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An empirical analysis of the information content of aggregate Insider
trading in the French context
Meriem JERBi
Phd student, Prism, University of Paris I Sorbonne
Bahram SOLTANI (corresponding author)
Associate Professor University of Paris I Sorbonne
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ABSTRACT
This paper examine corporate insider trading using the data extracted manually for French
companies during the period of 2007-2010. The major objective of the study is to empirically
investigate several important issues concerning the characteristics of corporate insider trading
and the conformity of transactions with mandatory regulations of the European Directive of
2003 on market abuse.
We investigate the time series trend change of corporate insider transactions during the period
of financial crisis. Results show that under favorable market conditions, they increase their
sell transactions, and when market performance falls they intensify their purchase
transactions.
We also investigate the reasons of increasing number of insider transactions to determine
whether this is due to their contrarian strategy (market to book value and volume) or private
information on firm future performance (return variation and ROA variation between 2009
and 2008). Results are significant for contrarian strategy assumption as we find negative
significant relation between insider trading ratios and trading volume and market to book
ration. It appears that corporate insiders select the undervalued stocks with high future returns.
This study is a contribution to literature in insider trading and may have practical implications
for regulatory and professional bodies.
JEL Classification: G01, G02, G11, G12, G14
Key words: insider trading, MAD EC directive, financial crisis, contrarian strategy,
private information, company’s future performance
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An empirical analysis of the information content of aggregate Insider
trading in the French context
Introduction
There has been an overwhelming debate on insider trading since the inception of the financial
market. The recent spate of corporate and financial crises have highlighted in dramatic
fashion further reflection on this issue. However, an important aspect of insider trading is
related to the transactions made by corporate management and those who represent the major
shareholders within company. For various reasons, particularly the influential position of
these groups, it is essential to identify the circumstances in which corporate insiders have
traded. Whether they have bought on balance before abnormally good price movements and
sold on balance before poor market periods for the stocks of their companies. It is equally
important to investigate about the incentives of corporate traders and ethical issues involving
the insider transactions.
The interest in insider trading is threefold. First, from the academic perspective, it
involves several theoretical discussions regarding particularly the economics of information,
theories of justice, information asymmetry and informational advantage, signaling effect,
pricing and market performance, predictive value of information it may convey and its effect
on market efficiency and quality. Insider trading has also several practical implications
notably in terms of contrary-opinion rules, market overreaction, top management role in
corporate reporting, earnings announcements and cash flows prospects. Finally, the topic of
insider trading concerns ethical considerations and corporate management behavior,
managers’ incentives and their personal interests, fraudulent actions and conflicts of interest.
Because of its multi-dimensional effects on market performance, perceptions of investors and
analysts and their decision-making processes, the regulatory bodies have shown particular
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interest in shaping the characteristics of insider trading and the effective policies in this area.
The regulatory efforts undertaken by the SEC in the United States and the European
Commission in Europe have accelerated particularly since the beginning of this century and
following several high profile financial scandals and management misconduct that began to
surface from late 2001 to 2003.
This paper aims to examine corporate insider trading in the European context by using
the data extracted from French market. The major objective of the research study is to
empirically investigate several important issues such as the reasons of shares’ trading
undertaken by members of top management and those representing major shareholders,
whether such transactions produce favorable outcome, the effect of these transactions on
market liquidity and the conformity of transactions with mandatory regulations of the
European Directive 2003 on insider dealing and market manipulation (market abuse). This
directive was among several other regulatory initiatives introduced, in the form of directive or
regulation, by the European Commission in 2002 and 2003. They essentially deal with buy-
back programs and stabilization of financial instruments (EC 2273/2003), quality of
disclosure prospectus of listed companies EC 203/71), fair presentation of investment
recommendations (EC 2003/125) and the application of international accounting standards
(EC1606/2002). All these mainly aim at improving the quality of information disclosed by
public companies and market functioning.
The remainder of the paper is organized as follows. Section II contains a discussion on
theoretical framework including literature review. Section III presents an overview of
regulatory framework especially in the European context. Data sources, sample companies,
research design and questions are presented in Section IV. This will be followed by the
analysis of our empirical results. The final Section discusses the concluding remarks,
contributions and limitations of study.
