112 THEORY AND EVIDENCE ON SHORT SELLING
model. (As discussed above, the major exception may be among stocks
of different sizes.) Thus, selection among possible additions to the port-
folio (especially of the same size) cannot be based on anticipated
returns. However, the contributions to diversification (and risk reduc-
tion) are likely to differ between securities.
Markowitz optimization may be useful in identifying possible risk
reducing additions to the portfolio. This procedure is cheap if historical
data are used in deriving the covariance matrix (with sophisticated
methods used to reduce the large random element in historically derived
portfolios
58
). Normally, candidates for analysis can be identified this
way at low cost. If they prove after analysis not to be overpriced, they
may be purchased. Hopefully, by repeating this process, diversification
can be maintained at low transactions costs. Only if this procedure fails
would sales for the purpose of maintaining diversification be done.
It is conceivable that the optimal portfolio strategy is to combine
analyzed stocks with unanalyzed ones. This might happen if certain cat-
egories were believed to have such efficiently priced securities as not to
justify any analysis, and other categories had less efficiently priced secu-
rities. The most plausible example of this would be where there were
believed to be opportunities for analysis in small stocks, while certain
large stocks were so well studied that one did not expect to be able to
uncover information not reflected in the prices. Yet, diversification
might require some exposure to large capitalization stocks. One optimi-
zation exercise might combine studied small stocks expected to earn a
competitive 12%, with other stocks selected by simple rules and
expected to yield 10%. There are firms now that offer to provide com-
pleteness portfolios at low cost to provide diversification and exposure
to types of securities one does not maintain expertise in.

overpriced, one forgoes the added diversification benefit. Of course, after
the analysis is done the $100,000 is already spent and the portfolio return
reduced by this amount. At least conceptually, with knowledge of the cli-
ent’s trade off between expected return and risk, whether analyzing an
additional stock was worthwhile can be determined.
In doing such an analysis notice the only inputs to Markowitz opti-
mization (and similar procedures) are expected returns and a covariance
matrix. The size of the firm does not enter into the calculations. If one
believes it will be cheaper to analyze a small firm (perhaps because it is
in only one line of business), the ratio of added benefit to the portfolio
from identifying a suitable security to the cost of analysis will be great-
est for the smaller stocks.
In practice, one usually cannot purchase the required analysis of an
additional stock at short notice. The difficulty is not finding someone to
take your money and give an opinion. It is not even finding someone
whose opinion you think is worth $100,000. The difficulty is being sure
the new analysis is comparable with the analysis done by your own staff.
Thus, the information on the benefits of analyzing an additional stock is
most useful in deciding on how large an analytic budget to incur.
In practice, the cost of an analytic staff is fixed in the short run. Pro-
cedures such as discussed above aid in determining the budget for analy-
sis and the number of stocks to be followed. In the example above, a
budget of $2,500,000 per year would permit following 25 stocks. The
expected portfolio size would be 20 stocks (allowing for a fifth to be
rejected). These 20 would be in the portfolio (with perhaps weights cho-
sen by an optimization program) and the analytic resources devoted to
following these 20 stocks, plus five more as candidates for purchase and
to replace any that became overpriced. Analyses of this type would be
done form time to time to determine if the staff size was optimal. There
is a role for consultants, because managers are likely to be always in

