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forecasts of a firm™s future earnings are high, they tend to be too high relative to the
objective prospects of the firm. This results in a high initial P/E (due to the optimism
built into the stock price) and poor subsequent performance when investors recognize
their error. Thus, high P/E firms tend to be poor investments in general.
2. Overconfidence. People tend to underestimate the imprecision of their beliefs or
forecasts, and they tend to overestimate their abilities. In one famous survey, 90% of
drivers in Sweden ranked themselves as better-than-average drivers. Such overconfidence
may be responsible for the prevalence of active versus passive investment management”
itself an anomaly to an adherent of the efficient market hypothesis. Despite the recent
growth in indexing, less than 10% of the equity in the mutual fund industry is held in
indexed accounts. The dominance of active management in the face of the typical
underperformance of such strategies (consider the disappointing performance of actively
managed mutual funds documented in Chapter 4 as well as in the following pages) is
consistent with a tendency to overestimate ability.
An interesting example of overconfidence in financial markets is provided by Barber
and Odean (2000, 2001), who compare trading activity and average returns in brokerage
accounts of men and women. They find that men (in particular single men) trade far
more actively than women, consistent with the greater overconfidence among men

6
This discussion is based on W.F.M. De Bondt and R. H. Thaler, “Financial Decision Making in Markets and Firms,”
in Handbooks in Operations Research and Management Science, Volume 9: Finance, eds. R. A. Jarrow, V. Maksi-
movic, W. T. Ziemba (Amsterdam: Elsevier, 1995).
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Essentials of Investments, Hypothesis Companies, 2003
Fifth Edition




281
8 The Efficient Market Hypothesis


well-documented in the psychology literature. They also find that high trading activity is
highly predictive of poor investment performance. The top 20% of accounts ranked by
portfolio turnover had average returns seven percentage points lower than the 20% of the
accounts with the lowest turnover rates. As they conclude, “Trading [and by implication,
overconfidence] is hazardous to your wealth.”
3. Regret avoidance. Psychologists have found that individuals who make decisions that
turn out badly have more regret (blame themselves more) when that decision was more
unconventional. For example, buying a blue-chip portfolio that turns down is not as
painful as experiencing the same losses on an unknown start-up firm. Any losses on the
blue-chip stocks can be more easily attributed to bad luck rather than bad decision
making and cause less regret. De Bondt and Thaler (1987) argue that such regret theory is
consistent with both the size and book-to-market effect. Higher book-to-market firms
tend to have lower stock prices. These firms are “out of favor” and more likely to be in a
financially precarious position. Similarly, smaller less-well-known firms are also less
conventional investments. Such firms require more “courage” on the part of the investor,
which increases the required rate of return.
4. Framing and mental accounting. Decisions seem to be affected by how choices are
framed. For example, an individual may reject a bet when it is posed in terms of possible
losses but may accept that same bet when described in terms of potential gains. Mental
accounting is another form of framing in which people segregate certain decisions. For
example, an investor may take a lot of risk with one investment account but establish a
very conservative position with another account that is dedicated to her child™s education.
But it might be better to view both accounts as part of the investor™s overall portfolio
with the risk-return profiles of each integrated into a unified framework. Statman (1997)
argues that mental accounting is consistent with some investors™ irrational preference for
stocks with high cash dividends (they feel free to spend dividend income, but will not
“dip into capital” by selling a few shares of another stock with the same total rate of
return) and with a tendency to ride losing stock positions for too long (since “behavioral
investors” are reluctant to realize losses).
The nearby box offers good examples of several of these psychological tendencies in an in-
vestment setting.


Mutual Fund Performance
We have documented some of the apparent chinks in the armor of efficient market pro-
ponents. Ultimately, however, from the perspective of portfolio management, the issue of
market efficiency boils down to whether skilled investors can make consistent abnormal
trading profits. The best test is simply to look at the performance of market professionals
and see if their performance is superior to that of a passive index fund that buys and holds
the market.
As we pointed out in Chapter 4, casual evidence does not support the claim that profes-
sionally managed portfolios can consistently beat the market. Figures 4.3 and 4.4 in that chap-
ter demonstrated that between 1972 and 2000, a passive portfolio indexed to the Wilshire 5000
typically would have better returns than the average equity fund. On the other hand, there was
some (admittedly inconsistent) evidence (see Table 4.3) of persistence in performance, mean-
ing that the better managers in one period tended to be better managers in following periods.
Such a pattern would suggest that the better managers can with some consistency outperform
their competitors and would be inconsistent with the notion that market prices already reflect
all relevant information.
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Essentials of Investments, Hypothesis Companies, 2003
Fifth Edition




