timing, profitability and information content of abnormal insider...
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Timing, profitability and information content of abnormal insider sales
Francois Brochet Stern School of Business – NYU 44 West 4th Street – Suite 10-99F
New York, NY 10012 (212) 998 0024
November 2005
** Preliminary – do not quote/distribute **
When corporate insiders sell their stock in quantities that deviate from firm-specific trends, their trades are more likely to precede bad news over a horizon of several months, but not in the short run. This is consistent with insiders avoiding “suspicious timing” when engaging into “suspicious amounts” of trading, the combination of which would likely result in Rule 10b-5 securities lawsuits. Furthermore, the occurrence of abnormal sales is negatively associated with the ex-ante litigation faced by the firm. I also find that patterns of discretionary accruals and unmanaged earnings are indicative of managers using accruals to avoid reporting a loss after their abnormal trades and delay the report of earnings decreases two quarters away from their abnormal sales. In terms of stock returns, there is a smaller amount of good news following abnormal trades that are contemporaneous to loss-avoiding discretionary accruals, which is consistent with managers timing their trades and accruals to maximize their proceeds. By contrast, there is a greater amount of positive returns following trades during quarters where accruals offset an earnings decrease, which suggests managers delay the recognition of bad economic news to avoid litigation. More generally, trades in firm-years subject to high litigation cost precede greater positive stock returns, even if they eventually predict bad news. Finally, abnormal returns and trading volume around SEC filing dates of insider sales indicate that the market reacts to insider sales disclosure after the implementation of Section 403 of the Sarbanes-Oxley Act, which stipulates that insiders must report their trades within two business days. In particular, returns around those filings are associated with the probability that a trade is not motivated by liquidity needs. I would like to thank Joshua Ronen for his help and support. Discussions with Yonca Ertimur, Lucile Faurel, William Greene, Steve Huddart, Sarah McVay and Steve Ryan have also proved helpful.
1. Introduction
In a corporate environment where stock-based compensation has become
increasingly relied upon to align managers’ interests with those of shareholders, corporate
insiders routinely trade their own company’s shares in order to satisfy their consumption
and portfolio rebalancing needs. Yet, they are endowed with private information that
enables them to trade profitably, i.e. buy or sell at a price that does not reflect
forthcoming good or bad news that they only are privy to. However, executives trading in
their company’s stock while in possession of material nonpublic information can be
prosecuted, since it constitutes a violation of Rule 10b-5 of the US Securities and
Exchange Act of 1934.
This raises several questions. If we can sort out from the pool of insider sales
those that appear as liquidity-driven vs. private-information motivated, how is each type
of sale associated with future news? Can we gain insight into the nature of insiders’
private information that is driving the magnitude and timing of this news? Since insider
sales become observable to the public when filed with the SEC, do investors react to their
disclosure?
Some of these questions have been addressed to a certain extent in prior literature.
Several studies have found that – on average - insider sales have limited or no
explanatory power when it comes to predicting future returns or forthcoming disclosure,
despite the alleged existence of private information-motivated transactions, and conclude
that the combined effects of liquidity sales and litigation threat probably explain the weak
association1. Numerous papers have been dedicated to identifying the link between
insider trading activity and selected subsequent news announcements. A strand of this
literature focuses on earnings (announcements) and has produced mixed evidence.
Sivakumar and Waymire (1994) find no association between insider trading and next
quarterly earnings announcement surprise. Ke et al. (2003) show that insiders increase
their sales two to nine quarters prior to a break in earnings increases, but not within two
quarters, which the authors attribute to litigation concern. Managers have also been 1 Such studies include Lakonishok and Lee (2001), Huddart and Ke (2005) for abnormal returns, Noe (1999) and Cheng and Lo (2005) for management forecasts. The tendency of researchers to aggregate insider purchases and sales into net purchases measures probably contributes to understating the relative inability of insider sales to predict future returns compared to insider purchases.
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shown to use their discretion over accounting accruals in order to manipulate reported
earnings, and consequently stock price. However, conflicting theories have emerged to
explain the link between managerial trading incentives and accrual manipulation. Bartov
and Mohanram (2004) argue that insiders inflate earnings to increase their proceeds from
option exercise, while Beneish et al. (2005) posit that they resort to income-increasing
accruals so as to delay the revelation of bad news to the market, and thus decrease their
exposure to litigation threat.
The studies mentioned above partially address the questions that I raise, but some
are left unanswered, such as what subset of sales is more strongly associated with future
news or how accruals around insider sales affect contemporaneous stock returns. Beside,
the role of litigation with respect to these questions remains to be documented explicitly.
The first goal of this study is to extract from the pool of insider sales - using firm-
specific patterns of trades - those that appear as potentially driven by foreknowledge of
bad news because of their suspicious amount and investigate their association with future
news, in terms of stock returns in the days and months following insider sales, as well as
around specific events such as earnings announcements. Using a measure of litigation
cost based on filings of Rule 10b-5 securities lawsuits, I investigate how ex-ante litigation
impacts the incidence of abnormally large sales and the timing of insider sales with
respect to bad news. I then revisit the literature pertaining to the association between
insider sales and accrual manipulation by looking at patterns of quarterly earnings
components around individual insider sales. I also attempt to distinguish empirically
between the proceeds-maximizing story and the litigation avoidance explanation for
income-increasing discretionary accruals contemporaneous to insider sales by looking at
the timing of negative returns after the sales.
Section 403 of the Sarbanes-Oxley Act (thereafter SOX) amends Section 16 of the
Exchange Act of 1934 by requiring insiders to report their trades to the SEC within two
business days. I investigate whether there is a market reaction to insider sales, if yes
whether it differs for trades that are more likely to be private information-based vs.
others, and whether the accelerated filing introduced under SOX modified the nature of
the reaction to insider sale disclosure.
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I hypothesize and find that the sales that deviate from firm-specific patterns and
hence identified as “abnormal” are more likely to precede bad news than other insider
sales, but not in the days immediately following the transaction. Those bad news
materialize, among other time periods, around subsequent earnings announcements, but
not the closest one. Both sets of results are consistent with the argument that abnormal
trades are not timed shortly before bad news, in order to avoid legal scrutiny. Because
lawyers do track firm-level insider selling activity, I hypothesize that managers are more
likely to engage in abnormal equity selling activity when their firm’s ex-ante litigation
cost is low. The results are consistent with this hypothesis, although they also show that
ex post, firm with abnormal sales face a higher litigation cost. With respect to earnings
components, I expect managers to be more (less) likely to use income increasing
(decreasing) accruals that exceed negative (positive) pre-managed earnings in the
quarters around their abnormal sales. The results hold in terms of levels of positive and
negative accruals, and negative changes in accruals. Further empirical analysis shows that
abnormal trades, when contemporaneous to income increasing discretionary accruals that
offset a loss, are timed ahead of smaller amounts of positive stock returns, which suggests
that managers use discretionary accruals to inflate earnings and stock price to maximize
their proceeds. By contrast, managers are less likely to use accruals to offset an earnings
decrease around their abnormal sales, and when they do so, their trades are followed by
greater positive stock returns, which supports the contention that managers tend to delay
the revelation of bad economic news after their suspicious trades using discretionary
accruals in this specific scenario.
Given the observed returns and trading volume around filing dates of SEC Forms
4 and their association with insider trades characteristics, I document that the market
reacts to Form 4 filings and conditions its reaction on the probability that a trade is
abnormal. The distinction between pre- and post-SOX trades reveals that the market
reacts to trade filings only after SOX, insofar as my proxies capture information relevant
to investors. Taken together, the findings of this study show that simple monitoring of
firm-specific trading patterns helps identify trades that are more likely to precede bad
news, that those trades are generally not timed immediately ahead of bad news, and that
managers use their discretion over reported earnings to manipulate the timing of bad
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accounting and economic news after their large trades. In addition, I find that market
participants react to insider trade disclosure. In particular, when such disclosure becomes
significantly more timely because of Section 403 of SOX, their reaction is associated
with the level of suspicion of a trade.
This study contributes to the literature by showing that insider trades that deviate
from firm-specific average levels - as detected using methods inspired from legal practice
– are a subset of the population of insider sales which are a better predictor of future bad
news. Furthermore, by looking at individual trades separately, I am able to document how
insider sales are timed with respect to future news. Also, I provide direct evidence of how
litigation affects managers’ trading decisions. I find that high litigation risk generally
preempts large insider selling activity and induces managers to time their trades
immediately before good news. Building on a strand of literature that focuses on the
relation between accounting information and managerial equity transactions, I show how
abnormal insider sales are timed with respect to accrual patterns and find evidence
supportive of the contention that managers delay bad accounting news with income
increasing accruals around their abnormal sales. In addition, I show that depending on
whether they use discretionary accruals to offset a loss or an earnings decrease, managers
time their trade so as to maximize their proceeds or delay the reflection of bad news in
stock price. However, since managers are generally less likely to resort to increases in
discretionary accruals after their suspicious sales, the evidence in this paper gives only
limited support to the role of discretionary accruals in avoiding litigation in the presence
of high insider selling activity. Finally, I contribute to the literature that explores the role
of insider trading in incorporating information into stock prices. To the best of my
knowledge, this is the first study to examine the impact of Section 403 of SOX on insider
trading informativeness. Except for Aboody and Lev (2000) in the case of R&D, and
Lakonishok and Lee (2001) for size and book-to-market ratio, no study has explored the
determinants of the returns around SEC filing dates of insider trades.
The remainder of the paper is organized as follows: Section 2 reviews the relevant
literature. Section 3 develops the hypotheses. Section 4 delineates the research design.
Section 5 describes the sample and presents the results. Finally, Section 6 concludes. In
addition, the appendix provides information on variable constructs.
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2. Background and literature
There are numerous studies – in the finance and accounting literature -
investigating the association between insider trading and the information dissemination
process on capital markets, and whether the former contributes to the latter.
It is well established that trades by insiders are followed by abnormal returns.
Papers documenting this result include Jaffe [1974], Finnerty [1976], Seyhun [1986,
1992], Rozeff and Zaman [1988], Lakonishok and Lee [2001]. While insiders trade
routinely in their own stock for liquidity and portfolio rebalancing purposes, the findings
in the studies aforementioned are indicative of their trades being motivated by
information not impounded into stock price at the time of the transaction. When it comes
to identifying the nature of the information that managers trade upon, insider trading
around earnings announcements has received a great deal of attention in the past
literature. For instance, Sivakumar and Waymire (1994) find that, although post-earnings
announcement insider trades earn significant abnormal returns, they are not consistent
with the subsequent one-quarter-ahead earnings surprise. Ke et al. (2003) document that
insiders modify their trading activity in response to upcoming breaks in strings of
earnings increases as early as two years in advance, but not within two months, which
they interpret as avoidance of legal scrutiny. Managers may also have more of an
information advantage about earnings components that are estimate-based rather than
factual. Beneish and Vargus (2002) find that accruals are less persistent when preceded
by abnormally large insider selling activity, which they partly attribute to opportunistic
earnings management. Beneish et al. (2005), in a sample of firms experiencing default,
find that managers sell their stock prior to managing earnings upward, which they
interpret as an attempt by insiders to delay bad news in order to reduce their exposure to
litigation. Looking at option exercises, Bartov and Mohanram (2004) find that during
years of abnormally high level of exercise, firms report positive discretionary accruals,
that reverse in the subsequent year. All three papers provide evidence consistent with
managers resorting to income manipulation in response to their trading incentives.
Altogether, the evidence so far on the effect of accruals on insider trading timing and
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profitability is limited, as most studies aggregate insider transactions and accruals on a
yearly basis.