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Theoretical framework
The academic debate and early research work on insider trading date back to the 1960s and
1970s, the period of the development of several fundamental issues in finance. The early
studies on this topic are Lorie and Niederhoffer (1968), Finnerty (1976a and b), The
expansion of financial markets in the 1980s and the subsequent periods in terms of number of
listed companies, their size and importance has been a determinant factor in growing interest
in academic research in the area. After almost five decades, there are still no clear-cut
academic explanations for a number of research questions on insider trading. Part of the
problem relates to mitigating results the research studies on this topic report. For instance,
several studies discussed in this section provide mixed support for the efficient market
hypothesis (e.g., Roddenberry and Bacon, 2011). On the other hand, the ever-increasing
complexity of such transactions due to increasing role of corporate management and
executive board members in capital market economy does not contribute to providing
satisfactory explanations for a number of outstanding questions on insider trading.
The early research of Jaffe (1974) argued that public investors who consistently traded
with the insiders based on announced insider transactions would have enjoyed excess risk-
adjusted returns. This argument was supported by the study of Trivoli (1980) in favor of
combining insider trading information with key financial ratios to increase the investors’
returns. The study of Nunn et al. (1982) went on saying that there are some insiders who are
more ‘inside’ than the others and the investors should consider in their strategy which group
of insiders (board chair, officers, directors versus other insiders) is involved in buying and
selling the companies’ shares. In contrast, Seyhun (1986) stated that the realizable return to
investors who attempt to use insider reports was not positive after considering total
transaction costs. The work of Lee and Solt (1986) supported this argument stating that it is
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not possible to use aggregate insider trading activity as a guide to market trading. This was
later confirmed by the results provided in the studies of Seyhun (1988) and Chowdhury et al.
(1993).
Several research papers examine whether the buying and selling transactions of
corporate insiders convey information for market participants. Seyhun (1988) provides
evidence on the positive correlation between net aggregate insider trading activity and market
portfolio. Similarly, the study of Petit and Venkatesh (1995) showed a significant relationship
between insider trading and longer-term security performance indicting that on average,
insider trades are associated with substantial changes in share valuation. The study of Seyhun
(1988) shows that on an overall basis, “insiders increase their stock purchases prior to
increases in the stock market and decrease their stock purchases following increases in the
stock market” (p. 22). This may provide evidence on the ability of inside traders to predict, at
least partially, the favorable or unfavorable effects of economy-wide activity. However, the
author does not provide clear evidence on the extent to which the outcome of insiders’
transactions depends on their anticipation capacity of economic conditions or the nature and
quality of private information they possess because of influential position they hold in
company. In his following paper, Seyhun (1990) sheds light on the position of insider traders
who did not systematically foresee the market crash of 1987. “As stock prices began to
decline during the week of October 12, 1987, insiders became buyers rather than sellers” (p.
1386). The author believes that the corporate insiders’ attitude is mainly due to overreaction
effect in market pricing. In our opinion, this may also be related to the reluctant position of
corporate insiders at the time of crisis and their defensive strategy to protect their interests.
The issue of overreaction has been examined by Rozeff and Zaman (1998) who
provide evidence on increasing purchasing transactions by corporate insiders as stocks change
from growth to value categories and that they increase their purchases after low stock returns
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and decrease their purchases after high stock returns. The authors state that this strategy of
corporate insiders is in contrast to the position of outside investors who overvalue growth
stocks and undervalue value stocks. Rozeff and Zaman (1998) acknowledge that “corporate
insider, who presumably have superior information, have incentives to take advantage of the
misvaluations, to the legally permissible extent, by buying value stock more heavily and/or
selling growth stocks more heavily (1998, p. 702). Although not explicitly expressed in the
paper of Rozeff and Zaman (1998), we believe that the potential profit arising from private
information the corporate insiders hold will result in a serious detriment to investors and
competitive market conditions.
The concept of contrarian beliefs is one the major topics studied in literature on
corporate insider trading. This concept is based on contrary-opinion rules widely used by
technical analysts. These technical trading rules are based on the premise that the majority of
investors are wrong as the market approaches peaks and troughs. Consequently, the traders
take advantage of the opportunities and engage in the opposition direction when the majority
of investors is either very bullish or very bearish. In line with this proposition, several papers
for example Jiang and Zeman (2009), Piotorski and Roulstone (2005), Gregory et al. (2011)
and Lakonishok and Lee (2001) examined the issue of insider trading from the viewpoints of
contrarian beliefs or superior information. Although different in research design and sample
data, they provide similar conclusion showing that insiders are able to predict the market
returns either on the basis of contrarian beliefs or because they benefit from superior
information on future cash-flows prospects.
