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Unformatted text preview: THE JOURNAL OF FINANCE • VOL. LVII, NO. 5 • OCTOBER 2002 An Investigation of the Informational Role
of Short Interest in the Nasdaq Market
HEMANG DESAI, K. RAMESH, S. RAMU THIAGARAJAN,
and BALA V. BALACHANDRAN*
ABSTRACT
This paper examines the relationship between the level of short interest and stock
returns in the Nasdaq market from June 1988 through December 1994. We find
that heavily shorted firms experience significant negative abnormal returns ranging from 0.76 to 1.13 percent per month after controlling for the market, size,
booktomarket, and momentum factors. These negative returns increase with the
level of short interest, indicating that a higher level of short interest is a stronger
bearish signal. We find that heavily shorted firms are more likely to be delisted
compared to their size, booktomarket, and momentum matched control firms. WE INVESTIGATE THE RELATIONSHIP between the level of short interest and the
stock returns in Nasdaq firms. Using monthly short interest data for the
universe of Nasdaq firms from June 1988 to December 1994, we find that
firms with a high level of short interest experience negative and significant
abnormal returns when they are heavily shorted. Using a calendartime portfolio approach, we regress monthly portfolio excess returns of stocks that
had at least 2.5 percent short interest ~number of shares sold short as a
percentage of the shares outstanding! in the previous month on the three
Fama and French ~1993! risk factors and a fourth momentum factor ~Carhart ~1997!!. The regression yields negative and significant abnormal returns
of 0.76 percent per month during our sample period. The magnitude of the
negative abnormal returns increases with the level of short interest. These
results indicate that a high level of short interest is a bearish signal.
* Hemang Desai is at the Cox School of Business, Southern Methodist University. K. Ramesh
is at Analysis Group0Economics, Boston, MA. S. Ramu Thiagarajan is at Mellon Capital Management, San Francisco, CA, and Bala V. Balachandran is at Northwestern University. We are
especially grateful to Mike Vetsuypens for comments and suggestions that have led to significant improvements in this paper. We acknowledge helpful comments of an anonymous referee;
Linda Bamber; Venkat Eleswarapu; Larry Glosten; Richard Green ~the editor!; Lex Huberts;
Ravi Jagannathan; Prem Jain; S.P. Kothari; Srini Krishnamurthy; James Livingston; Dave
Mauer; Tim McCormick; Mitch Petersen; Srini Rangan; Jay Shanken; Wayne Shaw; Avanidhar
Subrahmanyam; Rex Thompson; Sheridan Titman; Kumar Venkatraman; Beverly Walther; Jerry
Warner; Larry Weiss; William Wink; and the workshop participants at the University of Georgia, INSEAD, Mellon Capital Management, the University of Rochester, and the State University of New York ~Buffalo!. We thank the Nasdaq Stock Market for providing the data used in
this study and Kenneth French and Mark Carhart for providing the factor returns. Any errors
or omissions are the responsibility of the authors. 2263 2264 The Journal of Finance Aitken et al. ~1998! show that information in short interest is incorporated
quickly into prices of Australian stocks. While the information on short positions is available in real time for stocks traded on the Australian Stock
Exchange ~Aitken et al.!, only aggregate short positions are available on a
monthly basis for stocks traded in the United States. Using data available
on a realtime basis, Aitken et al. focused on intraday price reaction to information on short positions.1 In contrast, our study focuses on the longerterm price performance of heavily shorted firms in the Nasdaq market.
Three different perspectives have been offered on the expected relationship between short interest and stock returns. The first perspective, advanced by Diamond and Verrecchia ~~1987!; hereafter DV!, is that short
interest should bear a negative relation with stock returns. They suggest
that since short selling is costly, short sales by liquidity traders are less
likely. 2 Consequently, if informed traders are more likely to engage in short
selling, high short interest conveys adverse information, implying a negative relationship between short interest and stock returns.
An alternative perspective, popular on Wall Street, is that a high level of
short interest is a bullish signal because it represents latent demand, which
will transform eventually into actual purchase of the shares to cover the
short position. Consider the following statement from an article in Barron’s:
“A commonly held idea is that the larger the short interest, the more likely
that a stock will go up. That’s because shorts eventually will buy back the
stock, thereby putting upward pressure on its price” ~Epstein ~1995!!. Incidents of runup in the stock price of several companies have been attributed
to this explanation by the media. For example, Business Week ~Byrnes ~1995!!
attributes the run up in L.L. Knickerbocker ’s stock from $4 to $46 in less
than six weeks to this demand–supply perspective. The article states “by
July 14, short positions were 31,440. As the stock rose, shorts had to pay for
the stock to cover their bets. With only 800,000 shares available, the price
climbed.” ~p. 44!.
The third perspective is that short selling may be unrelated to stock returns if it is motivated by hedging strategies, arbitrage transactions, and
taxrelated reasons ~Brent, Morse, and Stice ~1990!!. For example, traders
may take short positions to implement techniques such as shorting against
the box. To remove any pricerelated uncertainty, a trader may sell short
securities ~usually for tax reasons! on which the trader already has a long
position. Such short positions may not trigger any future demand for the
shares nor are they motivated by short sellers’ negative information. 1
Using intraday data, they find that the price impact of short trades is negative ~ 0.20 percent! and that the information in the short trade is impounded into prices quickly ~15 to
20 minutes!.
2
Examples of costly constraints on short selling include the uptick rule, legal constraints on
short selling by certain institutional investors, and restrictions on immediate collection of proceeds from short sales. See Asquith and Meulbroek ~1995! for a detailed explanation of costs
associated with short selling. Short Interest and Stock Returns 2265 With the exception of Asquith and Meulbroek ~~1995!; hereafter AM!, prior
research on short interest has failed to document a strong and consistent
relationship between short interest and abnormal stock returns. For example, see Figlewski ~1981!, Conrad ~1986!, Vu and Caster ~1987!, Brent et al.
~1990!, Bhattacharya and Gallinger ~1991!, Senchack and Starks ~1993!, Choie
and Hwang ~1994!, and Woolridge and Dickinson ~1994!. This is likely due to
the use of data reported by the media or the use of small random samples.
The data reported by the media are incomplete, as they impose arbitrary
restrictions on the level of short interest or the change in short interest for
a firm to be included in their publications.3 These restrictions are likely to
exclude firms with large and significant short positions relative to the shares
outstanding. Also, since a typical firm has short interest of less than one
percent of the shares outstanding and since most firms have little or no
short interest, samples chosen on a random basis lack the statistical power
to detect a significant association between short interest and stock returns.
By examining the entire population of short interest in the Nasdaq market,
we are able to obtain a large number of firms with material short interest
positions.
Using a large sample of NYSE0AMEX firms, Asquith and Meulbroek ~1995!
document a strong negative relationship between short interest and subsequent abnormal returns. We extend AM’s study to Nasdaq firms. Moreover, recent advances in measurement of stock returns over long horizons
have suggested improved methods for the measurement of abnormal returns
over long horizons. Our methodology for measuring abnormal returns incorporates these insights.
Our empirical tests strongly support the view that short interest is a bearish signal and that the informativeness of this signal is increasing in the
magnitude of short interest. Specifically, we find that the abnormal return
for firms with short interest of at least 2.5 percent is negative 76 basis
points per month over our sample period. The corresponding abnormal return for firms with short interest of at least 10 percent is negative 113 basis
points per month. The negative abnormal returns are not clustered in certain industries, nor are they clustered in calendar time. The negative abnormal returns documented are robust to alternative classifications of heavily
shorted firms and to the use of alternative benchmarks for measuring abnormal returns. We also examine the survival status of firms with high short
interest. The results indicate that heavily shorted firms are more likely to
be liquidated or delisted in the 36 months after being heavily shorted than
their size, booktomarket, and momentummatched control firms.
The rest of the paper is organized as follows. Section I describes the data
and reports summary statistics for the sample. Empirical analysis of the
3
For example, the Wall Street Journal does not include a firm unless the level of short
interest is at least 225,000 shares or the short interest changes by at least 100,000 shares.