Many studies come to the conclusion that their results are consistent with
managers considering litigation threat in their trading decisions. However, very few do
actually implement tests of the effect of litigation on insider trading. Exceptions include
Ke et al. (2005), who show that insiders in firms facing high litigation risk shift their
trades to lower “jeopardy” periods (from right before to right after earnings
announcements) and their trades exhibit a stronger association with the recent earnings
announcement news, which is allegedly a low-risk strategy, since insiders can only be
sued for trading on non-public material information. Jagolinzer (2004) estimates the
litigation cost faced by individuals and how it affects their decision to elect for trades
scheduled within Rule 10b-5-1.
While those studies cover post PSLRA sample periods, federal regulation has
changed over time since the Exchange Act of 1934. Bainbridge (2001) provides a
comprehensive review of the pre-Sarbanes Oxley insider trading law in the US. The basis
of federal regulation on insider trading is Section 10(b) of the Securities Exchange Act of
1934, and more particularly Rule 10b-5. Another aspect of insider trading regulation of
potential importance to investors is the reporting requirements that insiders are subject to,
as defined under Section 16 of the Exchange Act until 2002, and Section 403 of SOX
subsequently. Under the previous rules, directors, officers and 10% or greater
stockholders were required to report most changes in their beneficial ownership every
month on a Form 4, to be filed within 10 days after the close of the calendar month in
which the transaction occurred. Section 403 amended this provision of Section 16 of the
Exchange Act by accelerating Form 4 filings. As of August 29, 2002, insiders are
required to file Form 4 with the SEC and the appropriate stock exchange within two
business days of the transaction date. As before, the report must include the insider’s
ownership as of the filing date. Additionally, starting July 30, 2003, insiders must file
Form 4 electronically. The SEC, as well as issuers maintaining websites, is required to
post those forms on a publicly available website within one business day of the filing.
Two studies have looked at returns around Form 4 filing dates in pre-SOX sample
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periods. Aboody and Lev (2000) find that raw returns around trade disclosures to the
SEC are significantly positive (negative) for purchases (sales), especially for firms with
R&D expenses. By contrast, Lakonishok and Lee (2001) find no economically significant
abnormal returns around transaction and SEC filing dates of insider open market
purchases and sales from 1975 to 1995. Other studies drawing conclusions on the
information content of insider trades include Damodaran and Liu (1993), who find that
insider trades elicit a market reaction in the context of appraisals of Real Estate
Investment Trusts (REITs), and Givoly and Palmon (1985), who infer from the observed
abnormal returns following insider transactions and the low disclosure incidence
following them that insider trades themselves generate abnormal returns, although they
do not refer to Form 4 filing dates. From a different angle, Piotroski and Roulstone
(2005b) show that insider trading activity is positively associated with the incorporation
of firm-specific information in stock prices. To my knowledge, no study, to date, has
investigated the impact of Section 403 of SOX on insider trading.
3. Hypothesis development
1) Timing and profitability of insider sales
Insider sales constitute the primary focus of this paper. Prior research has
consistently attributed a greater predictive ability for future returns to insider purchases2,
and often found that insider sales have – on average – little predictive power (see, e.g.,
Lakonishok and Lee [2001]) and are not profitable (Huddart and Ke [2005]). This result
is usually explained in the literature by two non-mutually exclusive hypotheses.
First, insider sales are subject to greater litigation risk than purchases. This is
assumed to be the by-product of an asymmetry in expected legal costs associated with
good and bad news. Consistently across studies that analyze a sample of securities-related
lawsuits, it appears that most cases are related to large stock price declines (Francis et al.
[1993], O’Brien and Hodges [1991]). Skinner (1994) suggests that “the legal reasons for
2 Studies documenting this regularity include Jaffe (1974), Finnerty (1976), Seyhun (1986, 1988), Noe (1999)
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this asymmetry appear to relate to proof of damages and the need to show a sufficient
causal connection between the plaintiff’s injury and the wrongful conduct.” In the case of
good news, one suffers an opportunity loss rather than an out-of-pocket cost, and proving
that they would not have sold if the information was available in due time, in order to
show causation, remains a difficult task. The connection with insider trading comes from
the fact that insider selling is recognized by courts as a mechanism to establish that the
defendants acted with scienter in securities fraud allegations, which plaintiffs ought to
prove for their lawsuit to prevail under Rule 10b-5. Hence, plaintiffs resort to insider
selling allegations to substantiate many cases. This has become particularly prevalent
after the enactment of the PSLRA of 1995, which further shifts the burden of proof to the
plaintiffs’ side3.
Insider sales are also driven by liquidity needs. Stock holdings are part of
managers’ compensation packages, and with the increasing tendency of firms to resort to
non-cash compensation devices, it is implicit that some or all of (restricted) stock and
option grants may be converted to cash for managers’ consumption needs. Trades that
respond to liquidity needs further weaken the predictive ability of private information-
based insider sales and provide an additional explanation for the lack of profitability of
insider sales4.
The first part of this paper is aimed at identifying insider sales of suspicious
amounts and investigating their association with future news. Given the importance of
litigation costs in insider trading decisions, I choose techniques observed in legal practice
as guidelines to identify abnormal trades. Lawyers, on behalf of investors, track insider
sales to detect any suspicious activity and include insider selling allegations in securities
fraud lawsuit filings (cite article). However, under the increased pleading standards for
scienter introduced by the PSLRA, courts have developed rules of thumbs to facilitate
their decision making process on motions to dismiss. Sale (2002) provides a review of the
heuristics used by judges to reject fraud-based allegations invoking insider selling to
3 Johnson et al. (2002) and Pritchard and Sale (2003) find in their samples that a majority of post-PSLRA lawsuits include insider trading allegations. 4 By contrast, I assume throughout the study that insider purchases are not motivated by liquidity needs. Since managers have undiversified portfolios with greater exposure to their company’s stock than optimal (from their point of view as an investor), they should only make open market purchases when expecting good news that will materialize in positive abnormal returns.
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establish scienter. Broadly speaking, plaintiffs must substantiate their allegations by
providing evidence that the trades are suspicious, with respect to their timing and
amount5. Hence, I follow courts’ approach to assess the probability that trades are
indicative of scienter to separate normal/liquidity from suspicious/abnormal trades. My
dichotomy is based solely on trading amount criteria, which enables me to test whether
abnormally large insider sales are timed opportunistically. I argue that managers, because
of the expected legal costs associated with selling their stock ahead of bad news, will
avoid large trades shortly before the release of bad news. However, relying on the timing
heuristics used by courts, whereby judges dismiss fraud allegations if trades are not timed
in a manner that univocally indicates fraud, I posit that summary judgments are more
likely to be granted to defendants if bad news is revealed gradually to the market or in the
months following the trades. Therefore, managers are hypothesized to deviate from their
liquidity-based trading pattern only if they anticipate bad news over a horizon longer than
what would be considered imminent. By contrast, liquidity trades should not – on average
– presage bad news. To summarize the short-term and medium-term distinction between
returns following normal and abnormal trades, the first hypothesis states:
H1: abnormally large insider sales are more likely to precede bad news than
those in line with past trading activity from the same firm’s insiders. Because of legal
jeopardy, bad news following abnormal sales do not materialize shortly after the trades
occur.
2) Insider sales and litigation
Conditional upon the rejection of the null of the first hypothesis, i.e. assuming that
abnormally large insider sales are, indeed, profitable, they should be subject to legal
scrutiny. In particular, because those trades are identified using techniques inspired by
legal practice, they constitute – in conjunction with bad news - a primary target for
securities lawsuits pursuant to Rule 10b-5. In the presence of forthcoming bad news, why
then would managers’ best response consist of trading in a way that is precisely what
5 I will review the heuristics in more detail in the research design section, where I articulate the different criteria of my distinction between normal and suspicious trades.
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investors consider as suspicious? I argue in Hypothesis 1 that insiders time their trades
sufficiently ahead of bad news to increase the difficulty for plaintiffs to prove the
connection between their trades and subsequent disclosure. Moreover, I argue that an
additional parameter in the decision to trade is the ex-ante litigation cost. If facing, ex-
ante, a low litigation risk, insiders are more likely to consider that the total benefit from a
large dollar amount of sales exceeds the expected litigation out-of-pocket cost. The
benefit accruing to an insider upon an abnormal stock sale is considered to be the sum of
two components. The first one is simply the proceeds from the sale, while the second one
is the loss avoided by trading before a benchmark date. By deviating from consumption-
driven trading patterns, abnormal sales are assumed to accelerate sales that would have
been timed in the next year(s) otherwise. Since I assume that litigation threat is
decreasing in distance to bad news, I argue that symmetrically, managers time their trades
further away from bad news as they face a higher ex-ante litigation risk. By doing so,
however, they are more likely to realize lower proceeds to the extent that more good
news is to be reflected in stock price after the trades are completed. In summary, the
second set of hypotheses is stated in alternative form:
H2: a) In years of abnormal insider sales, firms face lower ex-ante than firms
with no abnormal trading.
b) The amount of good news following an insider sale is increasing in the ex-
ante litigation faced by the firm.
3) Insider sales and accruals
The hypotheses so far are silent about the nature of the private information that
insiders trade upon. Previous research has shown that managers use their information and
discretion about future earnings reports to increase their profits from stock-based
transactions. Bartov and Mohanram (2004) find that in years of abnormally high option
exercise, managers resort to income increasing accruals in order to inflate earnings and
potentially stock price on exercise date. In the year following abnormal exercise, they
report disappointing earnings that result from the reversal of the prior year’s accruals. In
a concurrent study, Beneish et al. (2005) document similar findings using insider sales in
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a sample of firms experiencing technical default, but interpret the earnings management
in the year of abnormal insider sales as a deferral of bad news in order to avoid litigation.
The aggregation of trades or option exercises and accruals at the firm-year level in the
studies aforementioned make it difficult to sort out between a proceeds-maximizing
scenario, whereby managers would inflate stock price through income increasing accruals
and sell at a peak vs. the litigation hypothesis, which suggests that managers resort to
positive abnormal accruals after their sales in order to delay bad news and conceal its
connection with their abnormally large selling activity. The litigation scenario is
consistent with findings in the literature, such as the increase in insider sales two to nine
quarters prior to a break in earnings increases documented by Ke, Huddart and Petroni
(2003). The absence of association between the occurrence of the break and insider
selling in the two preceding quarters is attributed to litigation avoidance. Likewise, if
income increasing accruals persist in the quarters subsequent to insider sales, it would be
provide additional support for the litigation interpretation. In addition, stock returns
following insider sales contemporaneous to high unexpected accruals should be
informative about managers’ use of accruals for proceeds-increasing or litigation-
avoidance purposes. For example, the joint occurrence of opportunistic accrual
manipulation and insider sales puts managers at risk with respect to litigation if plaintiffs
can prove that price was inflated at the time of the sales. Therefore, to the extent that the
litigation avoidance argument holds, I would expect – ceteris paribus – more good news
to follow insider sales when contemporaneous to positive accruals. To summarize the
role of accounting discretion in the timing and profitability of insider sales, H3 a) is
stated in its alternative form, whereas H3 b) is stated in its null form, since the distinction
between the price-maximizing and litigation avoidance hypotheses is left as an empirical
question:
H3: a) abnormal sales are more likely to be immediately followed by positive
discretionary accruals and negative pre-discretionary accruals earnings (or change
thereof) than normal sales,
b) The positive stock returns following abnormal sales executed during a quarter
where managers use discretionary accruals to avoid reporting a loss or an earnings
decrease are not different from those following other sales.