conservative side. Conservatism will seldom lead to underpricing since
there will usually be enough well informed investors to keep the stock
priced at least competitively. However, if the accounting sometimes
exaggerates profits, there are likely to be enough poorly informed inves-
tors for the stock to become overpriced.
The obstacles to short selling, especially failure to receive full use of
the proceeds or to receive a market return on them, are more important
when the errors in pricing will occur years in the future than when they
will be revealed in the near future. Exploitable opportunities to avoid
59
See Chapter 7.
5-Miller-Restrictions Page 114 Thursday, August 5, 2004 11:10 AM
Restrictions on Short Selling and Exploitable Opportunities for Investors 115
overpriced stocks are most likely when the overpricing is due to various
factors that will be typically revealed only years in the future. Possible
opportunities arise from things like extrapolating growth too far in the
future, not allowing for new entry or market saturation, leaving out
numerous low probability adverse events that in the aggregate have an
appreciable effect, and the like. Looking for such events several years
out probably has a higher return than trying to forecast next year’s
earnings, which is where so much effort is expended.
Since competition makes it very difficult to identify stocks that are
grossly undervalued, investment success comes from avoiding losers
rather than finding great winners. Investing is a loser’s game. If great
winners will be very hard to find in a competitive economy, analytic
effort should be focused on a small number of stocks which can be
extensively studied, rather than on an extensive search for stocks that
will double in a year. Typically, investment managers try to follow far
too many stocks, frequently failing as a result to uncover relevant nega-
tive information about certain stocks.

1
It will be shown here that in a world with restricted short selling that
1. Divergence of opinion tends to raise prices.
2. Thus profits can be improved by avoiding stocks with high divergence
of opinion, including those analysts disagree about.
3. When the divergence of opinion drops, stock prices tend to decline.
1
Edward M. Miller, “Risk, Uncertainty, and Divergence of Opinion,” Journal of Fi-
nance (September 1977), pp. 1,151–1,168.
M
6-Miller-Implications Page 117 Thursday, August 5, 2004 11:11 AM
118 THEORY AND EVIDENCE ON SHORT SELLING
4. Since the divergence of opinion on initial public offerings declines as
they become seasoned, these stocks tend to underperform the market.
5. Since risk correlates with divergence of opinion, the return to risk, both
systematic and nonsystematic, is less than the typical investor would
require to invest in risky stocks.
6. Thus, the typical investors should overweight the less risky stocks in his
portfolio.
7. There is a winner’s curse effect in the stock markets such that you tend
to purchase the stocks you erred in evaluating. This holds even if every
single investor is, on average, unbiased in his or her valuations.
This chapter will develop the implications for practitioners of a
world where there is little short selling and where investors disagree
about the merits of securities. Both seem at least as plausible as the
alternatives, that investors trade in perfect markets and always agree on
the values for all relevant variables (and successfully do the complex
calculations required to construct an optimal portfolio).
Textbooks sometimes deduce that security prices should be efficient
by assuming homogeneous beliefs. This is obviously wrong since people

least one of the opinions (and perhaps all of them) is wrong. To make it pos-
sible to compare this theory with the efficient market theory, the assumption
will be made that investors all have unbiased expectations. Of course, this is
just an exposition device. The behavioral finance literature shows that all
sorts of biases exist. Unbiased expectations means that if all the opinions
were averaged, the average would be the correct value. Incidentally, it may
even be true that each investor is on average correct when his estimates are
averaged over all the stocks he follows, even though he is sometimes high
and sometimes low. Finally, the implications of divergence of opinion for
value additivity, closed-end funds, and spin-offs will be developed.
INTERACTION OF DIVERGENCE OF OPINION AND SHORT SELLING
RESTRICTIONS
A distribution can be represented in either probability density form or
cumulative form. The first bell-shaped curve in Exhibit 6.1 shows the
distribution of investors’ opinions about the security’s maximum value.
This is the price at which the security just enters into their portfolios. At
lower prices they may hold more of the security, although this effect
cannot easily be shown in the exhibit (since it has only two dimensions).
EXHIBIT 6.1
Number of Investors with Various Estimates of Value
6-Miller-Implications Page 119 Thursday, August 5, 2004 11:11 AM
120 THEORY AND EVIDENCE ON SHORT SELLING
The same information can also be shown as a cumulative distribu-
tion as shown in Exhibit 6.2. The vertical axis is the price and the hori-
zontal axis shows the number of investors whose willingness to pay for
a security is at, or below, that level.
For expositional convenience, imagine that investors buy one share
if they decide to include a security in their portfolios and no shares oth-
erwise. (The argument can easily be generalized to where each investor
buys a certain number of shares depending on his wealth and diversifi-