Moreover, as Senchack and Starks ~1993! report, the criteria for inclusion of firms in media
publications have varied over time. 2266 The Journal of Finance association between short interest and stock returns is presented in Section II. Results of the robustness analysis are reported in Section III. Section IV presents the analysis on the survival status of heavily shorted firms.
Section V concludes. I. Descriptive Information on Short Interest
A. Sample Selection
We obtain monthly short interest data directly from the Nasdaq for the
period from June 1988 to December 1994.4 The market makers report the
short positions as of the 15th of each month to the Nasdaq within three to
four days after the 15th of the month. The Nasdaq, in turn, aggregates the
short interest for each security.5 It then releases the aggregate short interest data and the data are carried by, among others, The Wall Street Journal,
Barron’s, and The New York Times.
We obtain data on stock returns, firm size, trading volume, share turnover, and delisting status from the CRSP files. To identify firms with a
high level of short interest, we implement the following procedure.6 As in
AM, a firm is considered “heavily ” shorted if the number of shares sold
short is at least 2.5 percent of the shares outstanding at the end of the
month.7 We call this the 2.5 percent sample. Because the 2.5 percent cutoff
is arbitrary, we also analyze samples using cutoffs of 5 percent, 7.5 percent, and 10 percent.
We denote EN as the month in which a firm first attains a 2.5 percent
short interest position in our sample period. A firm remains in this sample
as long as its short interest remains at or above the 2.5 percent threshold at
the end of each month. If a firm’s short interest falls below the 2.5 percent
threshold it exits the short interest sample and the month preceding the
month of exit is designated as EX. Thus, EX is the last month for which the
firm’s short interest is at or above the 2.5 percent threshold. Each such
incidence in our sample firms gives us one observation. For example, assume that ABC Corp. has 1,000 shares outstanding. Suppose that at the end
of January 1994, its short interest first reaches 25 shares. Then, January
4
The Nasdaq does not have data for February 1990 and July 1990. For these two months, we
assume that the level of short interest in these months is the same as that in the immediately
preceding month. The tenor of our results is not affected when these two months are excluded
from our analysis.
5
Because of its structure of multiple market makers, the Nasdaq takes somewhat longer
than the NYSE0AMEX to compile the information.
6
We only include ordinary common shares in the analysis. Thus, ADRs, REITS, and closedend funds are excluded from the analysis.
7
The mean ~median! level of short interest for the entire universe of Nasdaq firms over our
sample period is 0.85 percent ~0.11 percent!. The 90th percentile of short interest for the universe of Nasdaq firms over our sample period is 2.09 percent. Thus, our “heavily” shorted
sample consists of firms with short interest in the top decile. Short Interest and Stock Returns 2267 1994 would be designated the EN month for ABC Corp. Having remained at
or above 25 shares in February, March, and April, suppose the short interest
drops to 10 shares in May 1994. Then, April 1994 would be designated the
EX month. Thus, ABC Corp. forms one observation or one event with EN of
January 1994 and EX of April 1994.
To implement the calendartime portfolio approach, we require the firms
in the portfolio to meet the threshold level of short interest in the preceding month. Thus, ABC Corp. would be included in the portfolio for the
months February, March, April, and May. If the short interest for ABC
Corp. were to reach 25 shares again, say in October 1994, then ABC Corp
would reenter the sample in October 1994, and would be considered a
separate observation.
In the 2.5 percent sample, we have 2,726 observations compared to 1,390,
860, and 577 observations in the 5 percent, the 7.5 percent, and the 10 percent samples, respectively. As a comparison, the number of observations in
AM in each of the four comparable subsamples over the period from 1976 to
1993 are 1,438, 734, 431, and 260, for the 2.5 percent, the 5 percent, the
7.5 percent, and the 10 percent short interest samples, respectively ~Table 2
in AM!.
B. Summary Statistics
The distribution statistics reported in Panel A of Table I indicate that the
level of short interest has increased steadily on the Nasdaq market over our
sample period. In particular, the mean ~median! short interest for the universe of Nasdaq stocks has increased from 0.51 percent ~0.08 percent! in
1988 to 1.14 percent ~0.16 percent! in 1994. AM document a similar pattern
of increasing short interest on the NYSE0AMEX. Panel B of Table I reports
the distribution of the number of observations in each of the four subsamples of short interest. Consistent with a pattern of increasing short interest
over time, the number of heavily shorted firms is also intertemporally
increasing.
Table II provides descriptive statistics on the sample firms. Since the
descriptive statistics are generally monotonic in the level of short interest,
for the sake of brevity, we report statistics only for the 2.5 percent and the
10 percent samples in Panels A and B, respectively. In the 2.5 percent
sample, the average ~median! number of consecutive months for which the
stocks are heavily shorted is 7.94 ~3.00! months. The fact that the short
positions are held for several months suggests that, at least from the perspective of the short sellers, any negative information they have is not
immediately impounded in the stock prices. The mean ~median! market
value of equity one month prior to entry ~EN 1! in the sample is $222.32
~$83.65! million. This corresponds to mean ~median! size decile of 7.29
~8.00! relative to the universe of Nasdaq firms, where decile one corresponds to the smallest firms. Given the concerns that the short sellers
have about a short squeeze, we expect them to have a preference for more 2268 The Journal of Finance
Table I Distribution of Short Interest over the Sample Period
The table reports statistics pertaining to the level and the distribution of short interest for the
universe of Nasdaq firms. Data are available from June 1988 to December 1994, except for
February 1990 and July 1990. For these two months, the firms are assumed to have the same
level of short interest as the previous month. Short interest is defined as a ratio of shares
shorted to the total number of shares outstanding at the end of each month. A firm enters
the short interest sample when its short interest reaches a certain threshold ~2.5, 5, 7.5, and
10 percent! in a given month and leaves the sample when its short interest level falls below the
threshold. Panel A reports the level of short interest for the universe of Nasdaq firms by year.
Panel B reports the distribution of number of observations in each of the four subsamples ~2.5,
5, 7.5, and 10 percent! by year.
Panel A: Short Interest for the Nasdaq Universe by Year Year
1988
1989
1990
1991
1992
1993
1994 Mean
~%! Median
~%! 25th Percentile
~%! 75th Percentile
~%! 0.51
0.59
0.81
0.84
0.87
1.03
1.14 0.08
0.09
0.10
0.11
0.13
0.15
0.16 0.02
0.03
0.03
0.03
0.03
0.04
0.04 0.25
0.29
0.42
0.49
0.58
0.71
0.79 Panel B: Number of Observations in each Short Interest Subsample by Year
Year
1988
1989
1990
1991
1992
1993
1994 2.5%
Sample 5%
Sample 7.5%
Sample 10%
Sample 262
251
339
340
416
550
568 120
140
189
172
206
271
292 66
91
121
104
121
167
190 40
61
70
80
83
98
145 liquid stocks.8 Consistent with this conjecture, we find that the heavily
shorted firms are highly liquid. In particular, the mean ~median! monthly
dollar trading volume is $54.95 ~$13.85! million in the month prior to entering the 2.5 percent sample. This corresponds to a mean ~median! decile
8
Generally, short sellers borrow the stock from an institutional investor, a brokerage house,
or a dealer. However, this borrowed stock ~loan! must be repaid on demand. A short squeeze,
thus, occurs when the lender of the borrowed shares wants to sell the stock. If the short seller
is unable to find another lender, he0she has to repurchase the shares in the open market to
fulfill the obligation to repay the loan ~shares!. Thus, short sellers prefer liquid stocks since it
is easier to find alternative lenders in case of a short squeeze. An article in Business Week
~Weiss ~1995!! quotes Bob Bandera of West Lake Capital, “I tried and simply could not borrow
@Netscape# stock and couldn’t take a short position.” ~p. 90!. Short Interest and Stock Returns 2269 Table II Summary Statistics for the Short Interest Sample
The table reports several summary statistics for the sample firms. Data are available from June 1988
to December 1994, except for February 1990 and July 1990. For these two months, the firms are
assumed to have the same level of short interest as the previous month. Short interest is defined as
a ratio of shares shorted to the total number of shares outstanding at the end of each month. A firm
enters the short interest sample when its short interest reaches a certain threshold ~2.5, 5, 7.5, and
10 percent! in a given month and leaves the sample when its short interest level falls below the
threshold. The market value of equity, monthly dollar trading volume, and monthly turnover are all
measured in month 1 relative to a firm’s entry into the short interest sample and are all obtained
from the CRSP files. Monthly turnover is defined as the number of shares traded in a month as a
percentage of shares outstanding. The booktomarket ratio and the cashf lowtoprice ratio are computed using variables from COMPUSTAT. These ratios are also computed in month 1. Book value of
equity is annual item #60 and cash f low ~operating income before depreciation and amortization! is
annual item #13 from the COMPUSTAT files. All of the decile rankings are assigned in month 1 and
are relative to the universe of Nasdaq firms. To avoid the lookahead bias for the booktomarket ratio
and the cashf lowtoprice ratio, we use the latest fiscal yearend values for book value of equity and
cash f low only if month 1 is at least four months after the firms’ fiscal yearend; if not, we use the
values from the previous fiscal yearend. Decile 1 corresponds to the smallest value. Fewer observations result from missing values in month 1 or if the firm is not on COMPUSTAT. In addition, we
exclude firms with negative values of book value of equity or cash f low. Panel A reports the statistics
for the 2.5 percent short interest sample and Panel B reports statistics for the 10 percent short
interest sample. Variable No. of
Obs. Mean Median 25th
Percentile 75th
Percentile Panel A: Summary Statistics for the 2.5% Short Interest Sample
Number of months in the
short interest sample
Market value of equity
~in million dollars!
