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This study documents the behaviour of short-sellers on and around insider-selling events, the reporting date for mandatory SEC filings and the insider sales around news announcement dates in particular. The results are obtained primarily by running event-studies around the insider-selling events in general and those near news announcement dates, and observing trends in short-selling activity in our selected event window. Our findings corroborate the widely-held view that short-selling activity sees a surge in the days immediately before the insider sales. Then, we classify the insider selling events as large and small sales and run similar event studies to find out any differential behaviour based on the size of the insider sale in the specified event window. We conclude that large insider sales are preceded by a significant spike in short-selling activity whereas small insider sales don’t get front-run in a significant manner. Our news announcement analysis leads us to infer that when insider sales are executed around news announcements about a firm, they are front-run by short-sellers even more significantly than usual. We complement all our event studies with corresponding regressions to test whether short sales are higher indeed around our designated events after controlling for usual suspects namely, returns, intra-day volatility and volume. We reach the conclusion that short-sellers have access to private information that they use to front-run insiders systematically.
Citation preview
Do short-sellers trade on inside information?
M.Sc. Finance 2013-14
Submitted by: Arjun Chhabra
Supervisor:
Student ID:
Dr. Vikas Raman
1357903
Module Title: Research Methodology & Dissertation
Module Code: IB93F0
Date Submitted: 01/09/2014
“All the work contained within is my own unaided effort and conforms with the University’s
guidelines on plagiarism.”
“No substantial part(s) of the work submitted here has also been submitted by me in other
assessments for accredited courses of study, and I acknowledge that if this has been done an
appropriate reduction in the mark I might otherwise have received will be made.”
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ii Do short-sellers trade on inside information?
Abstract
This study documents the behaviour of short-sellers on and around insider-selling events, the
reporting date for mandatory SEC filings and the insider sales around news announcement
dates in particular. The results are obtained primarily by running event-studies around the
insider-selling events in general and those near news announcement dates, and observing
trends in short-selling activity in our selected event window. Our findings corroborate the
widely-held view that short-selling activity sees a surge in the days immediately before the
insider sales. Then, we classify the insider selling events as large and small sales and run
similar event studies to find out any differential behaviour based on the size of the insider
sale in the specified event window. We conclude that large insider sales are preceded by a
significant spike in short-selling activity whereas small insider sales don’t get front-run in a
significant manner. Our news announcement analysis leads us to infer that when insider sales
are executed around news announcements about a firm, they are front-run by short-sellers
even more significantly than usual. We complement all our event studies with corresponding
regressions to test whether short sales are higher indeed around our designated events after
controlling for usual suspects namely, returns, intra-day volatility and volume. We reach the
conclusion that short-sellers have access to private information that they use to front-run
insiders systematically.
Keywords: short-selling, insider sales, event study, news announcements, private
information, front-running, form-filing.
Acknowledgements: I would like to thank my supervisor, Dr. Vikas Raman for his continued
guidance and support throughout my research and report preparation. I am grateful to him
for his valuable feedback and encouragement during the past 3 months. I am also thankful to
my parents for enabling me to study this programme at Warwick Business School and
providing important advice as required. Lastly, I would like to thank my friends at the
university and back home for all their care and generous help throughout my dissertation.
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iii Do short-sellers trade on inside information?
Contents
1. Introduction ........................................................................................................................... 1
2. Literature Review ................................................................................................................... 5
3. Data Sources & Sample Selection .......................................................................................... 8
4. Methodology ........................................................................................................................ 10
4.1. Short-Sales around Insider Sale Date ............................................................................ 10
4.2. Short sales around form-filing date .............................................................................. 12
4.3. Short-selling around large and small insider sales ........................................................ 12
4.4. Short-sales around news announcement-led insider sales .......................................... 12
4.5. Regression Studies-the alternate method .................................................................... 13
5. Results .................................................................................................................................. 16
5.1. Short-selling and Insider Sales ...................................................................................... 16
5.2. Short-selling and Form 4 filing ...................................................................................... 17
5.3. Short-sales and Insider Sale Size ................................................................................... 17
5.4. Short selling and news announcements ....................................................................... 18
6. Conclusion ............................................................................................................................ 20
References ............................................................................................................................... 22
Appendix .................................................................................................................................. 25
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1. Introduction
hort-selling of securities is quite common worldwide and accounts for approximately
24% of NYSE and 31% of NASDAQ daily share volume (Diether et al. 2008). Apart
from a few aberrations in the past relating to short-selling bans (most of which have been
widely debated), short-selling has largely existed simultaneously with normal buying and
selling of securities and helped price-discovery in the markets. Of late, especially in the light
of the 2008 financial crisis, there has been a tremendous interest, by academicians and
regulators alike, in the role of short-sellers and their so-called “superior” ability to process
available information about the market and predict future returns significantly. Short-sellers
have been shown to be sophisticated market participants who are more informed than the
general market and possess the ability to beat the market consistently, earning abnormal
returns over time. However, very little research has been done on the actual source of
information of short-sellers and the manner in which this information is obtained. Most of
these studies confine themselves to analysing the returns generated by short-sellers, stock-
picking ability and timing, attributing their sophistication to one factor or the other by way of
indirect implications, without addressing directly the question of where the information is
sourced from or how it is acquired, probably due to the paucity of short-interest data.
Another class of investors who are privy to the most profit-generating information is the
corporate insiders. In fact, insiders (CEO, directors, key employees, etc.) are the most
informed of all market participants since they possess all the private information about a
company that an outsider is unexpected to be privy to. The trading activity of insiders is
closely monitored by all market-watchers for it provides a very strong signal about a firm’s
fundamentals. In the absence of news announcements and analyst recommendations, insider
trading activity often lends credibility to or disproves rumours about a firm. Regulation
requires all insiders to disclose their trades to the SEC on Form 4 within two business days of
their execution, which is then made public in real time. Thus, the market tracks these trades
upon their disclosure by the SEC and exploits the information content in these trades. Insiders
are forbidden to share any confidential or private information about the firm with outsiders in
an illegal manner that may deem unfair to other market participants who may not possess this
information. Large insider trades have often been leaked in the process of execution by
S
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2 Do short-sellers trade on inside information?
several unscrupulous elements for profiteering and the relative benefits of getting away with
it as compared to the costs, which are the same for small trades. Although the regulatory
bodies have unearthed and successfully prosecuted some high-profile black sheep, insider
trading goes largely uncaught.
Despite the extant extolment of short-sellers by academicians and the widespread
acknowledgement of their role in market efficiency and price discovery, some quarters in the
popular press as well as the academic community have cast doubts on the means of acquiring
information by short-sellers. Several instances in the past including the sweeping
investigation by the SEC in 2007 into the conduct of some Merrill Lynch brokers have hinted
at what might be the tip of an iceberg; specifically, that short-sellers, because of their market
stature (most short-selling activity is undertaken by hedge funds), have access to private
information which they unethically use to front-run the corporate insiders. Our results
provide proof of short-sellers trading ahead of insiders for the firms in our sample and this
phenomenon is even more pronounced for large insider sales and when such sales are based
on news about a firm.
Legislation around the world makes it a fiduciary duty of the insiders “to protect the interest
of the company’s shareholders while they are in possession of any material non-public
information about the company’s security” (U.S. Securities & Exchange Commission,
Investor Information). This is evident in the fact that insiders can’t trade immediately before
a piece of information is made public as it skews the market in their favour, and any such
activity is regarded as fraudulent. However, it’s a common knowledge that the trading
volume goes up substantially before any announcement that affects the company’s immediate
price and its future prospects. The earnings announcements by a company are a fairly good
indicator of its short-term prospects as well as the immediate price effect. Therefore, it is
worthwhile to see any trends in short-selling around the earnings announcement dates,
considering that short-sellers account for a good share of the trading volume around events
that are associated with heightened volatility. We also include earning revisions and mergers
& acquisitions announcements in our news announcement analysis as these events also
generate significant volatility around them. The possibility that, some insiders due to their
inability and legal liabilities are tipping off the short-sellers before these announcements,
looms large. Whether these insiders gain anything if at all from this tipping off or not, is out
of scope of this study. Another theory, which has been argued about recently is that, brokers
in the process of execution, leak out private information to their favoured clients in return for
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3 Do short-sellers trade on inside information?
handsome commissions. This study does not chase the trail of events that lead to the passing
on of information to short-sellers. However, we do present firm evidence in favour of our
hypothesis of the front-running phenomenon. And it doesn’t paint a very good picture of the
short sellers as a community.