Danielson, and Sorensen, as part of a larger study (discussed later), report
that the mean short interest as of July 1, 1999, was only 1.454% of the
number of shares held.
2
Even looking at the top 1% of firms, the short
interest was only 15.6%. One would expect much higher ratio if there were
not obstacles to short selling, whether institutional or psychological.
Equilibrium Prices Do Not Equal Consensus Value Estimates
Several simple points emerge from the above analysis. Probably most
important is that there is nothing to insure that the demand and supply
curves intersect at a price representing the consensus valuation of all
investors. The consensus is at point A, the value where half of the inves-
tors think the stock is worth more and half think it is worth less. Only by
coincidence would this consensus value be the market determined price.
Normally only a small fraction of investors can absorb a security’s
total floating supply. Consider a small company with ten million shares
outstanding. Suppose each investor purchases 1,000 shares. Only 10,000
investors need think the stock is worth holding to absorb the whole sup-
ply of the stock. The stock will be priced at the level that is just adequate
to induce the marginal investor, the ten thousandth investor, to hold it.
Normally, much less than half of the investors can absorb the float-
ing supply of a stock, with the result that the marginal investor’s evalua-
tion is far above the valuation of the median investor or the average
investor. An alternative way to express the argument so far is that the
2
Rodney D. Boehme, Bartley R. Danielson, and Sorin M. Sorescu, “Short Sale Con-
straints and Overvaluation,” working paper, American Finance Association 2003
Annual Conference, January 2003.
6-Miller-Implications Page 121 Thursday, August 5, 2004 11:11 AM
122 THEORY AND EVIDENCE ON SHORT SELLING

This explains why equilibrium will be reached on the right hand
side of the distribution, with the optimists setting the price.
Varying the Divergence of Opinion
While the basic mechanism of price determination is best understood using
a cumulative distribution, the effects of changing the distribution can best
be understood using probability density diagrams. Consider Exhibit 6.1.
The number of investors who believe the stock will earn at least a certain
percentage is represented by the area to the right of the value.
Now let us consider increasing the divergence of opinion while
holding the average opinion constant. In the exhibit, this widens the dis-
3
Joseph Chen, Harrison Hong, and Jeremy C. Stein, “Breadth of Ownership and
Stock Returns,” Journal of Financial Economics (2002), pp. 171–205, Table 1.
4
Brad M. Berber and Terrance Odean, “Trading is Hazardous to Your Wealth: The
Common Stock Investment Performance of Individual Investors,” Journal of Finance
(April 2000), pp. 773–806.
6-Miller-Implications Page 122 Thursday, August 5, 2004 11:11 AM
Implications of Short Selling and Divergence of Opinion for Investment Strategy 123
tribution while holding its center fixed. As can be seen, as long as only a
fraction of the investors find the security attractive, a wider distribution
of opinion raises the price above which enough investors can be found
to absorb the fixed supply of a particular stock. Thus, the greater the
divergence of opinion, the higher the price can be expected to be.
One implication of Exhibit 6.3 is that the more investors are
required to absorb the supply of a security, the further to the left on the
diagram will be the equilibrium. This implies a lower price. Holding the
future dividends constant, a lower price implies a higher rate of return.
If we define breadth to be the percentage of investors that include a long
position in their portfolios, the implication is that stocks with a high