Don™t Ignore Luck™s Role in Stock Picks
When stock-market investors take a hit, they rail at their “People say, ˜My investment adviser didn™t get me
stupidity and question their investment strategy. But out of tech stocks in time, so I™m going to fire him.™”
when lottery ticket buyers lose, they shrug off their bad Mr. Reichenstein says, “The assumption is that you can
luck and pony up for another ticket. successfully pick sectors. But nobody can do that.”
Maybe those lottery players have the right idea.
Timing Patterns
Sure, if you lose a bundle in the stock market, it
could be your fault. But there is a fair chance that the Did you load up on stocks, only to see the market tank?
real culprits are bad luck and skewed expectations. Don™t feel bad. Short-run market activity is utterly un-
Examples? Consider these three: predictable. That is why investors who buy stocks need
a long time horizon.
Picking on Yourself “When people buy and the market goes down, that
If one of your stocks craters, that doesn™t necessarily is when regret hits the most, because they can easily
mean you are a fool and that your investment research imagine postponing the purchase,” Mr. Statman says.
was inadequate. By the same token, a soaring stock “People feel that the market is picking on them person-
doesn™t make you a genius. The fact is, the stock mar- ally.” But in truth, buying stocks ahead of a market de-
ket is pretty darn efficient. cline is just bad luck.
“When people buy stocks, they think they are playing Similarly, folks can also draw the wrong lesson from
a game of skill,” says Meir Statman, a finance professor their successes. For instance, if you made a brilliantly
at Santa Clara University in California. “When the stock timed switch between stocks and cash, that may bolster
goes down rather than up, they think they have lost their your self-confidence and make you think you are
knack. But they should take heart. All they have lost is smarter than you really are.
luck. And next time, when the stock goes up, they Once you accept that investment gains and losses
should remember that that was luck, too.” are often the result of luck rather than brains, you may
find it easier to cope with market turmoil. But what if
All Over the Map you still kick yourself with every investment loss? A fi-
nancial adviser could come in handy. Sure, the cost in-
Just as your portfolio likely will include a fair number of
volved will hurt your investment returns. But there is a
losing stocks, so you may have exposure to stock-market
little-mentioned benefit.
sectors that post lackluster returns for long periods. Were
“Investors use advisers as scapegoats, blaming
you wrong to invest in those sectors? Probably not.
them for all the stocks that went down while claiming
“In the 1990s, U.S. stocks beat international stocks,”
credit themselves for all the stocks that went up,” Mr.
notes William Retchenstein, an investments professor at
Statman says. “In an odd way, when people hire advis-
Baylor University in Waco, Texas. “That doesn™t mean
ers, they get their money™s worth.”
international diversification isn™t needed or doesn™t work.
International diversification is about reducing risk before
the fact. In 1990, no one knew that the U.S. would be
SOURCE: Jonathan Clements, “Don™t Ignore Luck™s Role in Stock
the hottest market for the decade. Similarly, today no Picks,” The Wall Street Journal, September 26, 2000. Reprinted by
one knows which region will be the hottest market. permission of The Wall Street Journal, © 2000 Dow Jones &
That™s why we diversify. Company, Inc. All Rights Reserved Worldwide.




On the other hand, the analyses in Chapter 4 were based on total returns unadjusted for ex-
posure to systematic risk factors. In this section, we will revisit the question of mutual fund
performance, paying more attention to the benchmark against which performance ought to be
evaluated.
As a first pass, we can examine the risk-adjusted returns (i.e., the alpha, or return in excess
of required return based on beta and the market return in each period) of a large sample of mu-
tual funds. Malkiel (1995) computes these abnormal returns for a large sample of mutual funds
between 1972 and 1991. The results, which appear in Figure 8.6, show that the distribution of
alphas is roughly bell shaped, with a mean that is slightly negative but statistically indistin-
guishable from zero. On average, it does not appear that these funds outperformed the market
index (the S&P 500) on a risk-adjusted basis.
282
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Essentials of Investments, Hypothesis Companies, 2003
Fifth Edition