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4) Information content of insider sales
The trades taken into consideration in this empirical study become eventually
observable because they are subject to filing requirements with the SEC, which releases
them through the EDGAR system. Insofar as it does not occur after the news that insiders
were anticipating, the disclosure of information about insider trades may be of interest to
market participants. However, there is no clear evidence in the literature as to whether the
market reacts upon the release of SEC Forms 4. Lakonishok and Lee (2001) find a
statistically but not economically significant average market-adjusted return around SEC
filing dates across a large sample of insider purchases and sales. Aboody and Lev (2000)
find that trades filed by insiders in firms that report R&D trigger larger (signed) raw
returns than no-R&D firms. They attribute this result to the greater information
asymmetry associated with R&D activity, which explains why investors pay greater
attention to trades in those firms. Following up on the previous hypotheses, I argue that
insider sales are not equally relevant to investors. Abnormal sales are more likely to
presage bad news, yet not in the short run, so that even if they are not immediately known
to the public, their disclosure may still trigger a negative market reaction. However, the
timeliness of the disclosure may have an impact on the nature and the magnitude of the
market reaction. My sample period is not homogeneous with regards to this dimension,
since Section 403 of the Sarbanes-Oxley Act, effective August 29, 2002, modifies the
disclosure requirements that corporate insiders are subject to with respect to their trades,
as previously defined by Rule 16b of the Exchange Act. Insiders are required to file their
trades with the SEC within two business days of the transaction, which drastically
reduces the delay that was allowed under the previous rule. To summarize the hypotheses
related to the market reaction to insider trade filings, H4 is stated in its alternative form:
H4: a) Abnormal returns around SEC filing dates of insider trades are negatively
associated with the probability that trades are motivated by insiders’ private information.
b) The nature of the reaction is different before vs. after Section 403 of the SOX
came to effect.
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4. Research design
1) Measures of normal/expected insider trading
The first stage of the analysis consists of identifying abnormally large insider
sales. Lack of consensus in prior research about the correct measure of insider trading
activity suggests the use of several alternative proxies. I choose to measure insider
trading with the number of shares traded, deflated by the number of shares outstanding on
the same day, as in Beneish and Vargus (2002), or by the number of shares held by the
reporting insider6. Next, I need to consider the level of aggregation of trades. There are
two dimensions for within-firm aggregation of insider trades: a temporal one, and the
type of insiders that are included in the aggregate measure. Most studies restrict their
analysis to directors and officers and exclude other persons subject to reporting
requirements of Section 16 of the Exchange Act, mainly large shareholders that hold 10%
or more of the shares outstanding. I choose to aggregate only trades from top
management team members (i.e. CEOs, CFOs, Chairmen of the Board, Presidents and
COOs as in Rogers [2004]) for my measures of expected trading. This choice is driven by
the assumption that those are the insiders whose access to non-public information about
the firm’s future operations is assumed to be most timely and accurate, and who are
assumed to exert influence on the disclosure policy of the firm. It is also motivated by
the “All-defendant” judging heuristic, which relies on the theory that if there was fraud,
the highest-ranking (“most knowledgeable”) managers must have taken part to the selling
activity (see Sale [2002] for example of cases where judges dismissed scienter inferences
based on the absence of trades by CEOs or CFOs). The “All-defendant” heuristic
reinforces the validity of monitoring insider trading at the firm-level. The time dimension
of insider trade aggregation is also subject to trade-offs between accuracy and data
6 Theoretically, deflating trades by insiders’ equity holdings is more appealing than using shares outstanding, because it better reflects the impact of trades on insiders’ portfolios, and patterns of trades as a percentage of insider holdings should provide a more accurate proxy for liquidity and portfolio rebalancing needs. However, when selling “conventional” stock, insiders report their holdings exclusive of options. By contrast, when selling options, they report only option holdings for a specific series, so total (option) holdings are generally not observable in Thomson Financial. Using other observations in the database (Such as holdings records with no associated transaction), I retrieve stock holdings data for insiders even in years when they do not trade and check for inconsistencies within years and from year to year.
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availability. Too large a window may introduce noise and decrease the detection power of
the model for abnormally large individual trades, while analyzing trades over small time
intervals potentially ignores the frequency with which liquidity trades occur. Another
factor that reduces trading frequency is the short-swing profit rule that entitles firms to
claim profits realized by insiders from round trip transactions within six months. Hence,
as a compromise, I aggregate trades over fiscal or calendar years as a base case for my
estimations of normal firm-level insider trading.
Abnormally large trades can be detected using either firm-specific time-series
patterns of trading or compared with other firms in the sample. Recent research has
attempted to distinguish between normal and abnormal levels of insider selling activity.
For example, Beneish et al. (2005) classify firm-years as abnormal sellers if their net
selling activity exceeds the median in the same size decile over the same calendar year
(cross-sectional approach) or if they sell more than the previous year (time-series
approach). As Bartov and Mohanram (2004) do for abnormally large option exercises, I
choose a time-series approach. Notwithstanding the difficulties to control for the
substantial cross-sectional differences among sample firms in terms of managerial
compensation (especially since my study is not restricted to Execucomp firms), liquidity
needs of managers are better assessed using their own past trading behavior rather than
contemporaneous trades by insiders in other firms. Furthermore, time-series detection of
abnormal sales akin to that in legal practice enables me to test the validity of court
heuristics. Yearly aggregate insider sales as a percentage of shares outstanding (and
shares held when available) are compared to their average over the past two to five years
for each firm. If the magnitude exceeds the historical average by more than three standard
deviations with respect to both measures, the firm-year is classified as abnormal (Abn=1)
with respect to insider sales, normal otherwise (Abn=0). If there is only one prior year of
data available, the firm-year is classified as abnormal if its level of sales exceeds the prior
year’s by more than 50%. The cutoffs are arbitrary and represent a trade-off between
sample size and noise7. To be consistent with the “Percentage heuristics”, whereby courts
have dismissed fraudulent insider trading allegations based on the premise that the
7 Sale (2002) reports that the courts rhetoric contains criteria such as trades being suspicious only if “drastically out of line with” past trades. Quantifying such wording necessarily requires a high degree of subjectivity. I try many different combinations of parameters to sensitize the abnormal trade definition.
14
defendants sold only a fraction of their total stock holdings, even if the transaction
proceeds amounted to several millions of dollars, shares held by insiders should be used
as the primary deflator. The “Option-basis heuristic” includes option holdings in the
denominator. Because insiders’ total holdings are not available in Thomson Financial,
common shares outstanding are used as the primary deflator in my tests. For firm-years
with consistent data on insiders’ holdings, I also check whether the sales qualify as
abnormal as a weighted-average percentage of insiders’ holdings. Note that throughout
the study, I refer to shares sold divided by shares outstanding as Net_Shrout and divided
by shares held as Net_Hold. As long as a firm has return data available on CRSP during a
given year, it is accounted for in the measure of expected trading. Hence, many firm-
years are assigned a value of zero trading. The next step consists of examining individual
trades within each ‘suspicious’ year. Given that the “abnormal” flag is attributed at the
firm-year level, all trades within an abnormal firm-year are considered as abnormal,
regardless of their size.
H1 tests the timing and profitability of normal vs. abnormal sales. I use stock
returns as my primary measure of news. Under the filing requirements prior to Section
403, it was not unusual that insiders would trade on several days in a given month and
report all trades altogether on the same filing date8. I aggregate trades reported by the
same insider on the same date. Pre-trade returns (PreRet) are computed over the 10
trading days prior to the first transaction date, cumulating size-adjusted daily returns.
Post-trade returns (PostRet) are computed over a window starting from the last
transaction date until the SEC filing date. Since this window varies in length, cumulative
size-adjusted daily returns are scaled by the number of trading days in the post-trade
window. I choose the SEC filing date as the end date because presumably, over the post-
trade window defined as such, the identity of the trader is not public information, and
8 The split of trades into several transactions over several days probably represents an attempt by insiders to limit the impact on stock price of large transactions. It may also be due to pre-arranged terms. I assume that the choice of transaction dates is at the discretion of the insider. Intra-day timing is more likely to be attributable to the broker.
15
information asymmetry between the corporate insider and outsiders is exacerbated (see
Aboody and Lev [2001] for a similar argument)9.
Insider trading profitability (more precisely loss avoided for sales) is measured
over a six-month period, following Huddart and Ke (2005). It is calculated as the product
of the number of shares traded times the reported transaction price times the abnormal
return computed over the six months following the trade, excluding the transaction date.
The abnormal return is adjusted for by a five-factor model, based on the Fama-French
(1993) three-factor model augmented for momentum as in Carhart (1997) and
information risk as in Aboody et al. (2005). Information risk is included in the pricing
model because of evidence in the literature that it is priced by investors (Easley et al.
[2002], Easley and O’Hara [2004], Francis et al. [2005]) and affects the profitability of
insider trades (Aboody and al. [2005]). The last factor is constructed using the return on a
mimicking portfolio that is long in low earnings quality firms and short in high earnings
quality firms. Consistent with Aboody et al. (2005), I use the cross-sectional modified
Jones model developed by Dechow et al. (1995) (see also Subramanyam [1996], Guay et
al. [1996], Bartov et al. [2000]) to measure abnormal accruals, whose absolute value
proxies for earnings quality. The following regression is run by Fama-French industry
and calendar year (using the most recent fiscal year for firms whose fiscal year-end is not
December), provided there are at least 20 observations with the required data available in
any given industry/year:
0 1 2 3( )i i i iTA Sales AR PPE ASSETi iγ γ γ γ= + ∆ −∆ + + +ε (1)
where TA is total accrual, Sales∆ is annual change in sales, AR∆ annual change
in accounts receivable, gross property, plant and equipment and beginning
of the year total assets. Since all variables are scaled by ,
PPE ASSET
ASSET 3γ is the intercept of the
regression. is measured as the difference between net income before extraordinary
income and operating cash flow adjusted for extraordinary items that affect cash flows
(Compustat annual Data124). To reduce the influence of outliers, all variables are
truncated at 1% each tail. Each regression produces firm-year specific error terms that are
TA
9 Because Section 403 reduces the transaction-filing date window to two days, I exclude trades executed after August 29, 2002 from this analysis. As a robustness check, I set the post-event window to ten trading days and include all trades in the sample period.
16
labeled discretionary (or abnormal) accruals. For each fiscal year, firms are ranked by the
absolute value of their discretionary accrual component. Firms in the bottom (top)
quintile are classified as high (low) earnings quality. To ensure that the data used in
classifying firms into earnings quality quintiles is publicly available, the factor-
mimicking portfolios are based on the previous year earnings quality rankings.
Over the two years preceding the month during which the trade occurs, daily
stock returns are regressed on daily market excess return, size, book-to-market,
momentum and earnings quality factors, using the following firm-specific time-series
specification:
, , 1, , , 2, 3, 4, 5,( )i t f t i i m t f t i t i t i t i t i tR R R R SMB HML UMD EQ ,α β β β β β− = + − + + + + + ε (2)
Where ,i tR is firm i’s stock return, ,f tR the risk-free rate (one-month T-Bill rate),
,m tR the market rate (CRSP value weighted index), and the Fama-French
(1993) size and book-to-market factors, the Carhart (1997) momentum factor and
the earning quality factor (the t subscript stands for day t). The coefficient estimates
obtained from this first stage regression are subsequently used to fit expected daily
returns based on the five factors
tSMB tHML
tUMD
tEQ
10 and subtracted from actual returns to obtain daily
abnormal returns, summed over the six month period to obtain the desired cumulative
abnormal return FFRet. In turn, this six-month abnormal return multiplied by the trade
value (shares traded times transaction price) times (-1) is defined as Profit. Because of
the skewness of the trade value variable, I use its logarithm multiplied by the abnormal
return (times -1) to compute Ln_Profit.
To test H1, I first use univariate tests. Since the distinction between normal and
abnormal trades is performed at the firm-level, I compute firm-specific comparisons of
profits for normal and abnormal trades, at the firm-year and individual trade levels. For
the firm-year level test, insider trading profits (for 3-, 6- and 9-month horizons) are
summed for each calendar year, and the firm-specific difference between average yearly
profits for abnormal and normal years is computed. I then look at the distribution of this
difference across all sample firms that have at least one normal and one abnormal year of 10 The factor loadings are estimated using rolling windows, because they are not expected to be stationary over time. Also, consistent with the unrestricted approach undertaken in the empirical finance literature, the intercept α is included in the estimation of expected returns, although its theoretical value is zero.