funds have reduced their holdings to zero, there are other funds that are in the pro-
cess of reducing their holdings and this produces continued selling. There may also
be a degree of herding among institutional investors such that after one fund has ac-
cumulated a position it then talks it up, inducing other funds to go into it.
Analyzing changes in breadth while holding the number of shares constant im-
plies that the intramarginal investors are changing their holdings of the stock, or that
there is a change in the fraction of potential investors who are bothering to examine
a stock. If existing investors are changing their holdings of the stock (the depth), one
needs to explain why. One possibility is that a few large investors (members of
founding families typically) are choosing to reduce their holdings. While their ratio-
nalization may be diversifying their own portfolios, the timing is likely to avoid pe-
riods when their inside information says it is best to continue to hold the stock and,
at worse, to be when their actual inside information tells them the price is likely to
decline. The increase in breadth is offset by a decrease in depth by the informed in-
vestors. Of course, rational investors, upon reading of such insider sales, are likely
to deduce that the future is not bright. This effect would be likely to lower return.
Another possibility is that the shape of the distribution of opinion changes. If the
optimistic investors become less optimistic, while still remaining optimistic enough
to hold the stock, they could generate net selling that result in an increase in breadth.
The problem is that this is a change in the information set that is likely to make it
harder to untangle the effect of pure breadth. In particular, this would be a change
in the average expectations that changed the average opinion. This would tend to
lower the future returns while the breadth increase was increasing them.
In Markowitz optimization, the limits to accumulating a stock with a high return
is set by the increased risk to the portfolio. The higher the standard deviation (risk)
of the stock, the quicker this limit is reached. Thus, an increase in risk could generate
increased selling by existing holders that leads to an increase in breadth.
6-Miller-Implications Page 124 Thursday, August 5, 2004 11:11 AM
Implications of Short Selling and Divergence of Opinion for Investment Strategy 125
ine investors all make estimates of returns (subject to errors of course)

(say cement) or that serve populations that are too poor to have many
investors (rural areas perhaps) may not be looked at very often. If only a
few investors look at a firm, it has to be priced so that a higher propor-
tion of those that look will choose to buy. This implies that these
neglected firms will provide on average higher returns. This theory has
been set out in detail elsewhere.
8
Technology can change the number of firm’s investor’s look at. Pre-
modern computer technology, small firms (especially those located out
of money market centers) failed to come to the attention of many inves-
7
Robert C. Merton, “A Simple Model of Capital Market Equilibrium with Incom-
plete Information,” Journal of Finance (July 1987), pp. 483–510.
8
Edward M. Miller, “Can the Neglected Stock Effect be Explained by Two Stage De-
cision Making?” Review of Business and Economic Research (Fall 1989), pp. 64–73.
6-Miller-Implications Page 125 Thursday, August 5, 2004 11:11 AM
126 THEORY AND EVIDENCE ON SHORT SELLING
tors. Now computer screening tools are widely available. A screen is
just as likely to show up a small firm as a large one (assuming size is not
being used as a screen and set to automatically exclude the small firms).
If this results in more small firms being viewed, the marginal investors
for small firms could now be even further to the right than large firms.
This might imply that their returns going forward would be below nor-
mal. This speculation also predicts that during the period in which
screening programs were coming into use, more and more small firms
would be “discovered” and have their prices bid up. This would cause
an overperformance of small firms during the period when computer-
ized screening was coming into use.
The above argument shows that prices will be higher and returns

tions,” Journal of Petroleum Technology (June 1971), pp. 641–653.
10
Edward M. Miller (principal investigator and author of most of study), Study of
Energy Fuel Resources, Vol. 1 (Cambridge, MA: Abt Associates, 1969).
6-Miller-Implications Page 126 Thursday, August 5, 2004 11:11 AM
Implications of Short Selling and Divergence of Opinion for Investment Strategy 127
Consider an auction where a bidder sees the price rise above what he
things something is worth. In discussions of the winner’s curse it is
assumed he simply drops out of the bidding (reduces his demand to
zero). However, if short selling was possible, he would offer to sell
short. The price would then reflect the average valuation. If the average
bidder was correct in his valuation, the price would reflect this and there
would not be a winner’s curse.
The author originally worked out the winner’s curse effect for a
study of the sale of federal oil and gas leases, and then later realized the
effect could be extended to other markets where true values were uncer-
tain and prices were set by competitive bidding.
11
The stock market is
such a market.
In a market that exhibits winner’s curse behavior, investors are typi-
cally disappointed with the outcomes of their investment even if their
original estimates were unbiased. Divergence of opinion implies that at
least some investors’ estimates contain errors. In a model where the
security ends up being owned by the optimistic investors with the high-
est valuations, there is a positive correlation between the error in an
estimate and the probability of the security being included in the portfo-
lio. Thus the expected error conditional on a security’s inclusion in the
portfolio is positive. This implies that the securities selected perform
worse than anticipated.