283
8 The Efficient Market Hypothesis




36

32

28

24
Frequency




20

16

12

8

4

0
“3 “2 “1 0 1 2
Alpha




F I G U R E 8.6
Estimates of individual mutual fund alphas, 1972 to 1991
Note: The frequency distribution of estimated alphas for all equity mutual funds with 10-year continuous records.
Source: Burton G. Malkiel, “Returns from Investing in Equity Mutual Funds 1971“1991,” Journal of Finance 50 (June 1995), pp. 549“72.




One problem in interpreting these alphas is that the S&P 500 may not be an adequate
benchmark against which to evaluate mutual fund returns. Because mutual funds tend to main-
tain considerable holdings in the equity of small firms, while the S&P 500 exclusively com-
prises large firms, mutual funds as a whole will tend to outperform the index when small firms
outperform large ones, and underperform when small firms fare worse. Thus, a better bench-
mark for the performance of funds would be an index that incorporates the stock market per-
formance of smaller firms.
The importance of the benchmark can be illustrated by examining the returns on small
stocks in various subperiods.7 In the 20-year period between 1945 and 1964, a small stock in-
dex underperformed the S&P 500 by about 4% per year on a risk-adjusted basis. In the fol-
lowing 20-year period between 1965 and 1984, small stocks outperformed the S&P index by
10%. Thus, if one were to examine mutual fund returns in the earlier period, they would tend
to look poor, not necessarily because small-fund managers were poor stock pickers, but sim-
ply because mutual funds as a group tend to hold more small stocks than are represented in the
S&P 500. In the later period, funds would look better on a risk-adjusted basis relative to the
S&P 500 because small funds performed better. The “style choice” (i.e., the exposure to small
stocks, which is an asset allocation decision) would dominate the evaluation of performance
even though it has little to do with managers™ stock-picking ability.8
Elton, Gruber, Das, and Hlavka (1993) attempt to control for the impact of non-S&P assets
on mutual fund performance. They calculate mutual fund alphas controlling for both the effects

7
This illustration and the statistics cited are based on a paper by Elton, Gruber, Das, and Hlavka (1993).
8
Remember from Chapter 1 that the asset allocation decision is usually in the hands of the individual investor. In-
vestors allocate their investment portfolios to mutual funds with holdings in asset classes they desire and can reason-
ably expect only that portfolio managers will choose stocks advantageously within those asset classes.
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Fifth Edition




284 Part TWO Portfolio Theory


Type of Fund Number t-Statistic
TA B L E 8.1 (Wiesenberger classification) of Funds Alpha for Alpha
Performance of
Equity funds
mutual funds based
on the three-index Maximum capital gain 12 4.59 1.87
model Growth 33 1.55 1.23
Growth and income 40 0.68 1.65
Balanced funds 31 1.27 2.73

Note: The three-index model calculates the alpha of each fund as the intercept of the following regression:
r rf M(rM rf ) S (rS rf ) D(rD rf ) e
where r is the return on the fund, rf is the risk-free rate, rM is the return on the S&P 500 index, rS is the return on a non-S&P small-
stock index, rD is the return on a bond index, e is the fund™s residual return, and the betas measure the sensitivity of fund returns to
the various indexes.
Source: E. J. Elton, M. J. Gruber, S. Das, and M. Hlavka, “Efficiency with Costly Information: A Reinterpretation of Evidence
from Managed Portfolios,” Review of Financial Studies 6 (1993), pp. 1“22.


of firm size and interest rate movements. Some of their results are presented in Table 8.1, which
shows that average alphas are negative for each type of equity fund, although generally not of
statistically significant magnitude. They conclude that after controlling for the relative per-
formance of these three asset classes”large stocks, small stocks, and bonds”mutual fund
managers as a group do not demonstrate an ability to beat passive strategies that would simply
mix index funds from among these asset classes. They also find that mutual fund performance
is worse for firms that have higher expense ratios and higher turnover ratios. Thus, it appears
that funds with higher fees do not increase gross returns by enough to justify those fees.
Carhart (1997) reexamines the issue of consistency in mutual fund performance controlling

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