Insider trading has been also studied in relation to other topics. For instance, it is
interesting to examine the relationship between information disclosure of the insiders’
transactions on the valuation implications of past and future earnings information. Very recent
study of Veenman (2012) provides evidence on the signaling effect of insider share purchases
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on the future earnings information (similar to Piotroski and Roulstane 2005 and Roulstone
2008) but also has the valuation implications of past earnings signals for rational investors.
The aforementioned comments clearly show the importance of ethical considerations
regarding the insider trading. Indeed, several research studies provide evidence that members
of the board and top management who engage in such operations significantly benefit from
informational advantage and that these operations are mainly driven by superior information.
Examining the corporate fraud cases in the United States and Europe, Soltani (2012) sheds
light on significant insider trading of the chairman and several board members (for example in
Enron and HealthSouth). The study also referred to the cases of market abuse and unethical
behavior of several members of top management before the collapse of several multinational
companies. Several other studies (e.g., McGee 2008 and Show, 1990) emphasized the
importance of ethical principles in insider trading. However, this discussion goes beyond the
scope of the present study.
Regulatory framework
Following high profile financial failures, particular attention has been paid by the regulatory
bodies in developed capital markets to corporate issues, market functioning and quality of
information. One of the critical topics is related to insider trading which concerns both legal
and illegal conduct. The regulatory bodies are mainly concerned with transactions made by
corporate officers, directors, and employees when they buy and sell stock in their own
companies. Since 2002, most regulatory bodies require the mandatory reporting on
transactions made by corporate insiders. The distinction between legal and illegal versions
should be usually based on whether the corporate insiders when buying and selling their own
companies are in breach of a fiduciary duty or other relationship of trust and confidence,
while in possession of material, nonpublic information about the security. However there are a
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number of problems in making such distinction including the difficulties associated with the
conditions under which insider trading violations may occur, the problems regarding the
trading by those who misappropriate such information (e.g., company’s management), and
"tipping" related information. Evidently, the regulatory bodies should treat the detection and
prosecution of insider trading violations as one of their enforcement priorities because of
tremendous effect the breach of a fiduciary duty may have on investor confidence in the
fairness and integrity of the securities markets and corporate disclosure.
In Europe, an initial step was taken in 1989 within the framework of the Directive on
Coordinating Regulations on Insider Trading (EC Directive 89/592). However, the
introduction of a comprehensive review of European Company Law and the EU Action Plan
in 2002 (Report of the High Level-Winter Group 2002) and recommendation 2003/284
emphasized the changes in redefining the term of insider trading and its disclosure policies. In
2003, following the recommendations of the High Level Group, three other initiatives were
put on the agenda by the European Commission. One was the introduction of a special
investigation to be requested by shareholders, another was the development of an EU wide
wrongful trading rule and the third was the imposition of directors' disqualification across the
EU.
The Directive on insider dealing and market manipulation (market abuse) (2003/6/EC)
was among the major initiatives of the Commission. It was aimed at reinforcing market
integrity by addressing the issues of price manipulation and the dissemination of misleading
information. The Commission acknowledges that “insider dealing and market manipulation
prevent full and proper market transparency” (Art. 21). By providing the detailed definitions
of the terms such as ‘insider trading’, ‘market manipulation’, and ‘financial instruments’, the
introduction of this Directive was a major step to reinforce the market quality. However, this
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Directive similar to several others lacks an in-depth analysis of the conditions and disciplinary
policies which may be determinant factors in achieving final outcome. This analysis goes
beyond the scope of this paper but as highlighted by Soltani (2005), the European Directives
and proposed regulations particularly those dealing with financial market functioning and
quality of corporate disclosure policies do not fully respond to the imperatives in this respect.
Moreover, The EC Directives and national laws and regulations can be considered as
minimum requirements and this does not prevent the corporations from going further by
providing additional oversight measures. This point was also raised in the Green paper of the
European Commission (2011).