17
insider selling activity. In particular, I test whether the cross-sectional mean and median
are significantly positive. I run the same test at the individual trade level. As for the
aggregate analysis, the mean and median firm-specific difference between the average
abnormal and normal trade profits (and returns) are expected to be significantly positive.
By contrast, short-term returns differences are not expected to be significantly different
from zero. A similar test is performed cross-sectionally. Individual sales are ranked
across all firm-years by Net_Shrout into quartiles. Within each quartile, the mean and
median Net_Shrout, Profit and Ln_Profit are then computed separately for normal and
abnormal trades. Again, I expect the mean and median Ln_Profit and Profit to be
significantly greater for abnormal than for normal trades, within each quartile. Ideally,
there would be no significant difference in terms of Net_Shrout, which would indicate
that the quintile decomposition effectively controls for scaled trade size.
In order to test jointly the association between normal/abnormal trades and short-
term/long-term returns, I use a multivariate logit regression analysis. Logit appears to be
more appropriate than an OLS specification because there may not be a linear
relationship between insider trading and subsequent returns, and the primary question is
to see if normal and abnormal sales are characterized by different timing and profitability,
so the dependent variable takes only two values. The joint test of timing and profitability
is summarized by the following equation:
0 1 2 3
4 5 6
7 8 9
Pr( 1) ( *
* *
)j jj
Abn f PreGood PreRet PreGood PreRet
PostBad PostRet PostBad PostRetPosProfit FFRet PosProfit FFRet
Ctrl
β β β β
β β ββ β β
β ε
= = + + +
+ + ++ + +
+ +∑ (3)
H1 states that abnormal trades are more likely to be profitable on average. Hence,
the variable PosProfit equal to one if the six month abnormal return following a trade is
strictly negative, zero otherwise is expected to be significantly and positively associated
with the probability that a trade is abnormal. Additionally, this dummy variable is
interacted with Profit, to see if the likelihood of a trade being abnormal is increasing in
its profitability, given that it is profitable. In a similar fashion, the timing of insider sales
with respect to short-term returns is captured by PreRet, PostRet and dummy variables
PreGood, PostBad that equal 1 if PreRet is positive and PostRet negative. Regarding
18
PreGood and PreRet, both abnormal and normal trades are expected to follow good
news, so these variables may not be significantly different from zero11. As for PostBad
and PostRet, according to H1, they should not be different from zero. Control variables
include Size (Log of market value as of the end of the most recent fiscal year) which is
expected to be negatively associated with Abn because large firms should have more
stable trading patterns, BM (Book to Market value of equity ratio, end of the most recent
fiscal year) which should exhibit a negative association with Abn because insiders tend to
be contrarians and sell more heavily when the market-to-book ratio is high (Rozeff and
Zaman [1998]), AllHi (variable equal to one if the price is an all-time high on the
transaction date, zero otherwise) should be positive because option exercise has been
shown to occur on all-time price days (Carpenter and Remmers [2001]). Lagged
performance measures (Lag∆ROA and LagRet) account for determinants of passive
trading that would not be captured by the short-term window over which PreRet is
measured, and should be positively associated with Abn if abnormal trades capture
passive trades.
In order to gain more insight into what private information insiders trade upon, I
investigate whether the profitability of abnormal sales materializes around specific
events. Earnings announcements are a natural candidate because they are associated with
returns of economic significance and there is mixed evidence in the literature as to
whether insiders engage into informed trading ahead of these events, so the
liquidity/informed trades distinction may shed light on this question. Furthermore, while
technically not mandatory, preliminary earnings announcements are very common and
relatively predictable in terms of timing, which partly mitigates concerns of endogeneity
between the timing of abnormal sales and that of earnings announcements. My primary
measure of earnings surprises is the 3-day abnormal return around the announcement
date. This measure circumvents the problem of unobservable market expectations and is
of greater interest in the case of insider trading because it measures directly a benefit (or
11 Alternatively, using the terminology introduced by Seyhun (198?), insiders may trade passively on their private information. Passive trading consists of delaying trades until after good news are released (in the case of insider sales) in order to maximize the proceeds. My abnormal trades may include large sales by insiders who want to capitalize on recent good news without consideration for future news.
19
loss) to insiders’ equity sales. Since I assume that insiders have a horizon of about six
months when deciding to trade on private information, annual earnings surprises may be
too untimely. Hence, I focus on quarterly earnings announcements. In addition, insiders
are assumed to favor abnormal sales that will be revealed gradually to the market, so I
include up to three leading earnings announcements (two of which fall within the 6-
month window over which Profit is measured). I perform a univariate and logit analyses.
The univariate test simply computes the mean and median abnormal returns around the
three earnings announcements following insider sales, separately for normal and
abnormal sales, and tests whether they are significantly lower after abnormal sales. For
the logit, as in Model (3), I primarily test the association between the incidence of
abnormal insider sales and negative returns around earnings announcements, but also
include variables that account for the magnitude of the surprise. Following the argument
that litigation threat decreases in distance to news, I expect abnormal sales to be
associated with negative returns around the second next earnings announcement, and
possibly third if insiders’ horizon exceeds six months. The logit model is:
0 1 2 3 4 1
5 1 6 1 1 7 2 8
9 2 2
Pr( 1) ( *
*
* )
t t t t t
t t t t
t t j jj
Abn f PosEA CarEA PosEA CarEA PosEA
CarEA PosEA CarEA PosEA CarEA
PosEA CarEA Ctrl
β β β β β
β β β β
β β ε
+
+ + + +
+ +
= = + + + +
+ + + +
+ + +∑2t+ (4)
In light of the discussion above, since the t nPosEA + are set to 1 if the abnormal return
around the n+1th quarterly earnings announcement following an insider sale is strictly
positive (zero otherwise), 4β and 7β are expected to be significantly negative. Litigation
threat should deter large sales ahead of the closest earnings announcements, so 1β is not
expected to be significantly negative. Because of plausible contradicting hypotheses, I
make no predictions for the signs of the coefficients on magnitudes of the returns.
The second hypothesis posits that insiders are more likely to deviate from normal
selling patterns if their ex-ante litigation cost is low, so as to minimize their exposure to
legal jeopardy. During the year of abnormal trading and the subsequent one, litigation
cost should, by contrast, significantly increase above that of firms with no abnormal
trading activity. To test H2, I first calculate the fitted probability of a class action
20
securities lawsuit being filed for a given firm-year using the model developed in Rogers
and Stocken (2005), similar to that in Johnson et al. (2000). I use the same variables as in
Rogers and Stocken (2005) but choose a logit specification on a yearly basis instead of
probit on a quarterly basis. More details are provided in the appendix. The second stage
consists of a univariate and a logit analyses as in the previous tests. For the univariate
analysis, all firm-years are ranked into quartiles based on aggregate Net_Shrout. The
mean and median ex-ante litigation costs are then calculated separately for normal and
abnormal sales within each quartile. I test whether the mean and median are significantly
lower for abnormal sales. Besides the ex-ante (lagged year) litigation cost measure, I
include the current (same year) and ex-post (next year) litigation fitted probability12. The
logit regression is as follows:
0 1 1 2 3 1Pr( 1) ( )t t t jj
Abn f Lawfit lawfit Lawfit Ctrl jβ β β β β− += = + + + + +ε∑ (5)
The main coefficient of interest is β1, which is expected to be negative, according
to H2. β3 is included to check whether the combination of abnormal insider sales and bad
news results in greater legal scrutiny.
The third set of hypotheses pertains to the role of accounting accruals with respect
to the timing and profitability of abnormal insider sales. To test H3, I need a measure of
discretionary accruals on a quarterly basis. I use a quarterly version of the annual model
described above for the EQ factor construct13. Unmanaged earnings are defined as the
difference between net income before extraordinary items and discretionary accruals. As
in the previous tests, I use a logit regression to test whether abnormal insider sales are
more likely to follow and precede patterns of discretionary accruals and unmanaged
earnings that are highly suggestive of earnings manipulation. I run the following two
tests:
12 H2 remains silent about the relation between ex-post litigation cost and abnormal sales. A predictably higher ex-post litigation cost may imply irrational expectations on behalf of managers. However, the joint occurrence of high insider selling activity and bad news will likely result in an increase in the litigation cost faced by the firm. Since the litigation cost is based upon filings of Rule 10b-5 lawsuits irrespective of whether they turn out to have merit or not, the higher ex-post litigation may be driven by lawsuits that will eventually be dismissed, which managers probably take into account in their trading decision problem. 13 All variables are the same except for net PPE instead of gross PPE, which has many missing observations on the quarterly tape. The caveat of switching to net PPE is the potential effect of managerial discretion on depreciation and amortization being attributed to non-discretionary accruals.
21
0 1 1 2 3 1 4 2 5 3
6 1 7 8 1 9 2 10
Pr( 1) (
)
t t t t
t t t t
j jj
Abn f Pump Pump Pump Pump Pump
Dump Dump Dump Pump PumpCtrl
β β β β β β
β β β β β
β ε
− + +
− + +
= = + + + + +
+ + + + +
+ +∑3
t
t
+
+
3
t
t
(6)
0 1 1 2 3 1 4 2 5 3
6 1 7 8 1 9 2 10
Pr( 1) (
)
t t t t
t t t t
j jj
Abn f Boost Boost Boost Boost Boost
Drag Drag Drag Drag DragCtrl
λ λ λ λ λ λ
λ λ λ λ λ
β ε
− + +
− + +
= = + + + + +
+ + + + +
+ +∑
+
+ (7)
Pump ( ) is set equal to 1 if the firm experiences an increase (decrease) in
discretionary accruals that more than offsets a decrease (increase) in unmanaged
earnings, zero otherwise. ( Drag ) is set equal to 1 if discretionary accruals are
positive (negative) and of greater magnitude than negative (positive) unmanaged
earnings. According to H3a, managers are expected, on average, to be more likely to
“pump” or “boost” earnings in the quarter during which they engage in abnormal sales to
postpone the revelation of poor future prospects to the market and/or inflate stock price to
increase their proceeds, so the coefficients on Pump
Dump
Boost
t and Boostt are expected to be
positive. Symmetrically, they are expected to be less likely to engage into abnormal
selling before a or scenario. The evidence in Ke et al. (2003) suggests that
insiders refrain from selling their stock within two quarters of a break in consecutive
earnings increases, but this result may not follow in terms of managed/unmanaged
earnings, therefore, while I expect a sign reversal for all sets of variables (e.g.
Dump Drag
1β (+) 2β (+) 3β (+) 4β (-) 5β (-)), I do not have specific predictions as to when they occur.
The further the reversal from the quarter during which the sale occurs, the more support
the evidence would give to the litigation avoidance hypothesis.
The fourth set of hypotheses relates to the potential market reaction to SEC filings
of insider sales. To test H4a and H4b, I use the following OLS regression model:
0 1 1 2 3 4
5 6 7
* *_
Abret PS Abnfit Abnfit PS PostRet PostRet PSBM Size R D
α α λ λ λ λλ λ λ ε
= + + + + +
+ + + + (8)
Model (8) tests the market reaction to SEC filings of insider sales using size-adjusted
returns measured over short-windows starting from the filing date and ending 2 to Abret
22
4 trading days after. The 2-day post-filing minimum requirement accounts for potential
delays between the filing date and the availability of its content to the public (though the
electronic filing requirement - effective July 2003 - mitigates this issue), while the 4-day
upper limit is consistent with that in Lakonishok and Lee (2001). is a dummy
variable equal to 1 if the insider trade was executed after August 29, 2002, zero
otherwise. So far, abnormal trades have been detected on a firm-year basis, which is not
timely enough for investors to react to individual trades throughout the year. To alleviate
this problem,
PS
Abnfit is constructed using only publicly available data. Details about the
estimation of Abnfit are provided in Appendix B. Although Abn is determined at the
firm-level using time-series data, determinants of Abnfit are also measured cross-
sectionally. The parameters, such as ex-ante litigation risk, size, book-to-market ratio,
R&D, trade size or past trading activity are borrowed from previous tests in this study.