One solution to this problem is to reduce return estimates for the
expected error before choosing the optimal portfolio. This problem has
had some discussion in the bidding literature and in the capital budget-
ing literature where it has been referred to as the problem of “uncer-
tainty induced bias.”
14
The amount of the reduction increases with the
uncertainty in the return estimates. While the paper proposing this
made the list of the 25 most-cited financial management papers,
15
the
idea has yet to make it into textbooks. However, explicit solutions have
not been worked out for investment applications. The need for this cor-
rection for uncertainty induced bias is not generally appreciated, and
examination of textbooks will show the recommended procedure is to
make the best estimate of expected return and risk that is practical, and
then to compute an optimal portfolio using these as inputs. The text-
books do not even point out the problem.
It is necessary to correct for the winner’s curse effect. I have dis-
cussed how to do this in the capital budgeting literature under the sub-
ject of uncertainty induced bias.
16
Using a decision tree argument, it can
be shown that even with unbiased estimates that net present value is the
wrong criteria. This happens whenever there are more poor projects
than good ones. This situation is normally to be expected in competitive
markets. Of course, security selection is one type of capital budgeting
problem, presumably one that might benefit from this approach.
Sources of Divergence of Opinion
The discussion in the previous section has left unclear the assumption

neer may know things from his job can be easily applied to evaluating a
semiconductor investment, while another investor would have to con-
sciously educate himself on these issues to understand. Those whose
occupations are in medicine, engineering, law, and the like may in the
course of the business learn things about companies and their products
that the professionals employed by institutions learn only later. Another
source of divergence of opinion is that some investors have inside infor-
mation and others do not.
Investment Implications
There is a large body of theoretical literature on the asymmetric infor-
mation and how investors may make deductions from observing others’
trading as to what information they have. Alternatively, they may make
deductions from observing market prices as to how other investors
value a security. This is not the place to review this literature, but in
some models investors adjust their beliefs with the aid of information
they obtain from observing other investors.
If everyone has different information and the information is com-
bined in the way discussed in this chapter, it was shown that the inves-
tor who purchases a security will be disappointed (i.e., the return will be
less than expected). If one plays with Markowitz optimization routines,
one will find that putting in expected returns for one security that are
appreciably higher than required for it to be included in the portfolio
will result in that security having a weight that is a multiple of that secu-
rity’s weight in the market portfolio. As a rule of thumb, the further
your estimate is from the average estimate, the more likely you are to
suffer from the winner’s curse effect. One common solution is to adjust
the estimates (or the estimates from a staff member) to correct for them.
When an adequate record is available, a regression of estimated errors
(for securities actually purchased) on the estimate’s deviation from the
average might be used to improve estimates.

In Chapter 5, the companion chapter to this one, I argued that mar-
kets were bounded such that there were few (possibly no) undervalued
securities that could be identified from publicly available information
while there could be overvalued securities. The optimal strategy is to do
analysis to avoid the overvalued securities. However, as discussed
above, if in the course of the analysis one convinces oneself that a secu-
rity is grossly underpriced, one is likely to be wrong. Since the underval-
ued securities are likely to be only a little undervalued, the optimal
percentage in a portfolio is likely to be low. A tight limit on the amount
of any one security held in a portfolio is a logical implication of the
above analysis. High diversification is a result.
Theoretical Objections
Since my original “Risk, Uncertainty, and Divergence of Opinion” paper
was published in 1977, there has been considerable discussion. The origi-
nal paper and the exposition above provide a simple diagrammatic exposi-
tion of the effects of divergence of opinion with short selling restricted.
6-Miller-Implications Page 130 Thursday, August 5, 2004 11:11 AM
Implications of Short Selling and Divergence of Opinion for Investment Strategy 131
After I published the argument, Figlewski
17
and Jarrow
18
provided a
more mathematical treatment. Jarrow also correctly points out there
could be investor disagreement about the risk properties of securities
that exactly counterbalanced the effects of the investor disagreements
about expected returns, leaving each investor’s demands for securities
unchanged.
Working in a general equilibrium framework, Jarrow also gives a
counter example in which with multiple stocks subject to short sales