Front-running refers to the practice of trading in advance of a client, an insider or a broker
with superior information leading to, or in anticipation of a favourable price movement. For
example, some investors might be tipped off in advance about a large impending insider sale
and these investors then sell before the insider expecting to gain from it. Front-running is not
illegal per se as long as the information is acquired in a legitimate way; however, lines do get
blurred a lot of times and law fails to catch up with it, leading to information asymmetry and
bias against other market participants. Front-running was alleged to be one of the prominent
reasons for the collapse of the LTCM (Long-Term Capital Management) in 1998. Some
researchers have in the recent past come out with firm evidence to back up the front-running
theory in the case of LTCM. Fang Cai (2008) finds empirical evidence of market makers’
engagement in front-running against customer orders from “a particular clearing firm (coded
“PI7”) that closely match various features of LTCM’s trades through Bear Stearns”, by using
a trail of audit transactions. Thus, we set out to find similar evidence, if any, of front-running
of insider sales in particular by short-sellers in the US markets using a mix of event studies
and regressions. It is important to mention that this study has been made possible due to the
high-frequency intra-day short-interest data which has been made available by the SEC
recently for the pilot years 2005-2007 under the Regulation SHO.
In this paper, our approach is centred on, firstly, relating short-selling activity to insider-
selling activity, and next, finding out if this relationship is supported by evidence of any
significant surge in short-selling prior to insider selling events around our selected news
announcements. The study isolates only earnings announcements, earnings revisions and
mergers & acquisitions in particular for news announcement analysis since the data on these
announcement dates are readily available for all the firms in our sample and it stands the
same scrutiny in terms of explanatory power as the rest of the event studies. We begin by
running an event study around the insider-selling date to observe any trends in the short-
selling activity before and after the insider sales. We find evidence of abnormal short-sales
peaking significantly just before the designated event, and this is even more striking when we
designate the form-filing day as our event. Then, we segregate these insider sales into large
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and small as a proportion of the company’s shares outstanding as of that date, and run similar
event studies. Our results clearly show that large insider sales are more often preceded by an
abnormal increase in short-selling than small insider sales and this result holds even when we
designate form-filing date as our event. We complement the abnormal short-selling figures
with important statistics on volatility around the insider sale event and the results point in the
same direction; the variance jumps around the event date as there is increased activity around
the insider selling date and this is more pronounced for large sales as compared to small ones.
Our next step is to run a regression explaining the short sales in the estimation window as a
function of contemporaneous and previous day returns, intra-day volatility, daily volume and
whether the short-sale in question is part of the pre-event window or not. Once the evidence
on abnormal short-sales around insider selling date is out, we observe trends in abnormal
short-selling activity around the insider sales before and after news announcement dates and
likewise, run regressions to explain any abnormal behaviour. The collective evidence from all
our empirical work makes our case stronger in suggesting that short-sellers manage to gather
private information about a company and exploit it to front-run insider sales in a systematic
manner.
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5 Do short-sellers trade on inside information?
2. Literature Review
Short-sellers as a community have been the recipient of a great deal of attention and a subject
of debate amongst academicians, regulators, corporations, etc. and extant literature exists on
their ability to generate abnormal returns due to their superior information processing skills.
Researchers are almost unanimous in their praise of short-sellers for their role in correcting
price deviations in the market by making use of contrarian techniques in response to market
overvaluations (Miller, 1977; Harrison and Kreps, 1978; Diamond and Verrecchia, 1987;
Scheinkman and Xiong, 2003, Dechow et al., 2001). While politicians and regulators have a
history of imposing bans on short-selling during periods of crises in the belief of limiting
volatility, they have been slammed across the board and these bans have been regretted in
hindsight.
Empirical research points to the ability of short-selling activity to predict future returns.
Diether et al. (2008) observes that a 10% increase in short-selling, measured as a proportion
of daily volume, is followed by a future decline in returns by 0.94% per month on NYSE.
Short-sellers are considered as informed traders who contribute to market efficiency in a
substantial way. In fact, some theorists have found evidence of prices diverging from
fundamental values when short-selling is constrained (Miller, 1977, Duffie et al., 2002, Hong
et al., 2006). Other researchers have argued that predictability is at best conditional and varies
with stock characteristics. Brent et al. (1990) and Lamont and Stein (2004) find that short
interest is positively related to past returns but does not predict future returns in cross-section
or time-series. Asquith et al. (2005) find return predictability only in the smallest stocks and
report that the effect is stronger in low institutional ownership stocks. As mentioned in the
previous section, while there is near unanimity about the role of short-sellers in contributing
to enhanced market efficiency, consensus still eludes on the subject of source of short-sellers’
information.
Likewise, substantial literature exists on the trading patterns and the information advantage of
corporate insiders. Most of this literature is in concordance with the general belief on the
market that insider activity is the most informed and is a fairly reliable indicator of a firm’s
health and profitability. This class of investors is very often accorded a status higher than the
“sophisticated” short-sellers in terms of forecasting a company’s financial fundamentals.
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6 Do short-sellers trade on inside information?
Jaffe (1974) and Sehyun (1986) document the ability of insider activity to forecast returns as
far as several years in to the future. Ross (1978) and Zhang (2001) conclude that corporate
insiders, through their trades, confirm or contradict the information in public corporate
announcements, which are then viewed by investors as signals who act accordingly in
response. Betzer and Theissen (2005) find that even uninformed outsiders can earn abnormal
profits by mimicking insider transactions. Of late, there has also been a discussion on the
kind of trading activity these corporate insiders engage in. Rozeff & Zaman (1998) study the
trading activity of insiders and infer that it resembles those of contrarians. However, they also
report through their findings that their trading choices are more sophisticated than those of
other contrarian investors. However, insiders are also bound by a variety of corporate laws
and company rules in respect of their trading behaviour and market participation. Insiders are
forbidden from trading on or passing on any confidential material information that has the
potential to skew the market in their favour. Insider trading cases of gigantic proportions have
come to light in the past decade which has in turn brought the debate back to the alleged
nexus between insiders and some class of investors.
There have, in the past, been suggestions linking short-selling to insider sales. Massa et al
(2013) argue that insiders compete with short-sellers in the trading of private information and
that the presence of such competition accelerates the rate at which private information is
disclosed to the market. Chakrabarty and Shkilko (2012) provide empirical evidence on
information leakage in financial markets and examine insider purchases and sales for any
front-running by short-sellers. Similarly, Khan and Liu (2013) also extend their front-running
argument on exact lines, while excluding all insider sales that are in response to news
announcements, and find that short-sellers trade in advance of insiders. However, both these
studies stop short of claiming that short-sellers are trading on private information and confine
their scope to a mere lead-lag relation between short-sales and insider-sales. There is in
general very scarce discussion on the source of this information that facilitates this kind of
front-running.
Several quarters of the academic community have linked this “sophisticated” trading
behaviour of short-sellers to their ability to predict news announcements and decode the
information contained in them faster than everybody else. While there is substantial evidence
of short-sales preceding bad news announcements, there has hardly been an effort to study
short-selling before insider sales that precede news announcements about a firm. Daske et al
(2005) focus on a range of securities traded on NYSE from 2004 to 2005 and find no
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7 Do short-sellers trade on inside information?
evidence of short-sale transactions concentrating prior to only bad news announcements,
ruling out private information as the source of short sale transactions in aggregate. Another
spectrum of studies have stressed on a more focused approach by way of examining changes
in monthly short interest around significant corporate announcements. For example, Dechow,
Sloan, and Sweeney (1996), Griffin (2003), Efendi, Kinney, and Swanson (2005) and Desai,
et al. (2005) find a significant increase in monthly short interest prior to events such as SEC
actions, class action lawsuits, and earnings restatements.