Size decile rank
Monthly dollar volume
~in million dollars!
Monthly dollar volume decile rank
Monthly turnover ~%!
Monthly turnover decile rank
Booktomarket ratio
Booktomarket decile rank
Cashf lowtoprice ratio
Cashf lowtoprice decile rank 2,726 7.94 3.00 1.00 10.00 2,638 222.32 83.65 27.65 214.01 2,638
2,636 7.29
54.95 8.00
13.85 6.00
3.76 9.00
44.80 2,636
2,636
2,636
2,034
2,034
1,473
1,473 8.43
26.76
8.75
0.55
3.99
0.22
4.27 9.00
17.02
9.00
0.36
3.00
0.11
4.00 8.00
9.36
8.00
0.20
2.00
0.06
2.00 10.00
29.71
10.00
0.62
6.00
0.20
6.00 Panel B: Summary Statistics for the 10% Short Interest Sample
Number of months in the
short interest sample
Market value of equity
~in million dollars!
Size decile rank
Monthly dollar volume
~in million dollars!
Monthly dollar volume decile rank
Monthly turnover ~%!
Monthly turnover decile rank
Booktomarket ratio
Booktomarket decile rank
Cashf lowtoprice ratio
Cashf lowtoprice decile rank 577 6.73 4.00 1.00 10.00 561 235.60 137.33 48.72 278.94 561
542 8.07
93.01 9.00
36.93 7.00
13.14 10.00
100.00 561
561
561
424
424
329
329 9.19
36.54
9.42
0.59
3.70
0.22
3.96 10.00
28.85
10.00
0.32
2.00
0.10
2.00 9.00
17.07
9.00
0.18
3.00
0.06
3.00 10.00
45.71
10.00
0.55
5.00
0.18
6.00 2270 The Journal of Finance rank of 8.43 ~9.00!, relative to the universe of Nasdaq stocks. Mean ~median! share turnover ~shares traded as a percentage of shares outstanding!
one month prior to entering the short interest sample is 26.76 percent
~17.02 percent!. This corresponds to mean ~median! decile rank of 8.75
~9.00! relative to the universe of Nasdaq stocks.
An examination of the fundamentals suggests that the heavily shorted
firms have low values of fundamentals relative to price. The mean ~median!
booktomarket ratio of the firms in the 2.5 percent sample is 0.55 ~0.36! in
month EN
1 with a cashf lowtoprice ratio of 0.22 ~0.11!.9 This corresponds to mean ~median! decile rank of 3.99 ~3.00! relative to the universe of
Nasdaq firms. The corresponding decile rank for the cashf lowtoprice ratio
is 4.27 ~4.00!. These findings are consistent with results in Dechow et al.
~2001!, who document that firms with high short interest on the NYSE0
AMEX have low values of fundamentals relative to market value.
Panel B of Table II reports summary statistics for the 10 percent sample.
The statistics indicate that firms in the 10 percent sample are more liquid
relative to the firms in the 2.5 percent sample. This finding is consistent
with results in Kadiyala and Vetsuypens ~2002!. Using a sample of stock
splits, they document a positive relationship between improved liquidity following a stock split and the level of short interest. II. Association between Short Interest and Stock Returns
A. Methodology
Several recent papers have proposed methods for measuring longhorizon
abnormal stock returns. Barber and Lyon ~1997! and Kothari and Warner
~1997! show that abnormal returns measured over long horizons are sensitive to the benchmarks used. Barber and Lyon show that the use of portfolio
returns as a benchmark ~e.g., a CRSP index or size decile portfolios! results
in holding period abnormal returns that are biased downwards, leading to
misspecified statistics. They recommend using a matching firm methodology. However, one potential limitation of the matching firm approach is the
assumption that the buyandhold or holding period returns are crosssectionally independent.
Mitchell and Stafford ~2000! advocate the use of time series regressions
and a calendartime portfolio approach to measure performance over long
horizons to address the problem of crosssectional dependence. In this approach, an event portfolio is formed each month to include all firms that
experience an event in the previous month ~or previous n months, depending
on the horizon over which the performance is evaluated!. An important advantage of this approach is that the variance of the event portfolios formed
in this manner automatically takes into account the crosssectional correlation among the individual securities that comprise the portfolio. Further9 The booktomarket ratio and the cashf lowtoprice ratio are updated each month. Short Interest and Stock Returns 2271 more, Mitchell and Stafford also show that the calendartime portfolio approach
yields the most conservative results among the various methods to evaluate
performance over long horizons. Finally, the calendartime event portfolio
approach represents an implementable investment strategy. Thus, we primarily use the calendartime portfolio approach in our analysis, although
selected results from the matching firm methodology are reported to test
the robustness of our findings.
A.1. Calendartime Portfolio Approach
At the beginning of each month from July 1988 to January 1995, we form
equalweighted portfolios of firms that had at least 2.5 percent ~or 5 percent,
7.5 percent, and 10 percent, as the case may be! short interest in the previous month. The portfolios are rebalanced monthly to drop all firms that
did not meet the threshold of 2.5 percent short interest in the previous month
and add firms that attained 2.5 percent short interest in the previous month.
Thus, a firm enters the portfolio in month EN 1 and remains in the portfolio through month EX 1. As a result, we have monthly portfolio returns
from July 1988 to January 1995. We then regress the monthly portfolio
excess returns ~excess returns are obtained by subtracting the yield on onemonth Tbills from raw returns! on the three Fama and French ~1993! factors as well as a fourth momentum factor suggested by Carhart ~1997!. The
portfolio excess returns are regressed on the four factors as in equation ~1!:
RPRFt a0 a 1 RMRFt a 2 SMBt a 3 HML t a 4 PR 1YR t et , ~1! where RPRFt is the monthly portfolio return for the short interest sample
minus the onemonth riskfree rate, RMRF is the market factor, SMB is the
size factor, HML is the booktomarket factor, and PR1YR is the momentum
factor. These four factors and their construction are described in detail in
Fama and French and Carhart.
B. Stock Market Performance
Table III reports the OLS estimate of equation ~1! for the 2.5 percent, the
5 percent, the 7.5 percent, and the 10 percent short interest samples. The
coefficient of interest is the intercept, a 0 , in equation ~1!. The intercept for
the 2.5 percent sample is 0.76 percent ~ tstatistic of 3.34!, suggesting
that over the period from July 1988 to January 1995, the sample firms experienced negative abnormal return of 0.76 percent per month. This result
indicates that a high level of short interest conveys negative information.