In the U.S. context, the term of insider trading was introduced in the SEC Act of 1934
directly through Section 16(b) and indirectly through Section 10(b). Section 16(b) defines
‘insiders’ as officers, directors, and large shareholders of more than 10 percent of any equity
class of securities of an issuing company. Before the introduction of SOX Act in 2002, the
information regarding insider trading was publicly available through EDGAR system (SEC’s
Electronic Data Gathering, Analysis and Retrieval). The introduction of SOX Act, particularly
the provisions underlined in section 403, gave new prominence to disclosure requirements
regarding the transactions involving management and principles shareholders. Based on these
requirements all insider trading activities should be publicly available on form 4 through the
EDGAR system within two business days. This short delay compared to five days in major
European market (e.g., France) and the requirement to disclose the information in electronic
formats of XBRL (eXtensible Business Reporting Language) and XML (eXtensible Markup
Language) provides several benefits for the American investors in terms of transparency,
timeliness and lower cost of information-processing.
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Research design
We present in this part the hypotheses formulated in this study, sample selection and research
methodology and results.
Hypotheses
In line with the objectives outlined in the study, we test three following hypotheses
concerning the insider trading behavior measured in terms of increase or decrease of number
of transactions on comparative basis (before and after financial crisis), contrarian strategy and
the favorable (unfavorable) outcome of possible private information they may hold on their
transactions.
Hypothesis 1
The following hypothesis is defined to examine whether the insider traders increase
(decrease) their transactions during the time interval of 2007-2010 taking into account the
price movements. We test the trading behavior of insiders in terms of aggregate number of
transactions before and after crisis to make comparison between average number of
transactions with market movements represented by SBF 120 index.
H1: Do the inside traders, in anticipation of price movements, increase (decrease) their
purchases and sells before and after the periods of crisis.
Hypothesis 2
We investigate the reasons of increasing number of transactions made by insider traders to
determine whether this is due to their contrarian strategy and the selection of undervalued
stocks with high future returns.
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H2: Based on contrarian strategy hypothesis, and considering the insiders as contrarian
investors, is there a negative relation between insiders trading activity and firm market to
book ratio and transaction volume during the periods of crisis.
Hypothesis 3
The corporate insiders have influential position in company and are in charge of financial
reporting and control mechanisms. This provides them with superior information compared to
other economic agents including the current and potential shareholders. It is interesting to
examine whether this may have a favorable effect on the performance of their transactions
compared to companies’ performance measured by ROA and the variation of firms’ during
2008 and 2009. This analysis is based on a cross sectional regression of insider trading
purchases using different proxies of contrarian strategy and superior information.
H3: Considering the influential position of corporate insiders in having better quality of
information, is there a positive relation between insiders trading activity and future firm
performance as measured by ROA variation and firm return variation between 2009 and 2008.
Sample and Data:
The period of study includes 2007 to 2010. This provides the possibility to examine the
insider trading behavior before and after financial crisis. The time series analysis is used to
detect any abnormal behavior in response to the variation of global market performance
during this period. For the second part of our analysis, we focus on time interval of 2008-
2009, considering year 2008 as ex-ante and 2009 as ex-post crisis period.
The sample consists of all companies included in index SBF 250. In the absence of database
regarding the information we intend to use for the purpose of this study, We collect manually
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all the transactions of corporate insiders for sample companies, We eliminate from our sample
all firms that do not have a trading activity (buy or sell) during the period of study. Our final
sample contains 126 firms of SBF 250. The sample size includes 7418 transactions (4140
purchase transactions and 3278 sell transactions). For year 2008, our sample consists of 2181
transactions (1735 purchase transactions and 446 sell transactions).
We have collected our data from the official site of French financial market Authority (AMF)
which is a reliable source for the purpose of this study because the disclosed information on
this website is based on mandatory reporting of corporate insiders. In this study, we examine
only the purchasing and selling transactions undertaken by corporate insiders. We do not
consider the other types of insider transactions such as exercise of options; shares acquired
from compensation plan, private transactions etc. We have collected a number of information
from other sources. For instance the daily market variables including stock opening price,
stock volume, stock market value, stock market to book value, SBF120 price are collected
from DataStream database and ROA stock end year value from Thomson database.
Variable definitions
Insider trading activity:
We use the following measures of insider activity as defined by Seyhun (1990):
NP (Number of Purchase): denotes the number of total insider purchase transactions.
NS (Number of Sell): denotes the number of total insider sell transactions.
SP (Share Purchased): denotes the total number of share purchased by insiders
SS (Share Sold): denotes the total number of share sold by insiders
PRAT (Purchase Ratio to All Insider Transaction): is the number of purchase of firm i during
year t as a fraction of all purchases and sales by insiders.