Evidence linking short-sales (particularly those by hedge funds) to subsequent news
announcements is quite extensive. Chague et al. (2013) propose what are called the reaction
and anticipation hypotheses. According to the former, short-sellers possess superior
information processing skills in relation to other market participants which help them trade
ahead of others. On the other hand, the anticipation hypothesis postulates that short-sellers
have access to some kind of superior information, private or otherwise, beforehand and they
exploit this information to make abnormal returns. While both hypotheses are exhaustive in
terms of suggesting the plausible explanations for the scope of short-sellers’ information,
there is scarce discussion on the actual source of information in specific terms. Engelberg et
al. (2012) test these hypotheses using all the corporate news released to the public and find
evidence in favour of the reaction hypothesis but remain inconclusive about the anticipation
hypothesis. Our study relating short sales to insider sales motivated by these news
announcements fits the anticipation hypothesis more than the reaction hypothesis. However,
the study’s main contribution is that it examines short sales around those insider sales which
appear to be motivated by these news announcements rather than around such announcements
themselves.
This study contributes to the existing literature by adding to the insider sales events those
transactions which are not in the conventional form of stocks held by insiders; more
specifically we widen our analysis by including derivative transactions by insiders in our
sample, as companies around the world have significantly begun granting options to their
employees as part of their compensation. Next, as pointed out earlier, we observe trends in
short-selling activity around announcement-related insider sales events using intra-day short
interest data which has been made available by SEC under Regulation SHO for the pilot
years 2005-07.
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8 Do short-sellers trade on inside information?
3. Data Sources & Sample Selection
We restrict our sample period from 2005-06 to test for the hypothesis that short-sellers front-
run insider sales. The data on daily short-sales are obtained from the NYSE TAQ database
from January 2005 to December 2006 which has been made available under the Regulation
SHO. We restrict our sample to 2 years due to constraints of space and convenience since
intra-day data is quite voluminous and the relative benefits of extending our sample fall short
of the relative costs in terms of data cleaning. Data on prices, returns, number of shares
outstanding and volume are taken from the CRSP for the same period in daily frequency. The
earnings and earnings revisions announcement data are sourced from the Thomson Reuters
I/B/E/S database for annual and quarterly periodicities, using ticker codes obtained from our
short-sales and CRSP files. For data on mergers & acquisitions on our sample firms, we use
the Thomson One Banker database. Lastly, we obtain data on insider sales from Thomson
Reuters Insiders Database. For stock transactions, we use the Insiders Data Table 1 data and
for derivative transactions (more specifically, call and put option transactions), we use
Insiders Data Table 2. The data on SEC disclosure dates are likewise obtained from the same
sources respectively.
The TAQ database yields a total of 168,706,872 observations for intra-day frequency. We
begin by deleting all the records which are marked “E” for short-type. Such sales are
excluded from our sample as they represent the short-sales undertaken by market-makers in
the course of their inventory-management function and are marked “exempt”. While previous
studies have included market-makers’ short-sales in their sample, we exclude them to avoid
the criticism that market makers are obliged to short-sell in advance in line with their market-
making function as clients dump their shares around the insider-selling event. Although
market-makers too have been frequently accused of front-running their clients, there is no
clear evidence as to whether market-makers are the ones solely responsible for it, although
they do contribute significantly to the heightened volatility. Therefore, we only keep non-
exempt market trades as part of our study although this might be a possible limitation of our
model. We then proceed by aggregating intra-day sales for a company into daily short-sales
so that the data-matching requirements are met. The organized dataset is then merged with
the daily data obtained from CRSP by symbol and calendar time and we are left with a total
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9 Do short-sellers trade on inside information?
of 409,477 observations. For data on insider sales, the stock-based insider sales transaction
data are first combined with derivative-based transaction data (call and put options, where the
former are disposed of and the latter are acquired) and then refined to keep only such
observations as deemed the most informative about a firm’s fundamentals. Thus we only
keep the CEO’s sales as part of our insider sales and discard all others. Next, we eliminate
any insider sales events that are less than 10 days apart due to overlapping event windows
and where an insider sale is executed over multiple days, we regard only the first day as a
distinct insider-selling event. The same procedures are adopted when we simulate these event
studies for the form-filing event or for the news announcement related insider sales. Finally,
we merge the two datasets respectively using ticker symbols and dates so that our final
datasets are left with 4,313 distinct insider sale events, 4,141 SEC form-filing events, 2,485
news announcement-related insider sale events and 1,268 insider sale events solely preceded
by news announcements.
Table 1 shows our descriptive statistics for the insider sale events in general and the
respective categories. As shown in panel A, the mean average daily short sales in the
estimation window of [-60,-11] before our insider sale event is 0.16% of the number of shares
outstanding whereas the mean event date short sales is 0.18%. Therefore, the average daily
short sale is higher on the event date by about 0.2 percentage points. Similarly, the standard
deviation jumps from 0.15% in the estimation window to 0.23% in the event window,
suggesting increased volatility around the insider-selling event. For insider sales, our sample
has a mean of 0.21% when calculated as a proportion of number of shares outstanding
(approximately the same as demonstrated in Khan and Liu, 2013), whereas it is about 40% as
a proportion of daily trading volume.
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10 Do short-sellers trade on inside information?
4. Methodology
We begin by running the event studies to document the behaviour of short-sales on and
around our insider sale event and form-filing date, as described in Khan and Liu (2011) and
then proceed to conducting regressions to strengthen evidence of front-running. We also
demonstrate this phenomenon by computing and analysing variances for the estimation, pre-
event and post-event windows separately for both execution date and form-filing date.
Finally, we build on our hypothesis by conducting an event study around insider sale events
near news announcements in particular and checking for trends in abnormal short sales. This
event study is also complimented by regressing short-sales on our control variables and the
dummy variable suggesting any heightened abnormal behaviour around the news
announcement-related insider sale events in particular.
4.1. Short-Sales around Insider Sale Date
After finalising our dataset, we designate our insider sale event for a firm, i.e. the day it is
executed, as 0 and test for abnormal short-sales in the [-10, +10] event window. The normal
short-sales are estimated for each distinct firm-event as an average of short sales in the [-60, -
11] window, as demonstrated in Khan and Liu (2011), using the following formula:
E(Sn)=
∑
Sj,n
Where,
E(Sn)= Average daily short-sales in the estimation window [-60, -11],
J= Number of days in the estimation window, i.e. 50,
Sj,n =Short-sales on day j in the event window for the firm-event n, where we define short-
sale as the number of shares shorted as a percentage of number of shares outstanding.
Thus, every insider sale event has now been assigned a normal level of short-sales that occur
prior to the days in the event window. Our next step is to calculate, based on the estimated
expected daily short sales, abnormal short sales in our event window [-10, +10]. This is
calculated as follows:
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11 Do short-sellers trade on inside information?
ei,n=Si,n –E(Sn)
Where,
e= Abnormal short sales
n= Index for firm-event
i=Index for day, i ϵ [-10, +10]
To estimate volatility in the estimation window [-60,-11], we employ the following formula:
σ2E
=
∑
Sj,n-E(Sn)]
2
This statistic is compared against the volatility that results around the insider-selling event
separately for days prior to and days after the event, computed as follows:
σ2B
=
∑
Si,n-E(Sn)]2
Where, i ϵ [-10, 0]
And,
σ2A
=
∑
Si,n-E(Sn)]2
Where, i ϵ [+1, +10]
After these statistics have been calculated, we aggregate them over firm-events to look for
any trends that provide evidence in favour of our hypothesis. The statistic for abnormal sales
in the event window is aggregated across all firm-events for each day separately as follows
and then the results are tabulated:
EN (ei) =
∑
ei,n
Where, n= Index of firm event
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12 Do short-sellers trade on inside information?
Figure 1 sketches the event study graph, and as expected shows a peaking of abnormal short
sales around our event. Look at Table 2 for the abnormal short-sales statistics in our insider
sale event window.