The results for the 5 percent, the 7.5 percent and the 10 percent samples
indicate that the abnormal returns become increasingly negative with increasing levels of short interest. For example, the monthly abnormal returns
for the 5 percent, the 7.5 percent and the 10 percent short interest samples 2272 The Journal of Finance
Table III Calendartime Abnormal Returns for the Sample
of Heavily Shorted Firms: Firms Are in the Portfolio
from Month EN + 1 to EX + 1
This table reports the coefficients from a timeseries regression of excess monthly portfolio
returns ~in excess of Tbill rate! on the three factors suggested by Fama and French ~1993! and
the fourth suggested by Carhart ~1997!. The following regression is estimated:
RPRFt a0 a 1 RMRFt a 2 SMBt a 3 HML t a 4 PR 1YR t et , where RPRFt is the portfolio excess return for the sample firms in month t and RMRFt ~market
factor! is the excess return of the valueweighted portfolio of NYSE0AMEX and Nasdaq firms.
The size factor ~ SMBt !, the booktomarket factor ~ HML t !, and the momentum factor ~PR1YR!
are described in Carhart. The portfolio returns for the short interest sample are in calendar
time. Data are available from June 1988 to December 1994, except for February 1990 and July
1990. For these two months, the firms are assumed to have the same level of short interest as
the previous month. The 2.5 percent short interest sample consists of those firms that had
short interest of at least 2.5 percent of the shares outstanding at the end of a given month. The
5 percent, 7.5 percent, and 10 percent short interest samples are defined similarly. For every
month from July 1988 to January 1995, the portfolio is formed using all the firms that had at
least a 2.5 percent short interest ~5 percent, 7.5 percent, and 10 percent as the case may be! at
the end of the previous month. Each month new firms get added when they attain the threshold
short interest level in the previous month and some firms get dropped when their short interest
drops below the threshold in the previous month. Thus, a firm enters the portfolio in month
EN
1 and remains in the portfolio through month EX
1. The tstatistic is reported in
parentheses.
Short Interest
Sample Adj. R 2
~%! Intercept RMRF SMB HML PR1YR 2.50% 0.76%
~ 3.34! 1.25
~18.85! 1.25
~12.19! 0.14
~ 1.25! 0.51
~ 5.57! 91.09 5% 0.85%
~ 2.84! 1.35
~15.46! 1.22
~9.02! 0.14
~ 0.95! 0.55
~ 4.62! 86.49 7.50% 0.90%
~ 2.44! 1.40
~13.04! 1.25
~7.50! 0.03
~ 0.18! 0.47
~ 3.17! 80.97 10% 1.13%
~ 3.08! 1.36
~12.70! 1.38
~8.33! 0.17
~ 0.94! 0.35
~ 2.37! 81.59 are 0.85 percent ~ tstatistic of 2.84!, 0.90 percent ~ tstatistic of 2.44!,
and 1.13 percent ~ tstatistic of 3.08!, respectively. This result implies that
a higher level of short interest conveys more negative information.
In the above approach, each firm is in the portfolio from month EN 1 to
EX
1. The statistics in Table II show that the mean ~median! number of
months for which firms stay in the portfolio is 7.94 ~3.00! for the 2.5 percent
sample. Thus, different firms are held in the portfolio for different lengths of
time depending upon how long they remain heavily shorted. In an alternative approach, we keep each firm in the portfolio for 12 months ~from EN 1
to EN 12! after it first enters the portfolio regardless of the level of short Short Interest and Stock Returns 2273 Table IV Calendartime Abnormal Returns for the Sample
of Heavily Shorted Firms: Firms in the Portfolio
from Month EN + 1 to EN + 12
This table reports the coefficients from a timeseries regression of excess monthly portfolio
returns ~in excess of Tbill rate! on the three factors suggested by Fama and French ~1993! and
the fourth suggested by Carhart ~1997!. The following regression is estimated:
RPRFt a0 a 1 RMRFt a 2 SMBt a 3 HML t a 4 PR 1YR t et , where RPRFt is the portfolio excess return for the sample firms in month t and RMRFt ~market
factor! is the excess return of the valueweighted portfolio of NYSE0AMEX and Nasdaq firms.
The size factor ~ SMBt !, the booktomarket factor ~ HML t !, and the momentum factor ~PR1YR!
are described in Carhart. The portfolio returns for the short interest sample are in calendar
time. Data are available from June 1988 to December 1994, except for February 1990 and July
1990. For these two months, the firms are assumed to have the same level of short interest as
the previous month. The 2.5 percent short interest sample consists of those firms that had
short interest of at least 2.5 percent of the shares outstanding at the end of a given month. The
5 percent, 7.5 percent, and 10 percent short interest samples are defined similarly. A firm
enters the portfolio if its short interest in the previous month reaches the 2.5 percent threshold
for the first time ~or 5 percent, 7.5 percent, or 10 percent, as the case may be!. The firm remains
in the portfolio for 12 consecutive months. Thus, each firm enters the portfolio in month EN 1
and remains in the portfolio through month EN 12. Thus, we have monthly portfolio returns
from July 1988 to December 1995. The tstatistic is reported in parentheses.
Short Interest
Sample Adj. R 2
~%! Intercept RMRF SMB HML PR1YR 2.50% 0.84%
~ 3.65! 1.18
~17.22! 1.13
~10.78! 0.16
~ 1.41! 0.34
~ 3.67! 87.64 5% 0.95%
~ 3.50! 1.21
~15.01! 1.20
~9.75! 0.09
~ 0.69! 0.30
~ 2.75! 84.20 7.50% 0.92%
~ 3.09! 1.26
~14.35! 1.19
~8.79! 0.14
~ 0.97! 0.31
~ 2.56! 82.53 10% 1.09%
~ 2.84! 1.34
~11.70! 1.17
~6.69! 0.11
~ 0.61! 0.40
~ 2.54! 75.08 interest during the next 11 months. Thus, under this approach, we have
monthly portfolio returns from July 1988 to December 1995. The results
from this alternative approach reported in Table IV show that the intercept
for the 2.5 percent sample is 0.84 percent ~ tstatistic of 3.65!. Thus, a
strategy of holding heavily shorted firms for 12 months after they first attain the threshold level of short interest yields negative abnormal return of
0.84 percent per month. The negative abnormal returns for the 5 percent,
the 7.5 percent, and the 10 percent samples are 0.95 percent ~ tstatistic of
3.50!, 0.92 percent ~ tstatistic of 3.09!, and 1.09 percent ~ tstatistic of
2.84! per month, respectively.
The results presented above are consistent with the negative relationship
between short interest and abnormal returns documented in AM. The results in AM show that the sizeandstandarddeviationadjusted return for 2274 The Journal of Finance the 10 percent sample over the period for which a firm remains heavily
shorted ~referred to as period zero in AM! is 16.1 percent. The mean ~median! number of months for which firms remain heavily shorted in their
10 percent sample is 14.2 ~6.0!. Although the abnormal returns across the
two studies cannot be compared directly due to differences in the sample
periods as well as differences in the methodology, the results nonetheless
show that a high level of short interest conveys negative information, regardless of whether the stock is traded on the NYSE0AMEX or on the Nasdaq
market.
C. Analysis of an Alternative Classification of Heavily Shorted Firms
While our identification of heavily shorted firms as those with short interest in excess of 2.5 percent is consistent with AM, it is admittedly arbitrary. As discussed earlier, the statistics in Table I indicate that shares shorted
as a percentage of shares outstanding has steadily increased over time. To
the extent the intertemporal increase ref lects increased short selling for
hedging purposes, a given absolute level of short interest may indicate different levels of adverse information over time. This possibility could be somewhat mitigated by the use of a “relative” cutoff to identify heavily shorted
firms. Consequently, we repeat the analysis using an alternative definition
in which a firm is classified as heavily shorted in a given month if its level
of short interest as a percentage of shares outstanding is above the 90th
percentile of all firms with short positions in that month. We also consider
a sample of firms with short interest above the 95th percentile.10
To implement the calendartime portfolio approach, for each month from
July 1988 to January 1995, we form portfolios of firms that had short interest in the 90th percentile or higher in the previous month. The portfolio
is rebalanced monthly to drop all firms whose short interest fell below the
90th percentile in the previous month and to add firms whose short interest
meets the 90th percentile cutoff in the previous month. The 95th percentile
portfolio is formed in a similar manner. The results ~not reported in tables!
show that the abnormal return for firms with short interest above the 90th
~95th! percentile is 0.65 percent ~ 0.77 percent! per month with a tstatistic
of 3.11 ~ 3.00!. These results show that our finding that a high level of
short interest conveys negative information is robust to alternative classification of heavily shorted firms.