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SPRAT (Share Purchase Ratio to all insider Transaction): is the number of purchased sell of
firm i during year t as a fraction of all shares purchased and sold by insiders.
This ratio was also used by Piotroski and Roulstone (2005) to proxy insider trading behavior.
Seyhun (1990) argues that these ratios (PRAT and SPRAT) are not sensitive to changes in the
number of firms or trading activity over the time and it do not display heteroscedasticity or
extreme outliers.
Firm performance Measure
The performance measures are usually used in accordance with the objectives of the study.
Accounting variables such as ROA and ROE denote return on efficient utilization of firm’s
assets. It is a good performance indicator. Pandya and Rao (1998) argue that these measures
include depreciation and inventory costs and affect the accurate reporting of earnings. For this
reason, these data should be used in conjunction with financial measures such as return
change.
We measure the future company’s performance by using two accounting and financial
indicators:
ROA: future changes in Return on Assets of firm i= ROAt+1 - ROAt.
ROA is defined as net income (income available to common stockholders) divided by the
book value of total assets.
ROAt+1 is the Return on asset of firm i at year t+1 (2009) and ROAt is the Return on asset of
firm i at year t (2008).
A positive change is a sign of well-performed firm in year t+1 relative to year t.
ROA is the performance indicator most frequently used in previous studies (e.g., Piotroski
and Roulstone (2005) and Pandya and Rao (1998)).
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returni: future changes in firm Return = return t+1 – return t.
lnr 2008: the contemporaneous 12 months market-adjusted return and is calculated as firm is
12 months log return for 2008 less the corresponding 12 months on the value weighted market
index, lnr2009 signifies future 12 months adjusted return measured as firm is 12 months log
return for 2009 less the corresponding 12 months on the value weighted market index.
To measure firm performance, Piotroski and Roulstone (2005) use firm future return.
We analyze change return level to proxy firm future performance because it reflects how
firms perform relative to last year. This measure was also used by Pandya and Rao (1998).
Measurement of contrarian factors
The measurement of contrarian factors should reflect the impact of current beliefs and
sentiment of investor on insider trading. The Book to market ratio and current return are
mainly used in previous studies [(Seyhun (1990), Rozeff and zaman (1998) and Piotroski and
Roulstone (2005)]. For the purpose of our study, we choose two measures:
Market to Book Ratio: denotes the market relative value of a company by comparing the
market value of a firm to its book value. The lower market to book ratio, the better the value
as this suggest a company’s assets are undervalued or that the company’s prospects are good.
Market to Book Ratio = Market price per stock ÷ Book value per stock
Rozeff and Zaman (1998), Piotroski and Roulstone (2005) and Gregory et al (2009) use book
value to market which reflects the market pricing error. However, this measure may also
indicate future performance measure. La Porta et al (1997) show that firms with greater book
value to book tend to have future earnings announcements periods returns. Thus, we add
another variable used in contrarian strategy literature to proxy investor sentiment.
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LN VO i: is the second contrarian strategy measure representing the trading volume for firm i
during year 2008.
Blume et al (1994) use volume information and historical price information to predict future
prices change and show a signaling role of volume in return predictability. Datar et al (1998),
Brennan et al (1998), and Chordia et al (2001) show that stocks with lower trading volume
earn higher expected returns. Baker and Stein (2004) suggest that turnover or liquidity, can
serve as a sentiment index. It is thus conceivable that when investor sentiment becomes high
(low), trading volume is likely to increase (decrease). Baker and Stein (2004) show that the
increase in trading volume reflects a rise in investor sentiment. Lei (2005) investigates the
ability of past volume on predicting stock returns and show that trading volume trend has a
negative and significant relation with expected stock returns,
Other variables
Index return: this represents the SBF 120 return measured by LN (Pt+1/Pt) with Pt+1 is the
SBF120 opening price of day t+1 and Pt is the SBF120 opening price of day t.
Beta i: denotes a measure of past stock return volatility for stock i and represents the market
model slope coefficient. Beta is computed using daily return from January 2006 to December
2007. This measure was used by Seyhun (1990) in his study on insider response to the market
crash of 1987. Seyhun (1990) argued that pre crash risk should be an important predictor on
stock price during and after the crash, thus insider in the higher market risk firms are more
likely to observe and trade on the basis of mispricing caused by economy wide factors.
