to get the ball rolling, I assume that reasonable

alternatives must predict either over-reaction or under-reaction” (p. 2).  The psychological

theories reviewed here cannot be reduced to such simple terms, contrary to Fama’s

expectations.

Barberis, Shleifer and Vishny (1997) provide a psychological model, involving the

representativeness heuristic as well as a principle of conservatism (Edwards, 1968), that

offers a reconciliation of the overreaction and underreaction evidence from financial

markets; see also Daniel, Hirshleifer and Subrahmanyam (1997) and Wang (1997).  More

work could be done in understanding when it is that people overreact in financial markets

and when it is that they underreact.  Understanding these overreaction and underreaction

phenomena together appears to be a fertile field for research at the present time.  There is

neither reason to think that it is easy obtain such an understanding, nor reason to despair that

it can ever be done.

Overconfidence may have more clear implications for the volume of trade in financial

markets than for any tendency to overreact.  If we connect the phenomenon of

overconfidence with the phenomenon of anchoring, we see the origins of differences of

opinion among investors, and some of the source of the high volume of trade among

investors.  People may fail to appreciate the extent to which their own opinions are affected

by anchoring to cues that randomly influenced them, and take action when there is little

reason to do so.

The extent of the volume of trade in financial markets has long appeared to be a puzzle.

The annual turnover rate (shares sold divided by all shares outstanding) for New York Stock

Exchange Stocks has averaged 18% a year from the 1950s through the 1970s, and has been

much higher in certain years.  The turnover rate was 73% in 1987 and 67% in 1930.  It does

not appear to be possible to justify the number of trades in stocks and other speculative

assets in terms of the normal life-cycle ins and outs of the market.  Theorists have

established a “nonspeculation theorem” that states that rational agents who differ from each

other only in terms of information and who have no reason to trade in the absence of

information will not trade (Milgrom and Stokey, 1982l; Geanakoplos, 1992).

Apparently, many investors do feel that they do have speculative reasons to trade often,

and apparently this must have to do with some tendency for each individual to have beliefs

that he or she perceives as better than others’ beliefs.  It is as if most people think they are

above average.

Odean (1996a), in analyzing individual customer accounts at a nationwide discount

brokerage house, examined the profits that customers made on trades that were apparently

not motivated by liquidity demands, tax loss selling, portfolio rebalancing, or a move to

lower-risk securities.  On the remaining trades, the returns on the stocks purchased was on

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