D. An Analysis of Intertemporal Increases in Short Interest
The results documented so far suggest that a high level of short interest is
a bearish signal. To test the robustness of the levels analysis, we examine
the informativeness of increases in short interest positions. If short interest
is a bearish signal, we should expect, on average, a negative association
10
The number of observations in the 90th percentile sample and the 95th percentile sample
are 24,318, and 12,173, respectively. Short Interest and Stock Returns 2275 between a large increase in short interest and stock returns. This analysis is
closer in spirit to the DV model which predicts that an “announcement of an
unexpected increase in short interest in a security is bad news” ~p. 301!. We
define change in short interest in a given month as the change in the number of shares sold short relative to the previous month, as a percentage of
the total number of shares outstanding.
Similar to the approach used in our levels analysis, we form four portfolios of stocks with a large increase in shortinterest positions. For the entire universe of Nasdaq stocks, the mean ~median! monthtomonth change
in short interest over our sample period is 0.000805 percent ~0.0 percent! of
the shares outstanding. Given that the monthtomonth change in short interest is small, similar to our levels analysis, we use ad hoc cutoffs to form
portfolios of stocks with relatively large increase in short interest. The cutoffs are increases in short interest of 1 percent, 1.5 percent, 2 percent, and
2.5 percent of the shares outstanding in a month. The number of observations in each of the above samples are 6,914, 4,291, 2,856, and 2,026, respectively. Similar to the approach used earlier, we measure abnormal returns
for the samples of large increase in short interest using the calendartime
portfolio approach.
In particular, for August 1988 to January 1995, we form a portfolio of all
stocks that had at least a 1 percent ~or 1.5 percent, 2 percent, or 2.5 percent,
as the case may be! increase in short interest in the previous month. The
portfolio is rebalanced monthly to drop all stocks that did not have an increase in short interest of at least 1 percent in the previous month and add
stocks whose short interest increased by at least 1 percent of the shares
outstanding in the previous month. We find that the abnormal return experienced by this portfolio over the sample period is 0.41 percent per month
with a tstatistic of 17.46 ~results not reported in tables!. The corresponding monthly abnormal returns for the 1.5 percent, the 2 percent, and the
2.5 percent portfolios are 0.42 percent ~ tstatistic of 10.48!, 0.42 percent ~ tstatistic of 4.48!, and 0.45 percent ~ tstatistic of 7.53!, respectively.
Thus, the results for the increase in short interest are consistent with the
results documented for the level of short interest and further support the
conclusion that high short interest is a bearish signal. The results also seem
to be consistent with the prediction in DV that an increase in short interest
conveys negative information.
E. Clustering by Time
To evaluate whether the negative performance of heavily shorted firms is
specific to a particular time period, we divide the sample period of 79 months
~from June 1988 to December 1994! into two periods of 40 months ~from
June 1988 to September 1991! and 39 months ~from October 1991 to December 1994!. Since the results for portfolios formed using returns from
month EN 1 to EX 1 and from month EN 1 to EN 12 are similar, we
only report the results for the former. Also, since the abnormal returns are 2276 The Journal of Finance
Table V Calendartime Abnormal Returns for the Heavily Shorted Firms:
June 1988 to September 1991 versus
October 1991 to December 1994
This table reports the coefficients from a timeseries regression of excess monthly portfolio
returns ~in excess of Tbill rate! on the three factors suggested by Fama and French ~1993! and
the fourth suggested by Carhart ~1997!. The following regression is estimated:
RPRFt a0 a 1 RMRFt a 2 SMBt a 3 HML t a 4 PR 1YR t et , where RPRFt is the portfolio excess return for the sample firms in month t and RMRFt ~market
factor! is the excess return of the valueweighted portfolio of NYSE0AMEX and Nasdaq firms.
The size factor ~ SMBt !, the booktomarket factor ~ HML t !, and the momentum factor ~PR1YR!
are described in Carhart. The portfolio returns for the short interest sample are in calendar
time. Data are available from June 1988 to December 1994, except for February 1990 and July
1990. For these two months, the firms are assumed to have the same level of short interest as
the previous month. The 2.5 percent short interest sample consists of those firms that had
short interest of at least 2.5 percent of the shares outstanding at the end of a given month. The
10 percent short interest sample is defined similarly. The sample period is divided into two
almost equal time periods, from June 1988 to September 1991 and from October 1991 to December 1994. For every month from July 1988 to October 1991, the portfolio is formed using all
the firms that had at least 2.5 percent ~or 10 percent! short interest in the previous month. New
firms get added each month if their short interest attains the threshold in the previous month,
and some firms get dropped if their short interest drops below the threshold in the previous
month. The same procedure is implemented from November 1991 to January 1995. Panel A
reports the results for the 2.5 percent short interest sample and Panel B reports results for the
10 percent short interest sample. The tstatistic is reported in parentheses. Time Period Intercept RMRF SMB HML PR1YR Adj. R 2
~%! Panel A: 2.5% Short Interest Sample
June 1988 to
September 1991 0.94%
~ 2.94! 1.26
~13.49! 0.97
~5.91! 0.04
~ 0.16! 0.61
~ 4.61! 92.42 October 1991 to
December 1994 0.57%
~ 1.76! 1.36
~12.31! 1.42
~11.05! 0.19
~ 1.49! 0.51
~ 4.05! 90.52 Panel B: 10% Short Interest Sample
June 1988 to
September 1991 1.19%
~ 2.08! 1.31
~7.88! 1.56
~5.32! 0.01
~0.02! 0.27
~ 1.16! 82.14 October 1991 to
December 1994 0.87%
~ 1.70! 1.51
~8.70! 1.25
~6.19! 0.28
~ 1.41! 0.46
~ 2.34! 79.32 generally monotonic in the level of short interest, we report results only for
the 2.5 percent sample and the 10 percent sample.
Table V provides the results of the analysis for the two subperiods. Panel A
reports the results for the 2.5 percent sample and Panel B reports the results for the 10 percent sample. The results for the 2.5 percent sample show
that in the first half of the sample period ~June 1988 to September 1991!,
the monthly abnormal returns are 0.94 percent ~ tstatistic of 2.94!. The Short Interest and Stock Returns 2277 abnormal returns over the second half ~October 1991 to December 1994! are
smaller ~ 0.57 percent per month!, but are significant at the 10 percent
level with a tstatistic of 1.76. The results are similar for the 10 percent
short interest sample.11
We also repeat the above analysis using an alternative definition of heavily shorted firms. For the 90th percentile short interest sample, we find that
the abnormal returns using the calendartime portfolio approach are 0.80 percent per month ~ tstatistic of 2.89! in the first half of the sample period
and 0.60 percent per month ~ tstatistic of 1.94! in the second half of the
sample period. For the 95th percentile sample, the monthly abnormal returns are 0.81 percent ~ tstatistic of 2.00! and 0.73 percent ~ tstatistic
of 2.17! in the first half and the second half, respectively.
Similarly, we also analyze the informativeness of the increase in short
interest over the two subperiods. We find that for the 1 percent increase in
short interest sample, the abnormal returns ~using calendartime portfolio
approach! are 0.60 percent per month ~ tstatistic of 10.38! in the first
subperiod and 0.25 percent ~ tstatistic of 5.92! in the second subperiod.