4.2. Short sales around form-filing date
We run an identical event study as above and calculate the same statistics of abnormal sales,
pre-event and post-event volatilities. The form-filing date is designated as day 0 and the event
window is [-10, +10]. By form-filing date, we mean the day the insider reports the sale to the
SEC using Form 4 which is made public in real time.
Figure 3 shows the abnormal short-selling activity in our event window. Statistics on
abnormal short-sales in the form-filing event window are presented in table 4 for reference.
4.3. Short-selling around large and small insider sales
To differentiate the behaviour of short-selling on the basis of size of the insider sale, we
segregate our insider sales sample into large and small where large insider sales correspond to
the top 30 percentile of all insider sales as a proportion of number of shares outstanding and
small insider sales correspond to the bottom 30 percentile. Then, we run separate event
studies for each of them in the same event window of [-10, +10]. Our results are depicted in
figure 2 for both large and small insider sales. For abnormal short-sales figures for our large
and small samples, refer to table 3.
Likewise, we segregate our insider sales on the basis of size as above for the Form 4 filing
date and tabulate our results in Table 5.
4.4. Short-sales around news announcement-led insider sales
Short-sales peaking before the insider sales may be a result of beforehand tip-off about any
significant news announcements which would, upon release, lead to increased trading in the
security in question. Thus, our methodology goes a step further to analyse the behaviour of
short-sales around those insider sales in particular which surround significant news
announcements. We filter our insider sale events, retaining only such events that are either
preceded or followed by our class of news announcements in the 10 day window.
Specifically, first we designate the news announcement related insider sale execution date as
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13 Do short-sellers trade on inside information?
the event day, i.e. day 0, and run a similar event-study in the event window [-10, +10]. Later,
we run a similar event study only around those insider sales which are preceded by these
news announcements in the 10 day window. The results are summarised in tables 6 and 7
respectively.
4.5. Regression Studies-the alternate method
Our alternate approach is centred around regressing the short-sales on a day on some factors
namely, the contemporaneous and previous day returns, intra-day volatility and volume
respectively for our entire sample of 2 years. To single out the effect of impending insider
sale, we add a dummy variable DAY which is 1 in 10 days prior to any insider-selling event,
[-10, 0] and 0 for all the other days. The regression model is specified as follows:
Si,n = αn + β1RETi,n + β2RETi-1,n + β3VOLi,n + β4VOLi-1,n + β5VARi,n +
β6VARi-1,n + β7DAYi + ϵi,n
Where,
Si,n= Short-sales on day i for the firm-event n,
RETi,n=Contemporaneous return on day i,
RETi-1,n= Previous day return,
VOLi,n= Volume of shares traded on day i,
VOLi-1,n= Volume of shares traded the previous day,
VARi,n= Intra-day price-volatility on day i,
VARi-1,n= Intra-day price-volatility on the previous day,
DAYi= 0 if i ϵ [-∞, -11] and 1 if i ϵ [-10, 0],
We report the results of this regression in panel A of table 8.
For the sake of precision and robustness to changes in the number of days in the pre-event
window, we now run an identical regression, except that the dummy variable DAY is now
assigned the value of 1 in 5 days prior to the insider-selling event, [-5, 0] and 0 for all other
days.
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Si,n = αn +β1RETi,n + β2RETi-1,n + β3VOLi,n + β4VOLi-1,n + β5VARi,n +
β6VARi-1,n + β7DAYi + ϵi,n
Where,
Si,n= Short-sales on day i for the firm-event n,
RETi,n=Contemporaneous return on day i,
RETi-1,n= Previous day return,
VOLi,n= Volume of shares traded on day i,
VOLi-1,n= Volume of shares traded the previous day,
VARi,n= Intra-day price-volatility on day i,
VARi-1,n= Intra-day price-volatility on the previous day,
DAYi= 0 if i ϵ [-∞, -6] and 1 if i ϵ [-5, 0]
Panel B of table 8 reports the results derived from this regression.
Our next regression involves adding an interaction term dummy variable SIZE*DAY where
the variable SIZE takes the value of 1 if the impending insider sale is large and 0 if it is small.
In this manner, we are able to distinguish large sales from small ones on the basis of whether
large insider sales get front-run more often than small ones in the before-event window. We
only run this regression for those days for which the impending insider-sale is either
classified as small or large and discard all others. Again, we run two separate regressions here
as above for the [-10, 0] and [-5, 0] windows for our dummy variable, DAY.
Si,n = αn +β1RETi,n + β2RETi-1,n + β3VOLi,n + β4VOLi-1,n + β5VARi,n +
β6VARi-1,n + β7SIZEi,n*DAYi + ϵi,n
Si,n= Short-sales on day i for the firm-event n,
RETi,n=Contemporaneous return on day i,
RETi-1,n= Previous day return,
VOLi,n= Volume of shares traded on day i,
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VOLi-1,n= Volume of shares traded the previous day,
VARi,n= Intra-day price-volatility on day i,
VARi-1,n= Intra-day price-volatility on the previous day,
DAYi= 0 if i ϵ [-∞, -11 or -6] and 1 if i ϵ [-10 or -5, 0],
SIZEi,n=0 if the impending insider sale is classified as small and 1 if large.
Table 9 shows the results of these regressions.
Our final regression for news announcement-led insider sale events is concerned with
regressing the short-sales on a day on the control variables as mentioned earlier. In addition,
we also introduce the interaction term ANN*DAY, where ANN is defined as 1 for all short-
sales around news announcement-led insider sales (i.e., within the 10 day event window) and
0 otherwise; DAY is 1 in the window [-10, 0], i.e. 10 days prior to and on the insider-selling
date and 0 otherwise. We repeat this procedure by redefining DAY as 1 for days in the
window [-5, 0], i.e. 5 days prior to and on the insider-selling date, and 0 otherwise (table 10).
Si,n = αn +β1RETi,n + β2RETi-1,n + β3VOLi,n + β4VOLi-1,n + β5VARi,n +
β6VARi-1,n + β7ANNn*DAYi + ϵi,n
Where,
Si,n= Short-sales on day i for the firm-event n,
RETi,n=Contemporaneous return on day i,
RETi-1,n= Previous day return,
VOLi,n= Volume of shares traded on day i,
VOLi-1,n= Volume of shares traded the previous day,
VARi,n= Intra-day price-volatility on day i,
VARi-1,n= Intra-day price-volatility on the previous day,
DAYi,= 0 if i ϵ [-∞, -11 or -6] and 1 if i ϵ [-10 or -5, 0]
ANNn= 1 if the insider sale event is led by news announcement, 0 otherwise.
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5. Results
5.1. Short-selling and Insider Sales
The results from our event study around the insider-selling date are indicative of what we
hypothesized earlier; short-sales do peak significantly before an insider sale in our sample. As
reported in table 2 and evident from figure 1, we can easily infer that short-sellers on average
front-run insiders in a significant manner. The t-stats reported for abnormal sales in our event
window are significant at 99% confidence level for days -4, -3, -2, -1, 0 and +1. Thus, short-
sales rise abnormally 4 days prior to the insider-selling event and peak on days -2 and -1,
suggesting prior knowledge of impending insider sale. As reported, abnormal short-sales in
the after-event window record consistently negative values except on day 1, implying that
short-sellers later close out their positions to profit from front-running.
The volatilities calculated for the estimation, pre-event and post-event windows also show the
same trend. The volatility of short-sales jumps from 0.02329 in the estimation window of [-
60, -11] to 0.03263 in the pre-event window of [-10, 0] and 0.02817 in the after-event
window of [+1, +10], implying heightened short-selling activity in the event window, which
is even more pronounced for days immediately before the insider-selling event. These values
were found to be significantly different from the estimation window volatility after
conducting the relevant F-tests.
We also report the results from the regression where daily short-sales are regressed on some
control variables and the dummy variable DAY, which differentiates the short-selling in the
pre-event window from that on any other normal day. As shown in table 8, the coefficient for
the DAY variable is found to be positive and significant at the 99% confidence level. Thus,
short-selling is found to be significantly higher in the pre-event window of [-10, 0] compared
to other days in our sample. The regression also returns significant coefficients for our
control variables, validating our methodology.