Another advantage of such method is to produce a continuous variable between 0 and 1
as opposed to a binary one. 1λ captures whether the market discounts pre-SOX insider
sales the more abnormal they are, and is expected to be negative as such. The increased
timeliness of post-SOX insider trade disclosure may result in a stronger market reaction
to abnormal sales: 2λ measures this potential incremental post-SOX reaction and is
expected to be negative as well. I include the average daily abnormal return PostRet from
the transaction date to the day before the SEC filing as an independent variable to control
for the amount of information impounded into stock price before the trade is known to
the public, whether through disclosure or informed trading. Since the window is
significantly longer for pre-SOX trade, PostRet may have different implications before
and after SOX, so I allow for separate coefficients 3λ and 3λ + 4λ depending on the
disclosure regime. Finally, the control variables include log of market value, book-to-
market ratio, an R&D indicator variable and dummies for insiders’ position within the
firm (CEO, CFO, COO, Board Chairman and President). In light of the results in Aboody
and Lev (2000), R_D is expected to exhibit a significantly negative association with
Abret.
23
I test H2b and H3b in the same regression. Those two hypotheses predict the
effect of ex-ante litigation costs and discretionary accruals on the timing of insider sales
with respect to bad news. I run the following OLS regression for all profitable trades in
the sample (i.e. followed by six-month negative returns):
0 1 1 1 2 1 3 4
5 6 7 8 9
10
( ) * *
* *
*
t t t t
t t t t t
t j jj
Lostxprof Cumax Abn Lawfit Lawfit Abn Pump Pump Abn
Dump Dump Abn Boost Boost Abn Drag
Drag Abn Ctrl
α α β β β β
β β β β β
β β ε
− −= + + + + +
+ + + + +
+ + +∑
(9)
Lostxprof is defined as the proceeds from an insider sale times the cumulative abnormal
return Cumax (based on the 5-factor model used to compute Profit) from the transaction
date until the highest cumulative return is reached over a six-month window (zero if
cumulative abnormal returns are all negative) and can be interpreted as an opportunity
cost. Because Cumax is censored at zero by construction (hence so is Lostxprof), I also
use a Tobit specification (untabulated). According to H2b, 1β should be positive. Since I
already expect abnormal trades to be timed when 1tLawfit − is low (see H2a), the effect of
on 1tLawfit − Lostxprof may not be different for abnormal trades vs. normal trades, hence
there is no expected sign for 2β . The signs of 3β , 4β , 7β and 8β pertain to H3b. If
managers use discretionary accruals to inflate earnings and stock price and maximize
proceeds from their sale, they will trade closer to a peak in stock price before bad news
about future cash flows is revealed to the market, so these coefficients should be negative
(or only 4β and 8β if this holds exclusively for abnormal sales). By contrast, if managers
use positive (changes in) discretionary accruals to delay the recognition of bad news after
their suspicious sales, the positive returns following their sales should be greater, so those
coefficients should be positive, in particular 4β and 8β because of the higher litigation
concern associated with large sales. Dump and Drag are included for completeness,
although they are not of primary interest to this test. Other controls include size, book-to-
market and R&D.
24
5. Results
1) Sample and descriptive statistics
The data employed for the main tests in this study is gathered from three sources:
1) CRSP for stock price and trading volume related variables, 2) Compustat for financial
information and 3) Thomson Financial insider trading database. Additional data was
retrieved from the Stanford Securities Class Action Clearinghouse for 10b-5 lawsuits
information. Sample size varies by test depending on data requirements.
Thomson Financial Insiders Data Feed contains trade information from directors,
officers and principal stockholders with holdings over 10% of the firm’s stock, all subject
to disclosure requirements as defined in Section 16 of the Exchange Act of 1934 until
August 2002, and Section 403 of the Sarbanes-Oxley Act subsequently. I select all open
market purchases and sales (including those of shares resulting from option exercises)
executed by CEOs, CFOs, COOs, Chairmen of the Board and Presidents between 1989
and 2004. Trades between 1989 and 1994 are included to build histories of insider trading
for firms with data available in that period (a total 7,509 trades). The actual sample
period spans the 1995-2004 decade, which consists of 83,787 insider transactions14
(including 58,934 sales) for which shares outstanding data is available. Since in the pre-
SOX period, many trades (usually by the same insider in the same calendar month) are
reported on a single Form 4, I aggregate trades at the insider/filing date level in most of
the tests, in which case the sample contains 16,752 purchases and 35,413 sales. Using
reported transaction prices, the mean (median) dollar value of insider sales in my sample
is $955,754 ($166,577). As a percentage of shares outstanding (respectively shares held
by the insider), the average sale is 0.077% (11.59%) while the median is 0.025%
(3.42%)15. In terms of profitability, the mean (median) Profit for sales is $119,836
($12,225), and 67% of sales in the sample are profitable16. The mean and median
14This is after a cleansing process that eliminates transactions with reported prices outside of the lowest bid-highest ask available or CRSP, with a number of shares exceeding total common shares outstanding. 15 The reader should keep in mind that my holdings measure understates the true amount of managers’ stock holdings and exert caution in interpreting or comparing these results. 16 This is substantially higher than the proportion reported in Ke and Huddart (2004), which is potentially driven by the fact that my restrictive choice of insiders (“top managers”) biases towards more profitable
25
Ln_Profit are 2.47 and 1.60. The base case for abnormal trading detection17 results in
17,576 transactions (for 3,579 firm-years) being flagged. Other descriptive statistics can
be found in Table 1.
2) Short- and long-term returns following insider sales
The first hypothesis tests the timing and profitability of insider sales. Tables 2 and
3 report univariate results. Table 2 presents results for firms that have both normal and
abnormal sales in the sample period. As found in Panel A, the average across firms of the
difference between the mean aggregate yearly profit for abnormal and normal sales is
significantly positive for 3, 6 and 9 month horizons (0.01 level of significance for log
profits, 0.10 for raw profits). These results indicate that for the average firm and using a
six-month horizon, yearly average profits to abnormal insider sales are greater than
average normal profits by $1,110,668. Panel B reports similar results, at the individual
trade level. On average, in a given firm, abnormal sales are followed by six-month
abnormal returns that are 3.7% lower than normal sales, and represent profits greater by
$168,834 (all results are significantly different from zero at the 0.01 level).
Results reported in Table 3 are based on Net_Shrout quartiles (pooled cross-
sectional time-series) and indicate that within a given quartile, abnormal sales are – on
average – more profitable than normal sales, as the mean and median (log)profit is
significantly greater for abnormal vs. normal trades within all quartiles except for mean
profits in the fourth quartile, which is supportive of the contention that abnormal sales are
more likely to be information-motivated. The fact that for three out of four quarters, there
is no significant within-quartile difference between normal and abnormal mean
sales, plus differences in sample periods and abnormal return computation. Since the purpose of my study is to look at the differences between normal and abnormal sales, this remains of little concern. 17 i.e. including firm-years with zero trading as normal trading observations, classifying as abnormal total sales that exceed the past 2 to 5 years’ firm average by more than 3 standard deviations (or are more than 150% times the previous year’s level) both with respect to shares outstanding and shares held as deflators (provided the data is reliable for the latter, i.e. no trade is more than 100% of holdings and beginning-of-the-year holdings are consistent with previous year’s holdings). Note that in terms of holdings, firm-year aggregation is a weighted average across all insiders in the firm, whether they trade or not in a given year. Modifying the parameters has little impact on the classification of abnormal trades. For example, using 5 instead of 3 standard deviations and 200% instead of 150% results in 16,128 trades being flagged as abnormal.
26
Net_Shrout shows that using Net_Shrout as a linear measure of insider selling intensity
masks cross-sectional differences that can be identified with firm-level time series
comparisons. In order to introduce control variables, I analyze the association between
normal vs. abnormal sales and both short- (for timing) and long- (for profitability)
window returns around those sales, using a logit test. Table 4 summarizes the results with
respect to both timing and profitability. The negative and significant coefficient on FFRet
in column (1) indicates that the more bad news follow a trade over six months, the more
likely the trade is abnormal. By contrast, the significantly positive coefficient on PostRet
shows that abnormal sales are timed ahead of greater returns (more positive or less
negative) than normal sales. Since PreRet is insignificant, abnormal sales are not driven
by passive trading with respect to recent news. Column (2) summarizes the results where
the regression includes good/bad news dummy and interaction variables. The results are
consistent with the first hypothesis: abnormal trades are more likely to be profitable (i.e.
preempt 6-month negative abnormal returns), as captured by the significantly positive
coefficient on PosProfit, but not to be timed shortly before bad news (since the
coefficient on PostBad is insignificantly different from zero), so the loss avoided by
abnormal sales materializes further away from the trade. The coefficient on PostRet
indicates that the larger the positive returns following an insider sale, the more likely it is
abnormal. Also, abnormal trades do not appear to be timed after good news more than
normal sales, although they are more likely to be timed at an all-time high stock price
(coefficient on Allhi significantly positive). Other longer-run past performance measures
are insignificant (Rett-1 and ∆ROAt-1), which indicates overall that abnormal sales exhibit
more active than passive trading. As expected, firm size and book-to-market ratio are
negatively associated with Abn. Hence, so far, the results indicate that abnormal trades, as
detected using firm-level trading patterns, are more likely to be motivated by private
information. Next, I examine specific news events following insider trades to shed light
on the nature of the information that insiders trade upon.
3) Returns around earnings announcements after normal and abnormal sales
27
Table 5 presents the results with respect to the abnormal returns around quarterly
earnings announcements following insider sales. In Panel A, the univariate analysis
reveals that on average, the returns around the three earnings announcements following
abnormal sales are significantly more negative than those following normal sales, except
for the median return two quarters ahead. For example, the mean abnormal return around
next quarter’s earnings announcement is -0.71% for abnormal sales vs. -0.03% for
normal sales, the difference being significant at the 0.01 level. In Panel B, you can find
logit regression results. The coefficients on PosEAt, PosEAt+1 and PosEAt+2 indicate that
abnormal sales are significantly more likely to precede bad news two quarters ahead but
neither around the closest forthcoming earnings announcement nor two quarters later.
The insignificant coefficient on PosEAt is interpreted as the effect of litigation avoidance
while the one on PosEAt+2 may be due to this event being too far away from the trade
(more than six months). In terms of magnitude, most variables are insignificant. The
significantly negative coefficient on PosEAt*CarEAt shows that abnormal sales are less
likely to precede good news of large magnitude around the closest earnings
announcement. The results in Table 5 extend the findings of Roulstone (2004) who
documents that the occurrence of insider sales is negatively associated with abnormal
returns around up to three quarterly earnings announcements ahead. Hence, so far, the
results show that abnormal sales are more likely to avoid losses over a six-month horizon
than normal sales, and the negative returns partially materialize around subsequent
earnings announcements, albeit not the closest. The distance between abnormally large
sales and salient events such as earnings announcements conveying bad news is
consistent with the litigation avoidance argument mentioned in H1 as well as prior
research. However, these events do not capture all the bad news following large insider
sales, and the combination of abnormal insider selling with subsequent bad news is the
typical scenario that puts the firm and its officers at risk for a securities lawsuit. The next
results pertain to the interaction between firm-level litigation risk and insider sales.