The corresponding abnormal returns for the 2 percent increase in short interest sample over the first and the second subperiods are 0.58 percent
~ tstatistic of 3.90! and 0.31 ~ tstatistic of 2.74!, respectively. Taken together, the results suggest that the negative abnormal returns documented
for the heavily shorted firms are not confined to a particular time period.12 III. Robustness Checks
We perform two robustness checks to examine whether the results are
sensitive to the benchmark used for measuring abnormal returns. First, we
replicate the calendartime portfolio analysis using valueweighted returns,
and second, we replicate the analysis using a matching firm methodology.
A. An Analysis of ValueWeighted Portfolio Returns
Since the common asset pricing models have difficulty explaining the cross
section of average returns of small stocks ~see Fama ~1998!!, and since, for
the most part, the abnormal returns in longhorizon event studies are most 11
We also examine if the sample is clustered in certain industries. We find that 63 different
industries ~at the twodigit SIC code level! are represented in the 2.5 percent sample. The
distribution is similar for the 5 percent, the 7.5 percent, and the 10 percent short interest
samples. There are six industries that each represent more than 5 percent of the sample. The
results show that the abnormal returns are not driven by specific industries.
12
The increase in short interest for the universe of Nasdaq firms ~reported in Table I! coincides with the increasing use of short sales for arbitrage and hedging transactions. To the
extent this transactions information is neutral, short interest has become a noisier proxy for
adverse information over time. Lack of more refined data limits our ability to further examine
the results of the subperiod analysis. 2278 The Journal of Finance pronounced for small stocks, one cannot rule out the possibility that our
results are due to the use of a misspecified assetpricing model. To the extent empirical assetpricing models are better specified for large firms, use
of valueweighted returns would mitigate the effects of model misspecification by giving less weight to small stocks. In Table VI, we report the main
results of our analysis using valueweighted ~using market value of equity in
the prior month as weights! portfolio returns for the 2.5 percent and the
10 percent samples. In Panel A, we report the result where each firm is
included in the portfolio from month EN
1 to EX
1 ~similar to the
analysis in Table III! and in Panel B, we report the results where each firm
is included in the portfolio from month EN
1 to EN
12 ~similar to the
analysis in Table IV!.
The results in Panel A show that the abnormal return for the 2.5 percent
sample is 0.45 percent per month ~ tstatistic of 1.73! over the sample
period. The corresponding abnormal return for the 10 percent sample is
0.85 percent ~ tstatistic of 2.06!. While the abnormal returns using valueweighted portfolio returns are smaller than the corresponding abnormal returns using equalweighted portfolio returns ~Table III!, the valueweighted
abnormal returns are still large and statistically significant. The results in
Panel B for the period EN
1 to EN
12 show that, while the abnormal
returns for the 2.5 percent sample are small and statistically not significant
~ 0.17 percent, with a tstatistic of 0.62!, the abnormal returns are large
and significant for the 10 percent sample. Specifically, for the 10 percent
sample, the abnormal returns are 0.80 percent per month with a tstatistic
of 2.14.
Thus, the results of the valueweighted analysis indicate that although
the magnitude of the abnormal returns accruing to the heavily shorted firms
are lower using valueweighted portfolio returns, the abnormal returns are
still relatively large, and for the most part, statistically significant. Given
that the larger firms are more actively followed, short sellers are more likely
to have an informational advantage in smaller stocks. The results of the
valueweighted analysis appear to be consistent with this possibility.13
B. MatchingFirmAdjusted Returns
The use of the matching firm or control firm as a benchmark is motivated
by the results in Barber and Lyon ~1997!, who show empirically that the use
of the control ~matching! firm as a benchmark yields wellspecified test statistics. We select matching firms based on size, booktomarket, and prior
sixmonth return momentum. The reason for matching on momentum is that
13
“Percentage misvaluations, in equilibrium, will be larger for small stocks. Otherwise, arbitrageurs could make more money, net of costs, by finding misevaluations among big stocks.
This is the logic in Shleifer and Vishny ~1990, 1997!. Thus, for any given misvaluations that
occur, there will be a stronger force pushing the price towards fundamental value ~and thus
limiting the magnitude of any misvaluation! for big stocks” ~Loughran and Ritter ~2000, p. 363!!. Short Interest and Stock Returns 2279 Table VI CalendarTime Abnormal Returns for the Sample of Heavily
Shorted Firms: ValueWeighted Returns
This table reports the coefficients from a timeseries regression of excess monthly portfolio
returns ~in excess of Tbill rate! on the three factors suggested by Fama and French ~1993! and
the fourth suggested by Carhart ~1997!. The returns are valueweighted using market value of
equity as weights. The following regression is estimated,
RPRFt a0 a 1 RMRFt a 2 SMBt a 3 HML t a 4 PR 1YR t et , where RPRFt is the portfolio excess return for the sample firms in month t and RMRFt ~market
factor! is the excess return of the valueweighted portfolio of NYSE0AMEX and Nasdaq firms.
The size factor ~ SMBt !, the booktomarket factor ~ HML t !, and the momentum factor ~PR1YR!
are described in Carhart. The portfolio returns for the short interest sample are in calendar
time. Data are available from June 1988 to December 1994, except for February 1990 and July
1990. For these two months, the firms are assumed to have the same level of short interest as
the previous month. The 2.5 percent short interest sample consists of those firms that had
short interest of at least 2.5 percent of the shares outstanding at the end of a given month. The
10 percent short interest sample is defined similarly. Panel A reports the results when firms
are in the portfolio from month EN 1 to EX 1. Specifically, for every month from July 1988
to January 1995, the portfolio is formed using all the firms that had at least 2.5 percent short
interest ~or 10 percent, as the case may be! at the end of the previous month. Each month new
firms get added when they attain the threshold short interest level in the previous month and
some firms get dropped when their short interest drops below the threshold in the previous
month. Thus, a firm enters the portfolio in month EN 1 and remains in the portfolio through
month EX 1. For results reported in Panel B, a firm enters the portfolio if its short interest
in the previous month reaches the 2.5 percent threshold for the first time ~or 10 percent as the
case may be!. This firm remains in the portfolio for the 12 consecutive months. Thus, each firm
enters the portfolio in month EN
1 and remains in the portfolio through month EN
12.
Thus, we have monthly portfolio returns from July 1988 to December 1995. The tstatistic is
reported in parentheses.
Short Interest
Sample Intercept RMRF SMB HML Panel A: Firms Are in the Portfolio from Month EN Adj. R 2
~%! PR1YR
1 to EX 1 2.5% 0.45%
~ 1.73! 1.32
~17.49! 1.07
~9.11! 0.51
~ 4.05! 0.42
~ 4.04! 89.24 10% 0.85%
~ 2.06! 1.30
~10.76! 1.10
~5.83! 0.79
~ 3.94! 0.31
~ 1.88! 77.67 Panel B: Firms Are in the Portfolio from Month EN 1 to EN 12 2.5% 0.17%
~ 0.62! 1.25
~15.34! 0.77
~6.18! 0.79
~ 5.87! 0.30
~ 2.65! 85.01 10% 0.80%
~ 2.14! 1.29
~11.52! 0.99
~5.80! 0.92
~ 5.07! 0.25
~ 1.64! 78.40 the sample firms experience a large runup in price prior to becoming heavily shorted. Lyon, Barber, and Tsai ~1999! show that, in cases where the
sample firms have experienced extreme prior performance, controlling for
the prior performance is especially important. 2280 The Journal of Finance
B.1. MatchingFirm Approach Each month we sort the entire universe of Nasdaq into 10 size ~marketvalueofequity! deciles. Then each size decile is further sorted into five booktomarket quintiles. Thus, each month, the universe of Nasdaq firms is divided
into 50 portfolios. To avoid the lookahead bias, we use the book value of
equity in a given month only if that month is at least four months after the
company’s fiscal yearend, otherwise we use the book value of equity from
the previous fiscal year.
For each sample firm, we identify four matching firms that have the same
size rank and the booktomarket rank as the sample firm, and have a prior
sixmonth return ~momentum! that is closest to the sample firm. Matching
firms are selected such that two of the matching firms have a prior sixmonth return ~momentum! larger than the sample firm and the other two
have a prior sixmonth return smaller than the sample firm. The matching
firms are selected in month 1 relative to the firm’s entry in the short
interest sample ~i.e., EN
1!. To ensure proper control, we do not allow a
sample firm to be a matching firm from six months prior to its entry in the
sample ~EN 6! until 36 months after it exits the sample ~EX 36!.