When we restrict the pre-event window to [-5, 0] and redefine the DAY variable as 1 for only
5 days prior to the insider-selling event, we find even more striking evidence of higher
abnormal short-selling preceding the insider sale. The coefficient of 0.0067953 for DAY[-5, 0]
is significantly higher than the coefficient of 0.0045877 for DAY[-10, 0].
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5.2. Short-selling and Form 4 filing
On conducting the event study designating the form filing date as our event, we observe
concurrent trends as in our insider sales event study. The SEC makes it mandatory for
corporate insiders to file their trades with it within two days of execution which are made
public in real time. Our event study around the SEC filing date shows that abnormal short-
selling surges significantly in the pre-event window, specifically on day -6 and peaks on days
-4 and -2 before the form-filing date. The t-statistics are significant at the 99% confidence
level for all these days. The -2 day before the form-filing day is effectively the day these
insider sales are executed. Therefore, this abnormal peaking of short-sales fits perfectly into
our hypothesis of insiders being systematically front-run by short-sellers in our sample.
We continue our analysis for the form-filing date by reporting the volatilities for estimation,
pre-event and post-event windows as above. The volatility of short-sales jumps from 0.02373
in the corresponding estimation window to 0.03244 in the pre-event window of [-10, 0], and
0.02851 in the post-event window of [+1, +10], making our hypothesis of front-running
stronger. While the pre-event window volatility is found to be significantly different from the
estimation window volatility, the post-event window volatility is not significantly different.
5.3. Short-sales and Insider Sale Size
We hypothesized that, large insider sales, due to their information content and potential
profitability relative to the costs of detection, are more likely to get front-run than small
insider sales. On segregating large sales from small ones and running an event study around
the insider selling event, we find that short sales peak significantly before a large insider sale
as seen in figure 2. The t-statistics support our findings empirically for days -3, -2 and -1 at
the 99% confidence level and for the day -4 at 90% level. For small insider sales, t-statistics
are found insignificant, as expected and even the significant ones show much less abnormal
short-selling when compared to large insider sales sample, as depicted in figure 2. Thus, our
results for the entire sample, which show a clear peaking in short-selling activity before the
event, are led by the large-insider sales being front-run than the small ones.
For the SEC filing date, we run similar event studies for large and small insider sales
separately and find parallel evidence. While abnormal short-sales peak significantly 2 days
prior to the form-filing date for the large insider sales, no such trends are observed for our
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corresponding small insider sales sample. The t-stats show significance for abnormal short-
sales before large insider sales at the 99% confidence level whereas abnormal short-sales
before small insider sales are found insignificant even at the 90% confidence level.
Therefore, we can conclude that large insider sales, being more profitable potentially, are
more likely to be preceded by heightened short-selling than small insider sales.
To avoid any criticism of methodology bias, we repeat our analysis by running a regression to
find out whether the size of the impending insider sale size affects short-selling behaviour
before the insider selling event. The interaction term SIZE*DAY is of interest here which
embodies the differential impact of large insider sale on the short-sales in our pre-event
window. As depicted in table 9, the SIZE*DAY variable has a positive coefficient which is
significant at the 99% confidence level and therefore, proves our hypothesis mentioned
above.
Similarly, when the pre-event window is confined to [-5, 0], we find a significantly positive
coefficient for our SIZE*DAY variable which is higher than the one found for the [-10, 0]
window. Short-selling in the days immediately before the insider sale date is higher indeed
when the impending insider sale is large as a proportion of the firm’s value. The higher
profitability argument is based on the fact that a large insider sale is ensued by a larger
favourable price movement and a higher volatility after the event as compared to a smaller
insider sale.
5.4. Short selling and news announcements
The results of our event study and regression for new announcement-led insider sales confirm
our earlier findings of significant front-running by short-sellers and also, importantly, ascribe
a motive for this phenomenon. When we designate the news announcement-related insider
sale execution date as the event date for the firms in our sample, we observe that abnormal
short-sales start peaking 2 days in advance of the event and the t-statistics computed show
significance at the 95% confidence level. In the post-event window, abnormal short-sales
decline and the t-statistics also return insignificant values.
For the event study around only those insider sales that precede our subset of news
announcements, we observe that short-sales spike abnormally 4 days before the execution
date and remain high until the post-event window. The t-statistics are significant at the 99%
confidence level.
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To complete our analysis, we regress short sales on a day on the same control variables as
above and the ANN*DAY variable where ANN is defined as 1 for days preceding news
announcement-led insider sales and 0 elsewhere. As shown in table 10, the coefficient for the
ANN*DAY variable is positive and significant at the 99% confidence level, suggesting that
short-sales jump much before the news announcements and short-sellers trade ahead of
insiders even though the information is still not public. When we confine the DAY variable to
1 in the pre-event window of only [-5, 0], our results are boosted by an even higher
coefficient of 0.0172143 which is significantly higher than the coefficient of 0.0095028 for
the [-10, 0] event window.
The news announcement analysis, together with our insider sale and form-filing analyses,
leads us to infer that short-sellers systematically trade ahead of insiders for profit motives and
this phenomenon exacerbates when the impending insider sale is relatively large as a
proportion of the firm’s market value. The heightened short-selling in advance of news
announcement-led insider sales in particular bridges the gap in our understanding of the
reasons for this behaviour of short-sellers. Thus, while insiders may be restricted from selling
before any significant news is announced, there is always the chance of their being front-run
by short-sellers. To what extent this front-running is facilitated by insiders themselves is a
matter of dispute; however, their legal liabilities and simultaneous privileged access to
private information puts them first in the list of possible sources of short-sellers’ information.
Also, our pre-announcement analysis for insider sales before news announcements rules out
the possibility of short-sellers acting on public information faster than insiders, since this
information is not public yet. Thus, short-sellers trading ahead of insiders before any news
announcements have access to inside information which manifests later in the form of public
announcement after the insider sale event.
This study does not take a position on as to how short-sellers obtain this information which is
strictly private since it’s clearly the domain of the regulatory authorities. However, we can
confidently make the claim that short-sellers are trading well in advance of the corporate
insiders who are touted as the most informed market participants generally. And, the reasons
they are doing it for, do not appear very encouraging. (c)
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20 Do short-sellers trade on inside information?
6. Conclusion
The study attempts to shed light on the source of short-sellers’ information using event
studies and regressions. We find astounding evidence of insider sales being preceded by
abnormal short sales which peak 2 days before the insider sale is even executed, let alone
being made public. When we treat the SEC form filing day as our event, i.e. the day these
sales are made public, we get evidence on similar lines; short-sales start peaking 4 days
before the form-filing event, implying that short-sellers have access to inside information on
average that they use to front-run insiders systematically. We also prove that large insider
sales (top 30% percentile as a proportion of number of shares outstanding), are more likely to
be front-run than small insider sales (bottom 30% as a proportion of number of shares
outstanding). Large insider sales possess a greater degree of information content and their
front-running has the potential to translate into even greater profitable trades after short-
sellers have bet their money on them. Our results hold when we analyse the behaviour of
short-sales around the form-filing date for large and small sales separately. The regression
studies undertaken for our purpose strengthen our argument of front-running further as the
dependent variable of short-sales is higher on pre-event days of the execution and form-filing
dates. The insider sale size argument also proves credible when we segregate our insider sales
into small and large and run another regression.