4) Litigation and normal vs. abnormal sales
28
Table 6 presents the results of the tests related to H2a. In Panel A, univariate tests
indicate that overall, insider selling volume tends to be decreasing in litigation risk (4-6%
for highest sales quartile vs. 10-14% for the smallest), whether ex-ante or ex-post. Within
quartiles, except for the sales of smallest magnitude, the average ex-ante litigation risk is
significantly higher for normal selling activity. The litigation risk contemporaneous to
insider selling increases for both normal and abnormal sales, but more so for abnormal
sales, and the difference becomes insignificant. Finally, the ex-post average litigation cost
is significantly greater following firm-years with abnormal sales compared to normal
sales. The results in Panel A are thus indicative of insiders engaging in abnormal selling
activity when their litigation risk is relatively low, but once they do so, the firm bears a
higher litigation cost. Panel B reports the results of the logit analysis. The coefficients of
interest are of the expected sign, i.e. negative for 1tLawfit − (lower ex-ante litigation risk
for abnormal sales) and significantly positive for ex-post litigation risk . 1tLawfit +
5) Patterns of discretionary accruals and pre-managed earnings around normal vs.
abnormal insider sales
Table 7 reports the results with respect to the occurrence of earnings manipulation
around insider sales. The estimates on the left-(right-)hand side of the table report logit
regression results testing model 7 (8). As indicated by the signs on the Pump coefficients,
in any of the five quarters around an insider sale, normal sales are more likely than
abnormal sales to be timed when reported earnings appear to be “pumped”, i.e. with
discretionary accruals that offset an earnings decrease. The pattern of coefficients on
(negative, significant), 1tDump − 1tDump + (negative, significant) and (positive,
significant) is consistent with managers avoiding to time their abnormally large trades
after and shortly ahead of a quarter reporting an earnings decrease driven by large
discretionary accruals and delaying such bad news until the following quarter, where
income decreasing accruals exceed an otherwise positive change in pre-discretionary
accruals. The insignificant coefficient on may be due to the fact that managers
2tDump +
tDump
29
avoid selling their stock before reporting disappointing earnings, whether the amount of
sales is abnormal or not. In the test where levels of accruals are used instead of changes,
the significantly positive coefficients on 1tBoost − , tBoost and 1tBoost + indicate that
managers are more likely to engage in abnormal equity sales right before and after
reporting positive discretionary accruals that exceed in magnitude negative unmanaged
earnings. The results with respect to tBoost are consistent with H3a and both the
earnings-inflation and litigation avoidance explanations for the joint occurrence of high
discretionary accruals and abnormal insider selling activity. The positive coefficient on
1tBoost − indicates that managers also tend to engage in abnormal sales after inflating
earnings, which does not fit in the litigation avoidance story. This result does not
necessarily conflict with those in Beneish et al. (2005) but emphasizes the usefulness of
looking at the timing of insider sales on a quarterly basis. Finally, the significantly
negative coefficient on indicates that managers avoid reporting deflated earnings
right after their abnormal sales, which is also consistent with H3a. However, we observe
no sign reversal in the pattern of coefficients on Drag variables, so abnormal sales do not
seem to predict large negative discretionary accruals that would turn a profit into a loss
within a year. Taken together, the results in Table 7 indicate that managers use accruals
to avoid reporting losses around their abnormal sales and refrain from engaging into large
sales during quarters where a loss or an earnings decrease driven by discretionary
accruals is reported, which is more likely to occur two quarters away from their trades.
Despite the occurrence of income increasing accruals around abnormal insider sales, six-
months abnormal returns following those sales are more likely to be negative than for
normal sales. The next test presents results with respect to the effect of discretionary
accruals (and litigation) on the timing of stock returns after insider sales.
tDrag
6) Earnings inflation and timing of bad news following insider sales
Table 8 reports the joint test of H2b and H3b. The amount of good news
(measured in terms of opportunity cost Lostxprof or positive abnormal stock return
Cumax) following insider sales is positively associated with , which is 1tLawfit −
30
consistent with H2b, i.e. insiders time their sales further away from bad news as they face
a higher ex-ante litigation cost, so as to conceal their suspicious trades. The significantly
positive coefficient on Abn indicates that on average, profitable abnormal sales precede
larger positive stock returns (0.8%) than normal sales, which complements the results
related to H1. There is – however - no incremental slope effect for abnormal trades on the
association between ex-ante litigation cost and positive returns subsequent to insider
sales. The results in terms of discretionary accruals are such that the null of H3b is
rejected, but loss and earnings decrease avoidance have different implications for stock
returns following insider sales. For normal trades, both Pumpt and Boostt are significantly
negative, which indicates that in quarters where they are inflating earnings, managers are
more likely to trade at a peak in stock returns, which is consistent with their maximizing
their proceeds, possibly at an inflated price. This association is accentuated for abnormal
trades contemporaneous to loss avoiding accruals, since Boostt*Abn exhibits a
significantly negative coefficient: the proceeds-maximizing explanation for the joint
occurrence of earnings inflation and abnormal insider sales as developed by Bartov and
Mohanram (2004) is descriptive in the case of loss avoiding accruals. By contrast,
Pumpt*Abn being significantly positive (as well as the sum of Pumpt and Pumpt*Abn,
according to an F-test not reported in Table 8), managers appear to time their abnormal
sales away from the reflection of bad news in stock price when an earnings decrease is
offset by an increase in discretionary accruals. Such result is consistent with managers
delaying bad economic news using positive accruals in order to decrease their exposure
to litigation, as Beneish et al. (2005) argue. However, since the previous table indicates
that managers are less likely to engage in abnormal selling when offsetting earnings
decreases with accruals, another possible interpretation from the results in both sets of
tests is that “pumping” earnings is associated with higher litigation risk, which is why
managers refrain from selling suspicious amounts of stock contemporaneously, and even
when they do so, they time their trades away from the revelation of bad news with respect
to future cash flows.
7) Market reaction to insider sales SEC filings
31
Table 9 presents the results of market reactions to insider sales SEC filings tests.
Panel A reports univariate results for three-day returns ( 0,2Abret ). They indicate that the
differences in mean and median return between the highest and lowest quintiles of Abnfit
are significantly negative for post-SOX trades but not pre-SOX, which is consistent with
the market reacting more negatively to insider sales disclosure when sales are more
“suspicious”, but only after SOX. In addition, in all quartiles, the median return for post-
SOX trades is significantly negative, as opposed to the bottom three quartiles in the pre-
SOX sub-sample, which suggests that the market reaction to insider sales is generally
more pronounced post-SOX. The regression results in Panel B are tabulated for five-day
abnormal returns starting on the filing date ( 0,4Abret ). The coefficient on Abnfit is
insignificant, while the one on *Abnfit PS is significantly negative (-1.14%). This
suggests that market participants impose a greater discount to stock price when they learn
about a trade and assess that it is more likely to be private information motivated, but
only so after Section 403 came to effect (an untabulated F-test shows that the sum of the
two coefficients is significantly negative). Finally, the coefficient on PostRet is strongly
significant and positive, which shows that the return following the disclosure of insider
sales is positively associated with the return between the trade and its disclosure. This is
consistent with the market expecting more bad news when learning from a trade
immediately followed by bad news, but other explanations are plausible. From Panel A
and Panel B, we can conclude that market participants revise their beliefs about the
intrinsic value of the stock downward after the disclosure of insider sales when those
appear as suspicious, but only for trades subject to disclosure requirements of Section 403
of SOX.
6. Conclusion
This paper investigates the timing of abnormally large insider sales with respect to
forthcoming news, in terms of stock returns and accounting numbers, and the information
content of insider trade disclosure based on whether they are abnormal or not.
The findings indicate that abnormal insider sales are more likely to be followed
by negative stock returns on the medium/long term (several months) but not the short-
32
term (within a month). Those returns materialize partly around earnings announcements,
albeit not the closest one following abnormal sales. In addition, I explicitly document that
managers are less likely to engage into abnormal stock selling activity when their firm-
level ex-ante litigation cost is high. Hence, when managers decide to increase their stock
sales to a level that raises suspicion, they do so under conditions that limit the risks of
triggering a securities lawsuit.
As suggested by the patterns of discretionary and non-discretionary portions of
earnings around insider sales, managers are more likely to use discretionary accruals to
avoid reporting losses in the quarters around their abnormal sales. The evidence also
suggests that insiders delay the recognition of earnings decreases driven by discretionary
accruals two quarters away from their large sales. The positive stock returns following
insider sales contemporaneous to income increasing discretionary accruals indicate that
when avoiding losses, managers time their trades close to a peak in returns, whereas they
delay the recognition of bad news after their trades when avoiding to report an earnings
decrease. That said, because insiders tend not to use positive accruals to offset earnings
decreases around their abnormal sales, the proceeds-maximizing interpretation of the
joint occurrence of high insider selling activity and income-increasing accruals appears to
be more descriptive than the litigation avoidance one.
The results of this study are also consistent with market participants reacting to
disclosure about insider sales, especially under the new disclosure regime as defined by
Section 403 of SOX, whereby insiders are required to file a Form 4 with the SEC within
two business days. Post-SOX returns around Form 4 filing dates of insider sales are
negatively associated with the probability that the trade is private-information motivated.
The empirical tests in this paper are subject to several caveats. First of all, the
parameters chosen for the normal/abnormal trade distinction are very arbitrary, and for
lack of reliable data availability on insider holdings in many cases, missing an important
determinant of insider liquidity needs. That being said, the purpose of this study is not to
determine equilibrium levels of insider trading and obtain complete separation of
opportunistic sales from liquidity sales, but rather show that techniques accepted in courts
to establish that managers acted with scienter are useful in detecting private-information
based trades. Other proxies such as discretionary accruals and the fitted probability of
33
litigation cost also measure with error the true variables used by managers in their
trading/reporting decision model, to an extent that remains unknown. As for the returns
around Form 4 filing dates, they are consistent with a market reaction to the trade(s)
being filed, but I cannot rule out the possibility that they are driven by other news.
Finally, potential issues of endogeneity are rampant in the insider trading literature.
However, the private information that jointly determines insiders’ trading and disclosure
decisions is unobservable, so finding valid instruments remains challenging.
This study warrants additional tests to increase the validity of the results and gain
more insight into questions such as how litigation affects managerial decisions to resort
to earnings manipulation around their suspicious sales. Further investigation on the
information content of insider sales and market’s responsiveness to their disclosure is
also on my agenda.
34
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Appendix: Estimation of Lawfit and Abnfit Litigation cost (Lawfit): this model is directly adapted from Rogers and Stocken (2005), the only difference being that I use logit instead of probit and run the model on an annual basis.
0 1 2 3 4 5
6 7
Pr( 1) ( _ _ )j
j
Litigation f Size Turnover Beta Return Std RetSkewness Min Ret HighRiskIndustries
α γ γ γ γ γ
γ γ γ
= = + + + + +
+ + +∑ ε+ (10)
Litigation: dummy equal to 1 if a securities class action lawsuit was recorded by the Securities Class Action Clearinghouse during a calendar year, zero otherwise. Explanatory variables include log firm size, average daily share turnover, stock beta measured against CRSP value-weighted index, cumulative annual raw return, standard deviation of daily returns, lowest daily return and dummies for high litigation risk industries (biotech, computer hardware, electronics, retailing and software). For more details, refer to Appendix A in Rogers and Stocken (2005). Lawfit distribution (pooled cross-sectional time-series sample, observations are firm-years):
N Mean (%)
Std Dev. (%)
1st quartile (%)
Median (%)
3rd quartile (%)
43,519 3.76 6.10 0.94 1.88 3.98 Probability that a trade is abnormal (Abnfit):
0 1 2 3 4 1 5
6 7 1 8 1 9 10 11
12
Pr( 1) ( * + _ _ _ )
t
t t
k kk
Abn f PreGood PreRet PreGood PreRet Lawfit BMSize ROA Ret Allhi Net Shrout Lag ShroutR D Position
β β β β β ββ β β β β β
β β ε
−
− −
= = + + + ++ + ∆ + + + +
+ + +∑ (11)
All variables in this model are listed in the variable definition list, except Lawfit which is described above. The model uses data available prior to insider sales. The coefficients are estimated separately for each calendar year from 1996 to 2004 using data from the previous year. Abnfit distribution: N Mean
(%) Median
(%) Std Dev. (%) #>50%
1996 604 42.4 40.5 25.1 227 1997 732 37.3 35.7 25.1 229 1998 830 39.4 39.5 23.1 275 1999 865 42.1 41.4 23.6 317 2000 1,426 50.0 51.5 22.9 743 2001 2,014 40.3 40.5 24.1 704 2002 2,354 36.2 40.9 23.6 771 2003 4,790 31.2 32.2 22.5 1,062 2004 3,437 27.9 27.9 22.1 660
39
Variable definitions
A few terms: Insider: CEO, CFO, COO, Chairman of the Board, President. Purchase (sale): open market purchase (sale) of common shares. Sales following option exercises are included in the sample, but not the actual option exercise. Insider Trading Variables: Net_shr Number of shares sold by an insider on a transaction date. Held Maximum number of common shares held by an insider over a
calendar (fiscal) year. Includes shares holdings and exercised options. Net_hold Net_shr divided by Held on a given transaction date. Shrout Number of common shares outstanding. Net_shrout Net_shr divided by Shrout on a given transaction date. Lag_hld Net_shr divided by Held over the previous calendar (fiscal) year. Lag_shrout Total insider-year level Net_shr divided by Shrout over the previous
calendar (fiscal) year. Position Set of dummy variables taking the value of 1 if the insider’s title is
CEO, CFO, COO, Chairman of the Board or President, zero otherwise.