From the two matching firms that are closest in sixmonth return momentum to the sample firm ~one with sixmonth return momentum larger than
the sample firm and the other with sixmonth return momentum smaller
than the sample firm!, we randomly designate one of the two as the first
matching firm. The other firm is designated as the second matching firm.
The remaining two matching firms are randomly assigned as the third and
the fourth matching firms. We use the first matching firm’s returns as the
benchmark against which we compare the performance of the sample firm.
If the first matching firm disappears, we use that firm’s returns until its
last available return date. After that, we use the second matching firm’s
returns and so on. This procedure guarantees that the matching firms are
picked at the same time as the sample firms and avoids the potential hindsight bias in the selection of matching firms. If all four matching firms disappear, we use the CRSP valueweighted index returns from that point on.
If a sample firm is delisted, we compound the sample firm returns as well as
the matching firm returns until the month of the last available return of the
sample firm.14
We examine the matchingfirm abnormal returns using two different methodologies. First, we develop an approach similar to the calendartime portfolio approach to provide estimates of abnormal returns that are directly
comparable to those reported using the calendartime portfolio approach. 14
For the matching firm adjusted analysis, we have 1,842 sample firms in the 2.5 percent
sample for which the requisite data are available ~most of the observations are lost due to
missing booktomarket values and some are lost due to missing prior sixmonth returns!. In
1,472 out of 1,842 cases, only one matching firm’s returns were needed. For 283 ~52035! firms,
we used two ~three0four! matching firms for each sample firm. Short Interest and Stock Returns 2281 Second, we examine the performance of the short interest sample over several holding periods, ranging from one month to 24 months. The results of
these analyses are discussed in sequence.
Similar to the calendartime portfolio approach, for each month from July
1988 to January 1995, we form a portfolio of all firms that have at least
2.5 percent short interest in the previous month. In the calendartime portfolio approach, portfolio raw return in excess of the riskfree rate is regressed on an intercept and the four assetpricing factors and the intercept
is an estimate of the abnormal return. In the matching firm approach, we
compute monthly abnormal return for each firm by subtracting the matching firm’s return from the sample firm’s return. Then the portfolio abnormal
return is calculated each month as the average of the sample firm abnormal
returns. The abnormal return to this strategy over the sample period is
0.98 percent per month, with a tstatistic of 4.00 ~results not reported in
tables!. The corresponding monthly abnormal return for the 10 percent
sample is 1.11 percent with a tstatistic of 2.99. We obtain comparable
results when firms are retained in the portfolio for 12 months from EN 1
to EN 12 ~similar to the approach in Table IV!.
In an alternative approach, we examine buyandhold returns over different holding periods. We calculate a buyandhold return for a stock i for T
months as
T ) ~1 R iT rit ! 1.0, ~2! t1 where rit is the raw return ~with dividends! for stock i in month t. The
return for the matching firm is computed in a similar manner and is denoted by R mT . The holding period abnormal return ~HAR! for stock i is calculated as
HAR iT R iT R mT . ~3! Abnormal return is then averaged over all the stocks in the sample to obtain
the average holding period abnormal return ~AHAR! for a portfolio of n stocks
and is given by
AHAR T 1
n n ( HAR iT . ~4! i1 The statistical significance of the AHAR T is determined by using a tstatistic
that is computed as
t AHAR T
SET , where SET is the estimated standard error of AHAR T . ~5! 2282 The Journal of Finance
Table VII Matching Firm Adjusted Abnormal Returns for the 2.5% Sample
The table reports the mean buyandhold ~holding period! raw returns for the sample firms
~RAWS!, the corresponding mean returns for the matching firms ~RAWM!, the average abnormal returns ~AHAR! for the sample firms, the tstatistic associated with the mean abnormal
returns, and the percentage of firms with positive abnormal returns ~HAR!. The matching
firms have the same size decile ranking and the same booktomarket quintile ranking as the
sample firm in the month before attaining the threshold level of short interest and are closest
in sixmonth return momentum to the sample firm. The matching firms are selected in month
1 relative to the firm’s entry into the short interest sample. Data are available from June
1988 to December 1994, except for February 1990 and July 1990. For these two months, the
firms are assumed to have the same level of short interest as the previous month. Short interest is defined as a ratio of shares shorted to the total number of shares outstanding at the
end of each month. A firm enters the 2.5 percent short interest sample when its short interest
reaches 2.5 percent in a given month and leaves the sample when the short interest level falls
below 2.5 percent. EN refers to the month in event time when the sample firm first enters the
short interest sample and EX refers to the last consecutive month for which the sample firm’s
short interest remains at or above the 2.5 percent level. Fewer than 2,726 observations result
due to either missing booktomarket values or the firm having fewer than three valid returns
in the sixmonths before entering the sample ~EN 6 to EN 1!.
No. of
Obs. Subperiod
EN
EN
EN
EN
EN
EN
EN
EX
EX 6 to EN 1 1 to EN
7 to EN
13 to EN
1 to EN
1 to EN
1 to EX
13 to EX 6
12
24
12
24
12
24 RAWS
~%! RAWM
~%! 1,842
1,842
1,841
1,829
1,785
1,841
1,841
1,802
1,687 29.76
1.18
2.55
4.34
14.26
7.02
22.27
10.53
14.39 26.55
0.80
7.11
5.23
15.72
13.59
31.13
17.84
18.27 AHAR
~%!
3.22
0.39
4.56
0.89
1.46
6.57
8.85
7.31
3.88 tStatistic
2.77
0.51
3.30
0.63
0.59
3.03
2.28
3.11
1.55 % Positive
HAR
50.71
51.47
45.90
48.17
47.68
44.60
45.03
45.78
47.95 B.2. Results
Table VII reports the results for the 2.5 percent sample using the matching firm methodology.15 The results show that the sample firms experience
large runup in price prior to becoming heavily shorted.16 The mean raw
returns for the sample firms in the six months prior to their entry in the
short interest sample ~EN 6 to EN 1! are 29.76 percent. In the month of
entry ~EN!, that is, the first month for which the short interest reaches the
2.5 percent threshold, the abnormal returns are 0.39 percent ~ tstatistic of
0.51! and are not significant. Recall that the Nasdaq releases the aggregate
data on short interest towards the end of the third week or in the early part
15 The results for the 10 percent sample are similar.
We require the sample firms to have the booktomarket ratio available in month EN 1
as well as at least three nonmissing returns in the six prior months ~from EN 6 to EN 1!.
As a result, the sample size for this analysis is smaller than the sample size for the calendartime portfolio analysis.
16 Short Interest and Stock Returns 2283 of the fourth week of a month. Thus, a likely reason for the lack of significance of the abnormal return in month EN is that the abnormal return in
that month primarily ref lects information available prior to the release of
the short interest position. The abnormal returns over longer holding periods show that following their becoming heavily shorted, the sample firms
significantly underperform their matching firms. The abnormal returns ~with
tstatistic in parenthesis! for holding periods of six months ~EN 1 to EN 6!,
12 months ~EN
1 to EN
12! and 24 months ~EN
1 to EN
24! are
4.56 percent ~ 3.30!, 6.57 percent ~ 3.03!, and 8.85 percent ~ 2.28!,
respectively.17
While market efficiency predicts an immediate adjustment of prices to
information contained in the short interest, our results show that the adjustment may not be immediate. The heavily shorted firms continue to experience abnormal returns in the months after the information on short
interest is released. While this result does not necessarily indicate market
inefficiency, it appears to be consistent with the results in the extant literature documenting postannouncement drift in various contexts ~see Fama
~1998! for a review of this literature!.
We also examine the stock price performance of the sample firms after
their short positions fall below the threshold for being considered as heavily
shorted, that is, after they exit the sample. The results show that the sample firms experience significant negative abnormal returns for 12 months
after ceasing to be heavily shorted ~EX
1 to EX
12!. The abnormal
returns over the period EX 1 to EX 12 are 7.31 percent with a tstatistic
of 3.11, while no significant abnormal returns are earned in the following
12 months ~EX 13 to EX 24!.