The results from the news announcement analysis prove a shot in the arm for our study. As
shown earlier, short-sales peak before the insider sales which are motivated by news
announcements for the firms in our sample. When these short-sales are regressed on the
interaction dummy representing news announcement-motivated insider sales, after
controlling for usual explanatory variables, namely daily returns, intra-day volatility and
volume, we observe that short-sales are significantly higher in the days preceding the news
announcement-led insider sales. The results are robust and in fact, more damning when we
confine our pre-event window to just 5 days before the execution dates. When the news
announcement analysis is confined to only those insider sales that are later followed by our
subset of news announcements, we get clear evidence of similar front-running, thereby
eliminating the alternative explanation of short-sellers reacting faster than insiders to recent
public announcements, since the information they are acting on is not yet public. The news
announcement analysis, in conjunction with the execution date and SEC form-filing date
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analyses provides empirical strength to our hypothesis of short-sellers exploiting private
information for profit motives to front-run insiders in a significant manner, with or without
the knowledge of these insiders. Since insiders are banned from trading on private
information before any major news announcement on their own, our evidence on short-
selling peaking before these announcements points towards only one direction; short-sellers
obtain inside information from these very corporate insiders in an illegal manner that is unfair
towards other market participants. Several studies have hinted at insiders timing their trades
and manipulating earnings announcement dates for their advantage, often in collusion with
other market participants (Yong-Chul Shin and Weimin Wang, 2011). This study is limited in
its scope of providing any definitive proof about the mechanics of how the information is
exchanged between short-sellers and insiders; this is the realm of the regulatory authorities.
However, it does add significantly to the nascent literature on the source of short-sellers’
information. As a solution to this problem, the financial regulatory bodies such as the SEC
should monitor these trades carefully and make disclosures about insider trades more
frequently so that price discovery is fair as well as transparent.
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References
Asquith, P., Pathak, P. and Ritter, J. (2005). Short interest, institutional ownership, and stock
returns. Journal of Financial Economics, 78(2), pp.243--276.
Beber, A. and Pagano, M. (2013). Short-Selling Bans Around the World: Evidence from the
2007--09 Crisis.The Journal of Finance, 68(1), pp.343--381.
Betzer, A. and Theissen, E. (2009). Insider trading and corporate governance: The case of
Germany.European Financial Management, 15(2), pp.402--429.
Boehmer, E., Jones, C. and Zhang, X. (2008). Which shorts are informed?. The Journal of
Finance, 63(2), pp.491--527.
Brent, A., Morse, D. and Stice, E. (1990). Short interest: Explanations and tests. Journal of
Financial and Quantitative Analysis, 25(02), pp.273--289.
Cai, F. (2003). Was there front running during the LTCM crisis.
Chague, F., De-Losso, R., DE GENARO, A. and GIOVANNETTI, B. (2013). Short Selling
and Inside Information.
Chakrabarty, B. and Shkilko, A. (n.d.). Information Leakages and Learning in Financial
Markets.
Christophe, S., Ferri, M. and Angel, J. (2004). Short-selling prior to earnings
announcements. The Journal of Finance, 59(4), pp.1845--1876.
Clacher, I., Hillier, D. and Lhaopadchan, S. (2009). Corporate insider trading: A literature
review. Spanish Journal of Finance and Accounting/Revista Espa\~nola de
Financiaci\'on y Contabilidad, 38(143), pp.373--397.
Damodaran, A. and Liu, C. (1993). Insider trading as a signal of private information. Review
of Financial Studies, 6(1), pp.79--119.
DASKE, H., RICHARDSON, S. and TUNA, \. (n.d.). Do short sale transactions precede bad
news events? New evidence from NYSE daily data.
(c) Cop
yrigh
t of A
rjun C
hhab
ra
23 Do short-sellers trade on inside information?
Dechow, P., Hutton, A., Meulbroek, L. and Sloan, R. (2001). Short-sellers, fundamental
analysis, and stock returns. Journal of Financial Economics, 61(1), pp.77--106.
Desai, H., Ramesh, K., Thiagarajan, S. and Balachandran, B. (2002). An investigation of the
informational role of short interest in the Nasdaq market. The Journal of Finance, 57(5),
pp.2263--2287.
Diamond, D. and Verrecchia, R. (1987). Constraints on short-selling and asset price
adjustment to private information. Journal of Financial Economics, 18(2), pp.277--311.
Diether, K., Lee, K. and Werner, I. (2009). Short-sale strategies and return
predictability. Review of financial Studies, 22(2), pp.575--607.
Dymke, B. and Walter, A. (2008). Insider Trading in Germany—Do Corporate Insiders
Exploit Inside Information?. BuR-Business Research, 1(2), pp.188--205.
Efendi, J. (2004). Can Short Sellers Predict Accounting Restatements and Foresee Their
Severity?.
Engelberg, J., Reed, A. and Ringgenberg, M. (2012). How are shorts informed?: Short sellers,
news, and information processing. Journal of Financial Economics, 105(2), pp.260--
278.
Griffin, P. (2003). A league of their own? Financial analysts' responses to restatements and
corrective disclosures. Journal of Accounting, Auditing \& Finance, 18(4), pp.479--517.
Harrison, J. and Kreps, D. (1978). Speculative investor behavior in a stock market with
heterogeneous expectations. The Quarterly Journal of Economics, pp.323--336.
Hong, H. and Stein, J. (1999). A unified theory of underreaction, momentum trading, and
overreaction in asset markets. The Journal of Finance, 54(6), pp.2143--2184.
Jaffe, J. (1974). The effect of regulation changes on insider trading. The Bell Journal of
Economics and Management Science, pp.93--121.
Ke, B., Huddart, S. and Petroni, K. (2003). What insiders know about future earnings and
how they use it: Evidence from insider trades. Journal of Accounting and Economics,
35(3), pp.315--346.
(c) Cop
yrigh
t of A
rjun C
hhab
ra
24 Do short-sellers trade on inside information?
Khan, M. and Lu, H. (2013). Do short sellers front-run insider sales?. The Accounting
Review, 88(5), pp.1743--1768.
Lamont, O. (2004). Go down fighting: Short sellers vs. firms.
Leung, T., Rui, O. and Wang, S. (2009). Short interest, insider trading, and stock
returns. Insider Trading, and Stock Returns (February 12, 2009).
Markham, J. (1988). Front-Running-Insider Trading under the Commodity Exchange
Act. Cath. UL Rev., 38, p.69.
Massa, M., Qian, W., Xu, W. and Zhabg, H. (2013). Competition of the Informed: Does the
Presence of Short Sellers Affect Insider Selling?.
Miller, E. (1977). Risk, uncertainty, and divergence of opinion. The Journal of Finance,
32(4), pp.1151--1168.
Purnanandam, A. and Seyhun, H. (2011). Do Short Sellers Trade on Private Information or
False Information?. Do Short Sellers Trade on Private Information or False Information.
Rozeff, M. and Zaman, M. (1988). Market efficiency and insider trading: New
evidence. Journal of Business, pp.25--44.
Scheinkman, J. and Xiong, W. (2003). Overconfidence and speculative bubbles. Journal of
political Economy, 111(6), pp.1183--1220.
Seyhun, H. (1986). Insiders' profits, costs of trading, and market efficiency. Journal of
Financial Economics, 16(2), pp.189--212.
Shin, Y. and Wang, W. (2011). The Timing of Insider Trades around Earnings
Announcements: Evidence from CEOs, CFOs, and COOs. International Review of
Accounting, Banking \& Finance, 3(1).
Wearing, R. and Li, C. (n.d.). SHORT SELLERS: VILLAINS OR
SCAPEGOATS?. CORPORATE OWNERSHIP \& CONTROL, p.391.
Zhang, G. (2001). Regulated managerial insider trading as a mechanism to facilitate
shareholder control.Journal of Business Finance \& Accounting, 28(1-2), pp.35--62.
(c) Cop
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Appendix
Table 1: Descriptive Statistics
Panel A reports descriptive statistics for the full sample of 4,331 insider sales events; Panel B
reports descriptive statistics on insider sales events which are classified as small, specifically
the bottom 30 percentile of our full insider sales sample; Panel C reports descriptive statistics
on insider sales events which are classified as large, specifically the top 30 percentile of our
full insider sales sample; Panel D reports summary statistics on those insider sales events
which are surrounded by news announcements within the 10-day window on either side;
Panel E reports summary statistics on those insider sales events only which precede news
announcements within the 10-day window. Event Date Short Sales refers to the proportion of
short sales as a percentage of shares outstanding on the insider sale execution day; insider
sales/shares outstanding is the number of shares sold by insiders as a percentage of number of
shares outstanding; insider sales/trading volume is the number of shares sold by insiders as a
percentage of daily trading volume; shares outstanding is the number of shares outstanding in
thousands; average daily short sales is the mean short sales as a proportion of number of
shares outstanding in the estimation window of [-60, -11] before the insider sale event.