Steve Figlewski, “The Informational Effects of Restrictions on Short Sales: Some
Empirical Evidence,” Journal of Financial and Quantitative Analysis (1981), pp.
463–476.
18
Robert Jarrow, “Heterogeneous Expectations, Restrictions on Short Sales, and
Equilibrium Asset Prices,” Journal of Finance (December 1980), pp. 1105–1113.
19
Joseph Williams, “Capital Asset Prices with Heterogeneous Beliefs,” Journal of Fi-
nancial Economics (November 1977) pp. 219–239.
6-Miller-Implications Page 131 Thursday, August 5, 2004 11:11 AM
132 THEORY AND EVIDENCE ON SHORT SELLING
In a steady state they end up agreeing on the covariance matrix, but still
disagree about the mean returns. Intuitively, as time passes more and
more evidence accumulates about covariances and eventually the inves-
tors come to agree. As Jarrow puts it, “they agree about the expected
return required to hold the asset in their portfolios.” In this circumstance
Jarrow’s conclusion regarding the effects of restricting short selling are,
“If they agree upon the covariance matrix of next period’s asset prices,
relative risky asset prices will always rise.”
With new information constantly arriving, investors clearly do not
agree completely on the covariance matrix of all securities (and of
course most investors do not even use explicit covariance matrices in
decision making). However, their opinions about the risk properties of
securities probably differ less than their opinions about the securities’
expected returns. Most investors try to limit the effect of large covari-
ances among pairs of securities by trying to diversify across industries,
and often by diversifying across categories of stocks strongly exposed to
certain factors (growth versus value, small versus large, cyclical versus
defensive, etc.). In practice, investors are likely to disagree more about
expected returns than about questions such as the firm’s industry, or

returns. Investors with a sufficiently high estimate of beta, but a conven-
20
See Edwin J. Elton and Martin Gruber, Modern Portfolio Theory and Investment
Analysis (New York: John Wiley & Sons, 1995) for a description of many ways of
using historical data. Better results are often obtained by multifactor models or av-
eraging data than by simply computing a covariance matrix from historical data.
6-Miller-Implications Page 132 Thursday, August 5, 2004 11:11 AM
Implications of Short Selling and Divergence of Opinion for Investment Strategy 133
tional estimate of the expected return would often wish to short the stocks
in the absence of short sale constraints. The short would provide a hedge
against market declines, permitting a greater investment in other risky
securities without increasing total portfolio risk. With short sale con-
straints, those who have low estimates of beta buy more of that stock,
while selling is limited by the difficulties in reducing the weight below zero.
Varian, in “Divergence of Opinion in Complete Markets: A Note”
(the phrase complete markets implies no obstacles to short selling) con-
cluded that for plausible parameters of risk aversion that dispersion of
opinion should lower asset prices.
21
As the reference to complete mar-
kets in the title shows, he is explicitly assuming full ability to make
short sales (or the equivalent). As he pointed elsewhere, the effect on
price of changing the divergence of opinion should depend on the curva-
ture of the demand curve.
22
It is useful to consider changing divergence of opinion in the context
of Markowitz optimization. Imagine a large number of identical inves-
tors that have initial identical beliefs and risk preferences. Consider a
security that has a higher return and a higher risk than the rest of the
portfolio. For each of these investors the weight of every security has