We find that the continuation of poor performance after exiting the short
interest sample is driven by continuing large short positions even after exiting the sample. Although a firm is not considered heavily shorted if its
short interest drops below 2.5 percent, the choice of 2.5 percent as the cutoff
is arbitrary. We find that the mean ~median! short interest of the sample
firms in the month in which they drop out of the 2.5 percent sample is
1.32 percent ~1.52 percent!. For the 10 percent sample, the corresponding
mean ~median! is 5.9 percent ~7.8 percent!. The 75th percentile of short interest for the universe of Nasdaq firms over our sample period is 0.5 percent. Thus, the sample firms continue to have relatively large short positions
even after they exit the sample.
To mitigate this effect, we examine the abnormal returns surrounding large
decreases in short interest position ~results not reported in tables!. Specifically, we identify stocks whose short interest declined by at least 2.5 percentage points in a month and, after the decrease in short interest, their
17
In addition to the buyandhold abnormal returns, we also examine monthly abnormal
returns for each month from EN
1 to EN
12. We find that the abnormal returns are
negative in 11 out of 12 months and are statistically significant in months EN 1, EN 3, and
EN 4. 2284 The Journal of Finance short interest level dropped below 2.5 percent of the shares outstanding. We
also examine a sample of stocks with at least a 5 percentage points decrease
in short interest. In these two samples, we find that the mean ~median! level
of short interest is only 0.55 percent ~0.22 percent! and 0.44 percent ~0.14 percent!, respectively, immediately after the large decline in short interest. In
the month subsequent to their exit, the abnormal returns in the above two
samples are 0.007 percent ~ tstatistic of 0.02! and 0.17 percent ~ tstatistic
of 0.09!, respectively. Thus, when the short interest positions are largely
unwound, the abnormal returns do not appear to persist. IV. Survival Status of the Firms Following Periods
of Heavy Short Selling
The results reported in the previous sections show that high level of short
interest conveys negative information as evidenced by subsequent poor stock
market performance. Given that heavily shorted firms perform poorly relative to their matching firms, it is reasonable to expect a higher incidence of
liquidations and bankruptcies in the sample firms than in their matching
firms. Thus, we expect to observe a higher incidence of performance related
delistings in the sample firms than in their matching firms.18
In this section, we test whether the sample firms experience a higher
incidence of performancerelated delistings than their size, booktomarket, and momentummatched matching firms.19 This analysis provides
an alternative test of the informational role of short interest without relying
on the magnitude of the abnormal returns. To conduct this analysis, we
track the survival status of the sample firms and their matching firms for
36 months following the sample firms’ entry in the short interest sample.
We use a nonparametric binomial test to examine whether the delisting
frequency in the sample firms is significantly higher than the matching
firms. We define n as the number of sample firms that have delisted in the
36 months following their entry into the short interest sample and m as the
corresponding number of matching firms that have delisted over the same
period. If the probability of delisting of the sample firms is the same as that
of the control firms, then the expected value of the number of delistings for
the sample firms is ~ n
m ! * 0.5 and variance is ~ n
m ! * 0.5 * 0.5 *
~~ N M
~ n m !!0~ N M
1!!, where N and M are the total number of
sample firms and control firms, respectively ~DeGroot ~1986, pp. 249–250!!.
18
We identify delistings and the cause of delistings from the CRSP delisting codes. For
example, firms are delisted if their share price falls below a certain level, if the firm has
insufficient capital, or if the firm does not meet the exchange’s financial guidelines for continued listing.
19
For the purpose of this test, we compare the survival status of a sample firm with the
survival status of one matching firm. We have a pool of four matching firms that were selected
based on size, booktomarket, and momentum. From the first two matching firms, we randomly designate one of them as the matching firm for the purpose of this analysis. Short Interest and Stock Returns 2285 Table VIII A Comparison of Delistings of Sample Firms and Their Matching
Firms 36 Months after Entry into the Short Interest Sample
The table reports the frequency of delisting of the sample firms and their corresponding matching firms 36 months after the sample firm enters the short interest sample. The sample consists of all firms on the Nasdaq from June 1988 to December 1994 whose short interest exceeds
a certain level. Data are available from June 1988 to December 1994, except for February 1990
and July 1990. For these two months, the firms are assumed to have the same level of short
interest as the previous month. Short interest is defined as a ratio of number of shares shorted
to the total number of shares outstanding at the end of each month. A firm enters the short
interest sample when its short interest reaches a certain threshold ~2.5 percent or 10 percent!
in a given month and leaves the sample when the short interest level falls below the threshold.
The delisting data are obtained from the CRSP files. The delistings are assumed to follow a
binomial distribution and the zstatistic is for the difference in the delisting frequency for the
sample firms and their matching firms. The matching firm for each sample firm is selected
randomly from the two matching firms that are in the same size decile and the same booktomarket quintile as the sample firm and that are closest in prior sixmonth return momentum
~one with return momentum larger than the sample firm and the other with return momentum
smaller than the sample firm!. The matching is done in month 1 relative to the firm’s entry
into the short interest sample. Fewer observations result due to missing booktomarket values
and missing sixmonth momentum for the sample firm and missing delisting code for either the
sample or the matching firm. Panel A presents the analysis for the 2.5 percent short interest
sample and Panel B presents analysis for the 10 percent short interest sample. Listing Status Frequency
~Sample! Percent
~Sample! Frequency
~Matching
Firm! Percent
~Matching
Firm! zStatistic for
the Difference
in Frequency Panel A: Delisting Analysis of the 2.5% Short Interest Sample
Active
Mergers or exchanges
Liquidations or delisted
by the exchange 1,425
185
141 81.38
10.57
8.05 1,469
170
112 83.89
9.71
6.40 Total 1,751 100.00 1,751 0.82
0.80
1.82 100.00 Panel B: Delisting Analysis of the 10% Short Interest Sample
Active
Mergers or exchanges
Liquidations or delisted
by the exchange 318
42
28 81.96
10.82
7.22 347
27
14 89.43
6.96
3.61 Total 388 100.00 388 1.12
1.81
2.16 100.00 Table VIII reports the survival status of the sample firms and the matching firms 36 months after the sample firms’ entry in the short interest sample ~i.e., in month EN 36! as well as the Zstatistic from the binomial test.
Panel A reports the results for the 2.5 percent short interest sample and
Panel B reports the results for the 10 percent short interest sample. In the
2.5 percent sample, we find that 8.05 percent of the sample firms either
liquidated or were forced to delist by the exchange within 36 months of their
entry in the short interest sample. On the other hand, 6.40 percent of the 2286 The Journal of Finance matching firms suffered the same fate. This difference is statistically significant at the 10 percent level with a zstatistic of 1.82. The results for the
10 percent short interest sample reported in Panel B of Table VIII are similar. The proportion of sample firms that are either liquidated or delisted by
the exchange is 7.22 percent; the corresponding proportion for the matching
firms is 3.61 percent. The difference is statistically significant, with a zstatistic
of 2.16. The above results provide further support to the assertion that a
high level of short interest conveys negative information.20
V. Conclusions
Short positions have been posited in the literature as being bearish, bullish, or neutral signals. The purpose of this paper is to examine which of
these perspectives is supported by empirical evidence. Our examination reveals that large short positions are bearish signals. We find that firms with
large short positions experience negative and significant abnormal returns
when they are heavily shorted. The negative abnormal returns are increasing in the level of short interest, suggesting that a higher level of short
interest is a stronger bearish signal. We also document a negative relationship between large increases in short interest and subsequent abnormal returns. The results are consistent with short sellers having private information.
Our results also suggest that short sellers target highly liquid firms whose
prices are high relative to their fundamentals. An examination of the survival characteristics shows that heavily shorted firms experience a significantly higher incidence of liquidations or forced delisting than their size,
booktomarket, and momentummatched control firms. Overall, the results
suggest that, on average, high level of short interest conveys negative
information.
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