Panel A: Descriptive Statistics for Insider Sale Events
Mean Q1 Median Q3 StdDev
Event Date Short Sales (%) 0.18 0.058 0.11 0.21 0.23
Insider Sales/Shares Outstanding (%) 0.21 0.003 0.024 0.102 1.71
Insider Sales/Trading Volume (%) 39.59 0.46 3.73 15.21 343.2
Shares Outstanding (‘000) 268,288 39,687 76,383 194,302 776,390
Average Daily Short Sales (%) 0.16 0.07 0.11 0.20 0.15
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Panel B: Descriptive Statistics for Small Insider Sale Events
Mean Q1 Median Q3 StdDev
Event Date Short Sales (%) 0.14 0.051 0.09 0.17 0.16
Insider Sales/Shares Outstanding (%) 0.0013 0.000099 0.0007 0.002 0.0015
Insider Sales/Trading Volume (%) 0.3 0.02 0.116 0.37 0.56
Shares Outstanding (‘000) 506,021 57,433 119,262 194,302 1,263,017
Average Daily Short Sales (%) 0.14 0.06 0.1 0.16 0.14
Panel C: Descriptive Statistics for Large Insider Sale Events
Mean Q1 Median Q3 StdDev
Event Date Short Sales (%) 0.22 0.07 0.13 0.25 0.28
Insider Sales/Shares Outstanding (%) 0.65 0.12 0.20 0.45 3.08
Insider Sales/Trading Volume (%) 123.3 14.68 28.3 64.57 618.8
Shares Outstanding (‘000) 101,121 27,513 50,799 104,599 200,473
Average Daily Short Sales (%) 0.19 0.08 0.13 0.24 0.17
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Panel D: Descriptive Statistics for News Announcement-related Insider Sale Events
Mean Q1 Median Q3 StdDev
Event Date Short Sales (%) 0.19 0.06 0.11 0.22 0.26
Insider Sales/Shares Outstanding (%) 0.24 0.004 0.027 0.11 2.17
Insider Sales/Trading Volume (%) 42.27 0.61 3.98 16.25 408.1
Shares Outstanding (‘000) 277,708 39,687 78,530 204,948 777,829
Average Daily Short Sales (%) 0.16 0.07 0.11 0.20 0.15
Panel E: Descriptive Statistics for Insider Sale Events preceding News Announcements
Mean Q1 Median Q3 StdDev
Event Date Short Sales (%) 0.18 0.06 0.105 0.21 0.25
Insider Sales/Shares Outstanding (%) 0.26 0.003 0.026 0.12 1.95
Insider Sales/Trading Volume (%) 20.28 12.16 18.14 25.75 11.48
Shares Outstanding (‘000) 274,004 37,479 72,697 202,315 778,955
Average Daily Short Sales (%) 0.15 0.07 0.11 0.18 0.14
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Table 2: Abnormal Short Sales around all insider sales
Table 2 reports the results of our event study around all our insider-selling events in the [-10,
+10] event window where the execution date is designated as day 0. Abnormal SS refers to
the short sales over and above the average short sales in the estimation window of [-60, -11].
*, **, *** denotes two-tailed statistical significance for our abnormal short sales from 0 at
10%, 5% and 1%, respectively. Figure 1 shows these results graphically.
Event Day, i Abnomal SS t-stat Event Day, i Abnomal SS t-stat
-10 0.0016% 0.64 1 0.0078% 3.02***
-9 0.0008% 0.34 2 0.0025% 1.01
-8 0.0021% 0.84 3 -0.0003% -0.123
-7 0.0010% 0.36 4 -0.0034% -1.41
-6 -0.0016% -0.65 5 -0.0064% -2.74***
-5 0.0020% 0.75 6 -0.0017% -0.62
-4 0.0075% 2.78*** 7 -0.0043% -1.71*
-3 0.0102% 3.43*** 8 -0.0043% -1.63
-2 0.0192% 5.78*** 9 -0.0065% -2.52**
-1 0.0185% 6.39*** 10 -0.0070% -2.69***
0 0.0150% 5.25***
Figure 1:
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29 Do short-sellers trade on inside information?
Table 3: Abnormal Short Sales and Insider Sales Size
Panel A (panel B) reports the results of our event study around small (large) insider-selling
events, i.e. the bottom (top) 30 percentile as a proportion of number of shares outstanding, in
the [-10, +10] event window where the execution date is designated as day 0. Abnormal SS
refers to the short sales over and above the average short sales in the estimation window of [-
60, -11]. *, **, *** denotes two-tailed statistical significance for our abnormal short sales
from 0 at 10%, 5% and 1%, respectively. Figure 2 shows these results graphically.
Panel A: Abnormal Short Sales for Small Insider Sales Sample
Event Day, i Abnomal SS t-stat Event Day, i Abnomal SS t-stat
-10 -0.0059% -1.75* 1 -0.0042% -1.21
-9 -0.0035% -0.87 2 -0.0018% -0.43
-8 -0.0019% -0.52 3 -0.0064% -1.57
-7 -0.0010% 0.28 4 -0.0038% -1.02
-6 0.0022% 0.56 5 -0.0041% -1.08
-5 0.0026% 0.65 6 0.0025% 0.45
-4 0.0001% 0.035 7 -0.0027% -0.67
-3 -0.0005% -0.09 8 -0.0058% -1.46
-2 0.0036% 0.88 9 -0.0110% -2.86***
-1 0.0080% 2.04** 10 -0.0116% -3.09***
0 0.0024% 0.69
Panel B: Abnormal Short Sales for Large Insider Sales Sample
Event Day, i Abnomal SS t-stat Event Day, i Abnomal SS t-stat
-10 0.0040% 0.81 1 0.0130% 2.4**
-9 0.0101% 0.19 2 -0.0001% -0.019
-8 0.0052% 0.91 3 0.0022% 0.42
-7 0.0005% 0.11 4 -0.0051% -1.06
-6 -0.0031% -0.64 5 -0.0122% -2.7***
-5 -0.0023% -0.45 6 -0.0121% -2.48**
-4 0.0096% 1.82* 7 -0.0045% -0.81
-3 0.0190% 3.32*** 8 -0.0040% -0.68
-2 0.0374% 5.06*** 9 -0.0055% -1.05
-1 0.0374% 5.34*** 10 -0.0063% -1.19
0 0.0266% 4.31***
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30 Do short-sellers trade on inside information?
Figure 2:
Table 4: Abnormal Short Sales for SEC form-filing date
Table 4 reports the results of our event study around all our SEC form-filing events in the [-
10, +10] event window where the form-filing date (also, the date the insider sale is made
public) is designated as day 0. Abnormal SS refers to the short sales over and above the
average short sales in the estimation window of [-60, -11]. *, **, *** denotes two-tailed
statistical significance for our abnormal short sales from 0 at 10%, 5% and 1%, respectively.
Figure 3 shows these results graphically.
Event Day, i Abnomal SS t-stat Event Day, i Abnomal SS t-stat
-10 -0.0008% -0.31 1 0.0019% 0.71
-9 -0.0012% -0.503 2 -0.0049% -1.93*
-8 -0.0012% -0.43 3 -0.0038% -1.18
-7 0.0012% 0.45 4 -0.0091% -3.69***
-6 0.0060% 2.1** 5 -0.0062% -2.47**
-5 0.0122% 3.91*** 6 -0.0023% -0.798
-4 0.0159% 5.06*** 7 -0.0039% -1.38
-3 0.0138% 5.09*** 8 -0.0072% -2.61***
-2 0.0158% 5.18*** 9 -0.0037% -1.42
-1 0.0128% 4.5*** 10 -0.0082% -3.37***
0 0.0061% 2.33**
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Figure 3:
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32 Do short-sellers trade on inside information?