Profit FF_Ret (see definition below) times Net_shr times the transaction price as reported by the insider on a given transaction date.
Ln_ Profit Natural logarithm of unsigned Net_shr times the reported transaction price, times FF_Ret.
Abn Dummy variable set equal to 1 if total Net_shrout and Net_hold at the firm-year level is more than 3 standard deviations above its past mean based on up to five years. If only one year of prior trading is available, Abn equals 1 when Net_shrout and Net_hold are 50% higher than the previous year. Abn equals zero otherwise.
Abnfit Fitted probability of a trade being abnormal, using a logit regression of Abn on variables listed in Appendix B.
Return and Litigation Variables PreRet Average daily size-adjusted return over the 10 trading days prior to
the first transaction date as reported on a Form 4 SEC filing. PreGood Dummy variable equal to 1 if PreRet is strictly positive. PostRet Average daily size-adjusted return from the first transaction date as
reported on a Form 4 SEC filing until the filing date. PostBad Dummy variable equal to 1 if PostRet is strictly positive. Abret Size-adjusted return starting on Form 4 SEC filing date of an insider
sale. Window ends 1 to 4 trading days after the filing date. CarEAt Three-day size-adjusted return around quarter t earnings
40
announcement date. PosEAt Dummy variable equal to 1 if CarEAt is positive, zero otherwise. FF_Ret 6-month five-factor adjusted return. Factor loadings are estimated
using a regression of daily returns on the four factors as in Carhart [1997] and an earnings quality factor as in Aboody et al. (2005) over the two-year period prior to the calendar month where each insider transaction occurs. Daily abnormal returns are computed as the difference between the actual raw return and the predicted return using the daily factors and the loadings from the first-stage regression. Daily abnormal returns are then summed over six months after the trade.
Lawfit Estimated probability that a Rule 10b-5 securities lawsuit will be filed against a firm in a given year, using a model akin to that in Rogers and Stocken (2005).
Accrual variables Dat Quarter t discretionary accruals, calculated using the cross-sectional
version of the Jones (1991) model, as in Dechow et al. (1995) PreDAt Net income before extraordinary items and DatPumpt Dummy variable equal to 1 if ∆Dat is positive, ∆PreDAt negative and
∆DAt exceeds ∆PreDAt in terms of magnitude, zero otherwise. Dumpt Dummy variable equal to 1 if ∆DAt is negative, ∆PreDAt positive and
∆DAt exceeds ∆PreDAt in terms of magnitude, zero otherwise. Boostt Dummy variable equal to 1 if DAt is positive, PreDAt negative and
DAt exceeds PreDAt in terms of magnitude, zero otherwise. Dragt Dummy variable equal to 1 if DAt is negative, PreDAt positive and
DAt exceeds PreDAt in terms of magnitude, zero otherwise. Control Variables Size Natural logarithm of the market capitalization of the firm, as of the
end of the most recent fiscal quarter. BM Book value of common stockholder equity divided by market value
of equity, as of the end of the most recent fiscal quarter. ∆ROAt-1 Change in ROA from fiscal year t-2 to t-1, where ROA is defined as
operating income before depreciation over total assets. Rett-1 Buy-and-hold raw return over the most recent past fiscal quarter. R_D Indicator variable equal to 1 if the firm reported a non-zero R&D
expense in the most recent fiscal quarter, 0 otherwise. All_hi Indicator variable set equal to 1 if the price on the insider transaction
date is an all time high (compared to past split-adjusted prices), 0 otherwise.
41
Table 1: Descriptive statistics
Variable Mean Std Dev 25th Median 75th
Insider trading Net_hold (%) 11.59 19.06 7.06 3.43 13.03 Net_shrout (‰) 0.80 2.76 0.09 0.26 0.72 Returns and profits Pre_dxret (%) 0.22 1.00 -0.33 0.14 0.71 Post_dxret (%) 0.00 1.11 -0.57 -0.02 0.52 Profit ($) 119,836 364,056 -2,611 12,225 88,638 Ln_Profit 2.52 4.88 -0.45 1.57 4.88 Form 4 filing returns and volumes
Aret0,1 (%) -0.09 4.03 -1.97 -0.15 1.64 Aret0,4 (%) -0.43 6.68 -3.53 -0.30 2.79 News CarEAt (%) 0.39 7.57 -3.32 0.19 3.95 CarTent (%) -0.04 5.16 -2.57 -0.17 2.30 Accruals DAt (%) 2.12 12.47 -4.22 2.04 8.42 PreDAt (%) -0.92 27.11 -7.35 0.74 8.92 Controls Ln_Market 6.01 1.89 4.65 5.94 7.17 BM 0.53 0.51 0.23 0.43 0.71 ∆ROAt-1 (%) 0.09 5.89 -0.92 0.00 0.89 Rett-1 (%) 6.93 36.65 -11.38 2.49 17.65 All_hi 0.04 - - - - R_D 0.42 - - - -
42
Table 2: profitability of insider sales – firm by firm analysis Panel A: firm-year aggregate profits (mean and median of firm-level means) Profits (proceeds from sale times 3/6/9-month abnormal return following trade times (-1)) accruing to insider sales are aggregated at the firm-year level. The mean firm-level aggregate profit is then calculated separately for years with normal trades (Abn=0) and abnormal (Abn=1). The table reports the mean and median across firms of the difference between the firm-level mean profits for Abn=1 and Abn=0, using 3,6 and 9 months to compute abnormal returns. Same for log(profits) where proceeds are transformed using natural logarithm.
Abn=1 – Abn=0 3 months 6 months 9 months Mean difference in profits 469,131***
(2.60) 757,198***
(3.45) 1,076,350***
(3.09)
Median difference in profits 9,380*** (71.5)
21,306*** (96.5)
32,091*** (105.5)
Mean difference in log profits 2.71*** (2.67)
5.19*** (2.81)
7.93*** (2.81)
Median difference in log profits 0.22* (37.5)
0.81*** (65.5)
1.28*** (85.5)
N 1,982 1,982 1,982 Panel B: trade-specific returns and profits (mean and median of firm-level means) Abnormal profits/returns are averaged at the firm-level separately for Abn=1 and Abn=0 individual insider sales. The table reports the mean and median of the difference across firms between the firm-level mean profits/returns for Abn=1 and Abn=0, using 3,6 and 9 months to compute abnormal returns. Same for log(profits) where proceeds are transformed using natural logarithm.
Abn=1 – Abn=0 3 months 6 months 9 months Mean difference in profits ($) 109,172***
(5.06) 196,266***
(4.91) 310,000***
(5.49)
Median difference in profits ($) 1,959*** (66.5)
3,433*** (79.5)
5,926*** (103.5)
Mean difference in log profits 0.19** (2.37)
0.44*** (3.43)
0.70*** (3.96)
Median difference in log profits 0.03 (30.5)
0.17*** (91.5)
0.23*** (109.5)
Mean difference in returns -0.010 (-1.57)
-0.026** (-2.51)
-0.042*** (-2.98)
Median difference in returns 0.000 (1.5)
-0.007*** (-77)
-0.009*** (-89.5)
N 2,268 2,268 2,268 ***,**,* indicate that the means and medians are significantly different from zero at the 0.01, 0.05 and 0.10 levels, based on t-stats for means and sign tests for medians (reported in parenthesis).
43
Table 3: profitability of insider sales – cross-sectional quartile analysis
This table presents results from a univariate analysis of profits (proceeds from sale times 6-month abnormal return following the sale times (-1)) accruing to insider sales. The mean and median profits and log-profits (same as profits but proceeds are natural log transformed) are reported separately for normal (Abn=0) and abnormal (Abn=1) sales, within each quartile of the distribution of Net_shrout (number of shares traded scaled by number of shares outstanding), based on all insider sales in the sample period 1995-2004. The rows labeled “Difference” report t-statistics for differences in means, z-statistics for differences in medians and corresponding p-values.
Variable Q1 Q2 Q3 Q4 Mean Median
Mean Median Mean Median Mean Median
Abn=0
0.0084% 0.0076% 0.036% 0.036% 0.100% 0.095% 0.494% 0.325%Abn=1 0.0086% 0.0081% 0.037% 0.036% 0.102% 0.097% 0.626% 0.338%Net_shrout Difference -1.11
(0.27) -0.75 (0.45)
-1.42 (0.15)
1.53 (0.12)
-1.69 (0.09)
-1.55 (0.12)
-3.31 (<0.01)
-2.21 (0.03)
Abn=0
117,633 8,503 225,726 24,616 477,527 56,693 1,140,070 126,585Abn=1 200,899 10,096 434,886 38,641 829,778 84,239 1,581,296 182,579Profit Difference -2.62
(<0.01) -2.50 (0.01)
-2.83 (<0.01)
-4.37 (<0.01)
-2.58 (<0.01)
-5.43 (<0.01)
-1.26 (0.21)
-3.08 (<0.01)
Abn=0
3.87 1.43 4.98 2.21 6.88 3.14 9.99 4.80Abn=1 4.68 1.68 7.57 3.07 10.21 4.39 11.93 5.35Ln_Profit Difference -1.11
(0.27) -2.27 (0.02)
-3.04 (<0.01)
-4.30 (<0.01)
-3.81 (<0.01)
-4.81 (<0.01)
-1.66 (0.09)
-2.27 (0.02)
Abn=0
2,385 2,366 2,315 2,070N Abn=1 1,204 1,224 1,275 1,519
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Table 4: Timing and profitability of insider sales - Logit
This table provides logit regression results for the association between the classification of insider sales as normal (Abn=0) or abnormal (Abn=1) and the following independent variables: short-window daily abnormal returns around trades (PreRet before, PostRet after) and profitability (six-month return after trade FFRet). Since each firm-insider-reporting date observation may include several transactions, returns are an average of returns following each transaction weighted by the proceeds. Model (1) includes only magnitudes of those variables, while Model (2) includes dummy variables PreGood, PostBad and PosProfit equal to 1 respectively if the insider sale is timed right after a 10-day positive abnormal return, right before a negative abnormal return measured until the SEC filing date of the trade and if the six-month abnormal return following the sale is negative. Model (2) includes interaction terms. The sample is restricted to pre-SOX trades (i.e. transactions before August 29, 2002). Calendar year dummies are included but not tabulated. Variable Expected
sign Coefficient (Chi-Square) Coefficient (Chi-Square)
(1) (2) Intercept ? -0.636*** (29.39) -0.834*** (35.60)
PreGood -0.036 (0.40)
PreRet 0.2186 (0.03) -4.514 (0.98)
PreGood*PreRet 6.447 (1.69)
PostBad 0.037 (0.43)
PostRet 6.5956*** (11.81) 10.573*** (7.58)
PostBad*PostRet -6.796 (1.32)
FFRet - -0.3293*** (49.27) -0.129 (0.72)
PosProfit + 0.195*** (8.94)
PosProfit*FFRet - -0.104 (0.39)
Size -0.0527*** (17.95) -0.046*** (13.02)
BM - -0.2491*** (12.28) -0.236*** (10.98)
∆ROAt-1 -0.1459 (0.17) -0.146 (0.17)
Rett-1 0.0137 (0.11) 0.013 (0.10)
All_Hi + 0.3211*** (11.08) 0.334*** (11.85)
R_D -0.1647*** (13.70) -0.180*** (15.86)
Percent concordant 59.2 59.5 Likelihood Ratio 264.53*** 280.35***
N (Abn=1 / Abn=0) 10,172 (3,460 / 6,712) ***,**,* indicate significance at the 0.01, 0.05 and 0.10 levels
45
Table 5: Normal vs. abnormal insider sales and subsequent earnings announcement returns
Panel A: mean and median 3-day abnormal returns around the 3 earnings announcements following an insider sale, computed separately for normal (Abn=0) and abnormal (Abn=1) sales. T-statistics and Z-statistics are reported for mean and median differences.