maintained if the price drops, raising the return and hence causing all
investors to have slightly higher return expectations. Thus, without
short selling restrictions, we might expect increased dispersion of opin-
ion to sometimes result in lower prices and higher returns.
One can imagine a security where the dispersion of return estimates
was small enough so that no one wished to short it. The more pessimis-
tic investors simply underweight it in their portfolios. Thus, if the short
constraint binds on sufficiently few investors, changing the divergence
of opinion could lower the price rather than raise it.
However, since the above effect depends on the curvature in the
demand curve (which in turn results from the covariance of a security
with a portfolio increasing as the weight of that security in the portfolio
increases), I would expect it to be relatively minor compared with the
effect of preventing investors from reducing the holdings below zero.
One would expect this effect to be strongest for the securities which
typically compose a large proportion of a portfolio. If one is thinking of
investors as being basically similar, the large stocks that have a high
weight in the “market portfolio” must typically have a high weight in
individual portfolios also. It is for such stocks that the price lowering
effect of increasing divergence of opinion would be most powerful.
EMPIRICAL TESTS
There are two obvious ways to test the divergence of opinion theory
prediction that increased divergence of opinion lower returns in the
presence of restrictions on short selling. One is to see if constraints on
short selling affect returns. The other is to see if high divergence of
opinion stocks have lower returns.
Evidence on Short Sales Constraints
The level of short interest can be interpreted in several ways. If short
sales are observed, some short selling is possible. Since the major reason
for short sales is because one expects the stock to underperform, the

For hard to borrow stocks, the rates were sometimes negative (i.e., the
borrower of the stock not only got no interest on the proceeds of the secu-
rity deposit, he or she paid an additional sum to the lender of the stock).
They found that the higher the fee paid for borrowing stocks, the lower
the return on the stocks. In other words the short sellers seemed able to
identify stocks that would underperform the market. It appears that when
there was little interest in shorting stocks, the demand could be met by
brokers lending out the shares already in their possession. However, when
the demand for shares to be shorted grew, brokers were forced to go to
the loan crowd to find shares to borrow. Noticing there was interest in
borrowing stocks, the Wall Street Journal then added coverage of that
stock to its list of stocks whose borrowing fees were reported. This story
suggests those stocks that were added to the list were those with a high
interest in being borrowed (which was confirmed by observing that the
fees for these stocks were usually higher when they were added to the
list). These newly listed stocks were found to underperform the market
after listing by 1–2% per month. Even after paying the fees, shorting
23
Charles M. Jones and Owen A. Lamont, “Short-Sale Constraints and Stock Re-
turns,” Journal of Financial Economics (2002), pp. 207–239. See also Chapter 7 in
this book.
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136 THEORY AND EVIDENCE ON SHORT SELLING
these stocks would have been profitable. Because addition to the short
borrowing list was observable and the fees charged were reported, the
possibility of earning abnormal returns is inconsistent with the efficient
markets model. The correlation of high short costs and low returns is pre-
dicted by the divergence of opinion, restricted short selling model.
Early studies showed an inconsistent relationship between short
interests and future returns. Desai et al. suggest that this was because of

opinion effect is probably greatest on the smaller stocks, Figlewski’s use
of S&P stocks and practice of value-weighting within portfolios proba-
bly reduced the effects. Likewise, his use of six months of data to iden-
tify the short interest and a 12-month holding period probably reduced
24
Heman Desai, K. Ramesh, S. Ramu Thiagarajan, and Bala V. Balachandran, “An
Investigation of the Informational Role of Short Interest in the NASDAQ Market,”
Journal of Finance (October 2002), pp. 2263–2287.
25
Averil Brent, Dale Morese, and E. Kay Stice, “Short Interest: Explanation and
Tests,” Journal of Financial and Quantitative Analysis (June 1990), pp. 273–289.
26
Figlewski, “The Informational Effects of Restrictions on Short Sales: Some Empir-
ical Evidence.”
6-Miller-Implications Page 136 Thursday, August 5, 2004 11:11 AM