Table 5: Abnormal Short Sales and Insider Sales Size for form-filing events
Panel A (panel B) reports the results of our event study around form-filing days for small
(large) insider-selling events, i.e. the bottom (top) 30 percentile as a proportion of number of
shares outstanding, in the [-10, +10] event window where the form-filing date is designated
as day 0. Abnormal SS refers to the short sales over and above the average short sales in the
estimation window of [-60, -11]. *, **, *** denotes two-tailed statistical significance for our
abnormal short sales from 0 at 10%, 5% and 1%, respectively. Figure 4 shows these results
graphically.
Panel A: Abnormal Short Sales for Small Insider Sales Sample (SEC Form-filing date)
Event Day, i Abnomal SS t-stat Event Day, i Abnomal SS t-stat
-10 -0.0060% -1.6 1 -0.0064% -1.61
-9 -0.0014% -0.39 2 -0.0069% -1.74*
-8 0.0015% -0.39 3 -0.0048% -1.24
-7 0.0019% 0.52 4 -0.0071% -1.7*
-6 0.0005% 0.12 5 -0.0061% -1.51
-5 0.0080% 1.45 6 0.0006% 0.14
-4 0.0001% 0.03 7 -0.0017% -0.4
-3 0.0051% 1.24 8 -0.0106% -2.21**
-2 0.0044% 1.16 9 0.0015% 0.3
-1 -0.0009% -0.24 10 -0.0007% -0.16
0 -0.0021% -0.57
Panel B: Abnormal Short Sales for Large Insider Sales Sample (SEC Form-filing date)
Event Day, i Abnomal SS t-stat Event Day, i Abnomal SS t-stat
-10 0.0042% 0.68 1 0.0032% 0.57
-9 0.0021% 0.4 2 -0.0062% -1.27
-8 -0.0018% -0.36 3 0.0003% 0.05
-7 -0.0023% 0.44 4 -0.0174% -3.87***
-6 0.0020% 0.39 5 -0.0134% -2.95***
-5 0.0152% 2.55** 6 -0.0063% -1.04
-4 0.0368% 4.78*** 7 -0.0043% -0.7
-3 0.0227% 3.97*** 8 -0.0073% -1.31
-2 0.0290% 4.21*** 9 -0.0019% -0.38
-1 0.0231% 3.56*** 10 -0.0148% -2.94***
0 0.0076% 1.48
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Figure 4:
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34 Do short-sellers trade on inside information?
Table 6: Abnormal Short Sales around News Announcement-related Insider Sales
Table 6 reports the results of our event study around those insider-selling events which are
surrounded by news announcements in the [-10, +10] event window where the execution date
is designated as day 0. Abnormal SS refers to the short sales over and above the average short
sales in the estimation window of [-60, -11]. *, **, *** denotes two-tailed statistical
significance for our abnormal short sales from 0 at 10%, 5% and 1%, respectively. Figure 5
shows these results graphically.
Event Day, i Abnomal SS t-stat Event Day, i Abnomal SS t-stat
-10 0.0032% 0.89 1 0.0173% 4.48***
-9 0.0057% 1.63 2 0.0065% 2.07**
-8 0.0085% 2.34*** 3 0.0046% 1.33
-7 0.0063% 1.56 4 0.0018% 0.54
-6 0.0062% 1.73* 5 -0.0040% -1.25
-5 0.0104% 2.58*** 6 0.0005% 0.13
-4 0.0204% 5.11*** 7 -0.0035% -1.08
-3 0.0269% 6.52*** 8 -0.0018% -0.51
-2 0.0451% 8.55*** 9 -0.0062% -1.8*
-1 0.0384% 8.7*** 10 -0.0044% -1.22
0 0.0280% 6.67***
Figure 5:
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35 Do short-sellers trade on inside information?
Table 7: Abnormal Short Sales around Insider Sales preceding News Announcement
Table 7 reports the results of our event study around those insider-selling events which
precede news announcements, in the [-10, +10] event window where the execution date is
designated as day 0. Abnormal SS refers to the short sales over and above the average short
sales in the estimation window of [-60, -11]. *, **, *** denotes two-tailed statistical
significance for our abnormal short sales from 0 at 10%, 5% and 1%, respectively. Figure 6
shows these results graphically.
Event Day, i Abnomal SS t-stat Event Day, i Abnomal SS t-stat
-10 0.0068% 1.48 1 0.0245% 5.13***
-9 0.0067% 1.39 2 0.0201% 4.38***
-8 0.0026% 0.65 3 0.0175% 3.74***
-7 0.0003% 0.08 4 0.0159% 3.16***
-6 -0.0029% -0.73 5 0.0118% 2.62***
-5 -0.0024% -0.59 6 0.0161% 2.98***
-4 0.0082% 1.81* 7 0.0127% 2.94***
-3 0.0051% 1.28 8 0.0133% 2.77***
-2 0.0015% 3.01*** 9 0.0085% 1.83*
-1 0.0247% 5.21*** 10 0.0095% 1.86*
0 0.0291% 5.07***
Figure 6:
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36 Do short-sellers trade on inside information?
Table 8: Regression results for Short sales and Insider Sales
Panel A (Panel B) shows the regression statistics when daily short sales are regressed on the
dummy variable DAY (DAY1), where DAY (DAY1) is 1 for the pre-event window of [-10,
0] ([-5,0]) and 0 elsewhere, and the other control variables. “Retx” refers to the daily return;
“retx1” refers to the lagged return; “lnvol” is the log of daily volume traded; “lnvol1” is the
log of volume traded a day before; “sd2” is the intra-day price volatility of the security on
that day; “sd12” refers to the previous day intra-day price volatility; “day” is a dummy
variable which is 1 in the pre-event window of [-10,0] and 0 otherwise; “day1” is a dummy
variable which is 1 in the pre-event window of [-5, 0] and 0 otherwise; “_cons” refers to the
intercept of the regression equation.
Panel A:
Panel B:
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37 Do short-sellers trade on inside information?
Table 9: Regression results for Short Sales and Insider Sale Size
Panel A (Panel B) shows the regression statistics when daily short sales are regressed on the
interaction dummy variable SIZE*DAY (SIZE*DAY1), where DAY (DAY1) is 1 for the
pre-event window of [-10, 0] ([-5,0]) and 0 elsewhere, and the other control variables. “Retx”
refers to the daily return; “retx1” refers to the lagged return; “lnvol” is the log of daily
volume traded; “lnvol1” is the log of volume traded a day before; “sd2” is the intra-day price
volatility of the security on that day; “sd12” refers to the previous day intra-day price
volatility; “day” is a dummy variable which is 1 in the pre-event window of [-10,0] and 0
otherwise; “day1” is a dummy variable which is 1 in the pre-event window of [-5, 0] and 0
otherwise; “_cons” refers to the intercept of the regression equation; “size” is the other
dummy variable which is 1 for days preceding large insider sales and 0 for days preceding
small insider sales.
Panel A:
Panel B:
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38 Do short-sellers trade on inside information?
Table 10: Regression results for Insider Sales around News Announcements
Panel A (Panel B) shows the regression statistics when daily short sales are regressed on the
interaction dummy variable ANN*DAY (ANN*DAY1), where DAY (DAY1) is 1 for the
pre-event window of [-10, 0] ([-5,0]) and 0 elsewhere, and the other control variables. “Retx”
refers to the daily return; “retx1” refers to the lagged return; “lnvol” is the log of daily
volume traded; “lnvol1” is the log of volume traded a day before; “sd2” is the intra-day price
volatility of the security on that day; “sd21” refers to the previous day intra-day price
volatility; “day” is a dummy variable which is 1 in the pre-event window of [-10,0] and 0
otherwise; “day1” is a dummy variable which is 1 in the pre-event window of [-5, 0] and 0
otherwise; “_cons” refers to the intercept of the regression equation; “ann” is the other
dummy variable which is 1 for those insider sales which are surrounded by news
announcements on the either side in the event window of [-10, +10], and 0 otherwise.
Panel A:
Panel B:
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