CarEAt CarEAt+1 CarEAt+2Returns in % Mean Median Mean Median Mean Median Abn=0 -0.25 -0.07 -0.03 0.29 -0.13 -0.15
Abn=1 -0.75 -0.22 -0.71 -0.25 -0.43 -0.05
T-stat or Z-stat for difference -3.80*** -3.13*** -5.07*** -5.86*** -2.29** 1.57
Panel B: logit regression results for the timing of abnormal (Abn=1) vs. normal insider sales (Abn=0) with respect to earnings announcements at the end of the quarter contemporaneous to the insider sale as well as the next two. The model includes dummy variables equal to 1 when the returns around those events are positive (PosEA), magnitudes of the returns (CarEA) and interaction terms. The independent variables also include controls (tabulated) and calendar year dummies (untabulated).
Variable Exp. Coefficient Chi-Square sign (1) Intercept -0.211** (3.74)
PosEAt - -0.018 (0.15)
PosEAt+1 - -0.146*** (10.37)
PosEAt+2 - -0.047 (1.12)
CarEAt 0.335 (1.15)
CarEAt+1 -0.258 (0.67)
CarEAt+2 -0.170 (0.29)
PosEAt* CarEAt -0.882* (3.00)
PosEAt+1* CarEAt+1 0.613 (1.57)
PosEAt+2* CarEAt+2 0.092 (0.04)
BM - -0.120** (4.74)
Size - -0.118*** (123.46)
∆ROAt-1 0.077 (0.06)
Rett-1 0.147*** (12.39)
All_Hi + 0.459*** (28.07)
R_D -0.182*** (26.38)
% concordant 62.7 Likelihood ratio 781.71
N (Abn=1/Abn=0) 17,166 (5,859/11,307) ***,**,* indicate significance at the 0.01, 0.05 and 0.10 levels
46
Table 6: litigation and abnormal sales
Panel A: this table reports mean litigation costs separately for normal and abnormal insider selling firm-years within quartiles based on the distribution of Net_Shrout aggregated at the firm-year level across all sample observations from 1995 to 2004. Estimated probabilities of a Rule 10b-5 lawsuit being filed in the years before (Lawfitt-1), contemporaneous (Lawfitt) and after (Lawfitt+1) each firm-year observation are computed. Within-quartile differences are reported, as well as t-statistics in parenthesis. Quartile 1 Quartile 2 Quartile 3 Quartile 4
Abn=0 10.2% 7.3% 6.5% 5.0% Abn=1 10.4% 6.2% 5.6% 4.1%
Lawfitt-1
Diff. -0.2% (-0.66)
1.1%*** (5.60)
0.9%*** (4.70)
0.9%*** (6.38)
Abn=0 11.7% 8.1% 7.2% 6.0% Abn=1 14.1% 7.8% 7.4% 6.1%
Lawfitt
Diff. -2.4%*** (-6.56)
0.3% (1.34)
-0.2% (-0.93)
-0.1% (-0.54)
Abn=0 10.6% 7.3% 6.7% 5.6% Abn=1 10.6% 8.8% 7.4% 6.0%
Lawfitt+1
Diff. -0.0% (-0.14)
-1.5%*** (-7.16)
-0.7%*** (-3.89)
-0.4%** (-2.22)
***,**,* indicate significance at the 0.01, 0.05 and 0.10 levels Panel B: Logit analysis of normal (Abn=0) vs. abnormal (Abn=1) insider selling firm-years on ex-ante, contemporaneous and ex-post litigation cost (Lawfit), plus controls, and non-tabulated calendar year dummies.
Variable Expected sign
Coefficient (Chi Square)
Intercept 0.316** (4.48)
Lawfitt-1 - -3.293*** (27.43)
Lawfitt 0.500 (1.08)
Lawfitt+1 + 1.761*** (15.43)
Size -0.086*** (16.09)
BM -0.307*** (12.75)
∆ROAt-1 -0.477 (0.85)
Rett-1 0.047 (0.54)
R_D -0.261*** (16.30) Percent concordant 59.0 Likelihood Ratio 103.55
N (Abn=1/Abn=0) 4,967 (1,851 / 3,116) ***,**,* indicate significance at the 0.01, 0.05 and 0.10 levels
47
Table 7: normal vs. abnormal insider sales and discretionary accruals This table reports logit regression results for differences in patterns of discretionary accruals and unmanaged earnings around normal (Abn=0) and abnormal (Abn=1) insider sales. Model (1) includes dummy variables Pump (Dump) equal to 1 if the firm reports a positive (negative) change in quarterly discretionary accruals that exceeds in magnitude a negative (positive) change in pre-discretionary accruals earnings, zero otherwise. Model (2) includes similar variables (Boost and Drag), except that they are defined in terms of levels of discretionary and non-discretionary portions of income instead of changes. For both models, the subscript indicates the quarter over which those earnings components are calculated, t being the quarter during which the insider sale occurs. Calendar year dummies are included but not tabulated. Variable Coefficient Chi-square Variable Coefficient Chi-square (1) (2) Intercept -1.096*** 23.76 Intercept -0.988*** 23.89
Pumpt-1 + -0.041 0.48 Boostt-1 + 0.142** 7.47
Pumpt + -0.101* 2.99 Boostt + 0.276*** 27.50
Pumpt+1 -0.108* 3.40 Boostt+1 0.105** 4.24
Pumpt+2 -0.048 0.62 Boostt+2 -0.210*** 15.81
Pumpt+3 -0.238*** 13.91 Boostt+3 -0.138*** 6.89
Dumpt-1 - -0.340*** 24.87 Dragt-1 - 0.048 0.19
Dumpt - 0.098 2.12 Dragt - -0.430*** 11.32
Dumpt+1 -0.191*** 7.95 Dragt+1 -0.138 1.55
Dumpt+2 0.303*** 22.98 Dragt+2 0.010 0.01
Dumpt+3 -0.069 1.17 Dragt+3 -0.159 2.34
BM -0.039*** 10.18 BM -0.153** 4.75
Size -0.074*** 22.52 Size -0.100*** 49.32
∆ROAt-1 -0.550 0.94 ∆ROAt-1 -0.326 0.56
Rett-1 0.208 0.27 Rett-1 0.138*** 7.99
All_Hi 0.429*** 11.23 All_Hi 0.473*** 16.59
R_D -0.055 1.25 R_D 0.029 0.40 % concordant 64.2 64.0
Likelihood ratio 477.74 565.88 N (Abn=1/0) 8,994 (2,806 / 6,188) 10,467 (3,506 / 6,961)
***,**,* indicate significance at the 0.01, 0.05 and 0.10 levels
48
Table 8: distance to bad news, litigation and discretionary accruals This table reports OLS regression results. In model (1), the dependent variable is the profit forgone by insider sales measured between the transaction date and the date where abnormal returns reach their highest point within six months. In model (2), the dependent variable is simply the abnormal return aforementioned. Only trades that are followed by a negative six-month abnormal return are included in the sample. The main variables of interest are Lawfitt-1 (ex-ante litigation cost), Pump/Dump (dummy variable equal to 1 if current quarter discretionary accruals are positive/negative and exceed negative/positive pre-managed earnings, either in terms of changes, zero otherwise) and Boost/Drag (dummy variable equal to 1 if current quarter discretionary accruals are positive/negative and exceed negative/positive pre-managed earnings, either in terms of levels, zero otherwise). T-statistics are reported in italic.
Ln_Lostprof Cumax (1) (2)
Expected sign Coefficient t-stat Coefficient t-stat
Intercept 1.654*** 21.93 0.163*** 26.09
Abn + 0.155*** 3.38 0.008** 2.15
Lawfitt-1 + 1.395*** 6.09 0.112*** 5.90
Lawfitt-1*Abn + -0.083 -0.21 -0.010 -0.32
Pumpt -0.061 -1.56 -0.006* -1.75
Pumpt *Abn 0.182*** 2.66 0.020*** 3.49
Boostt -0.097*** -2.51 -0.009*** -2.78
Boostt *Abn -0.123* -1.91 -0.010* -1.80
Dumpt -0.076 -1.63 -0.006 -1.47
Dumpt *Abn 0.006 0.07 0.001 0.16
Dragt 0.031 0.40 0.003 0.42
Dragt *Abn -0.099 -0.69 -0.000 -0.04
BM -0.190*** -4.09 -0.014*** -3.51
Size -0.109*** -11.31 -0.013*** -16.62
R_D 0.176*** 6.12 0.017*** 7.02
R2 4.41% 2.81% N 9,471 9,471 *,**,*** indicate significance at the 0.10, 0.05 and 0.01 level.
49
Table 9: returns around SEC filings of insider trades and probability that the trades are abnormal
Panel A: mean and median three-day returns (Aret0,2) starting on filing dates of insider sales, per quartile of Abnfit (constructed for each calendar year), separately for pre- and post- August 29, 2002 trades. The last two columns report the difference in means or medians between the two extreme quartiles and t-stats (Wilcoxon Z-stats) for differences in means (medians). Abnfit Q1 Q2 Q3 Q4 Q4-Q1 t- or Z-stat
Mean -0.07 -0.13 -0.32† -0.01 0.06 0.29
Pre-SOX Median -0.22 -0.03 -0.33† -0.15 0.07 0.26
N 1,611 1,673 1,636 1,551
Mean 0.03 0.01 -0.10 -0.28† -0.31*** -2.75
Post-SOX Median -0.09 -0.24† -0.14† -0.25† -0.16*** -2.66
N 2,093 2,039 2,708 2,145 † indicates that the mean or median is significantly different from zero at the 0.10 level or better. Panel B: results from OLS regression where the dependent variable is the five-day abnormal return Aret0,4 starting on the filing date of an insider sale. The independent variables are a dummy PS equal to 1 if the trade was executed after August 29, 2002 (subject to filing requirements of Section 403 of SOX), the fitted probability Abnfit that the trade is private information-motivated, and the average daily return PostRet from the transaction date until the day before the filing date, plus interaction terms and additional controls (incl. untabulated dummy variables for reporting insiders’ position in the firm, i.e. CEO, CFO, COO, Board Chairman).
Variables Exp. sign
Aret0,4 t-stats
Intercept -0.653** -2.00
PS 0.430** 2.37
Abnfit - 0.043 0.14
Abnfit*PS - -1.141*** -2.60
BM 0.228 1.41
Size 0.042 1.27
R_D - -0.184* -1.68
PostRet + 16.642*** 10.41
PostRet*PS 4.359* 1.90
Adj. R2 1.91% F value 25.06*** Obs. 14,825
In both panels, ***,**,* indicate two-tailed significance at the 0.01, 0.05 and 0.10 levels. In panel B, t-stats are based upon standard errors robust to heteroskedascity, using the Newey-West correction procedure.
50