However, he found no evidence on this issue. Jiang and Zaman (2010) show that firms with
high incertitude for future are more associated with contrarian strategy.
MV i: Firm size i is measured by average Market value during year 2008.
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Lakonishok and Lee (2001), show that insider in small firm are more able to predict future
market return on US market from 1975 to 1995. This result was later confirmed by Piotroski
and Roulstone (2005).
Results of empirical analysis
Time series Analysis of insider behavior and its comparison with market fluctuation:
First, we investigate aggregate insider trading activity during the period of study considering
global market fluctuations. The objective is to determine whether the corporate insiders react
to market performance particularly during the financial crisis.
Summary of descriptive statistics
Table 1 indicates different statistics on monthly insider trading variables (NP, NS, PRAT, and
SPRAT) and monthly market fluctuations (log of market index return of SBF120) during the
period 2007-2010 and for each year (2007, 2008, 2009 and 2010). Table 1 is completed by
table 2 in which we present average comparison tests of insider activity between periods.
[Insert table 1 here]
[Insert table 2 here]
Table 1 shows that for the whole period (2007-2010) the PRAT and SPRAT ratios are slightly
higher than 50%. During this period of study, insiders tend to purchase more shares than what
they sell with a slight difference. The average number of purchase transaction which consist
of 86 (5823793) is higher than the number of sell transactions 68 (2930729). This purchase
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activity corresponds to negative market return during the period. We also investigate this
results based on sub period analysis.
The difference in terms of trading activity is due, to some extent, to the level of trading in
2007 during which we observe a minor difference between buy and sell activity. Insider buy
in average 1152361 shares (100 buy transactions) and sell in average 2800475 shares (79
transactions). According to table 2, this difference is not significant for transaction number
and leads to a PRAT ratio close to 50% but the difference is significant between number of
purchased and sold shares and leads to relatively high SRPAT. The second important factor to
the purchase activity during the whole period is the insider trading activity (volume and
frequency) during 2008. As table 1 indicates, PRAT and SPRAT ratios show a large and
significant increase with a median of 81, 7% and 91, 9% respectively. This intensive buy
activity occurs during the unfavorable market performance period in which global return
market shows in average a negative trend of about -0,045%. According to table 2, the insider
purchase activity during 2008 is significantly higher than purchase activity during all analysis
periods.
Having considered market a sign of market recovery in 2009, we notice a reversal insider
activity as the PRAT and SPRAT ratio decrease to even fewer than 50%. Table 2 shows no
significant difference between sell and buy transactions during 2009. The activity trend was
supported during 2010 in which we observe a positive market return (0,001) and an intensive
selling activity significantly superior than insider buy transaction, as insider purchase in
average 41 shares and sell more than twice and low ratio as PRAT and SPRAT ratio reach in
average 31, 9% and 23, 3% respectively. Consequently, this may provide evidence that insider
purchase activity during the whole period is largely explained by the intensive buy activity in
2008 which has compensated the increase in sell activity especially in 2010.
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Monthly trading insider activity:
Table 3 presents different measures of insider trading activity and global market variations for
every month from January 2007 to December 2010. We try also to report results on figure 1, 2
and 3 indicating insider behavior in time based on market variations.
[Insert table 3 here]
[Insert figure 1 here]
[Insert figure 2 here]
[Insert figure 3 here]
As reported in table 3 and figures (1, 2 and 3), for the first half of 2007, we observe no
significant difference between buy and sell activity. In November 2007, the insider activity
purchase increases and the sell activity decreases matching with first sign of crisis in the
European market. Then insider buy activity shows a pick on January 2008 thus PRAT and
SPRAT ratio reach 92% and 95% respectively. This abnormal purchase activity corresponds
to market crash as we observe the unfavorable market return performance in this month (-0,
12). The relative market recovery decreases insider purchase transactions which still
significantly higher than insider sell activity. The second insider purchase activity pick
occurred in October 2008 (PRAT and SPRAT reach 92% and 93% respectively) which in fact
follow a second crash indicating significant negative return value (-0,155).
Insider purchase activity was at high levels until the first quarter of 2009. Following the
market recovery, the insider activity shows a reversal trend. As we observe, picks of insider
sell activity occur in September 2009 and March 2010 as PRAT and PRAT ratio reach in
average 17,3% and 18,4% respectively for September 2009 and 17% and 12, 9% respectively
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for march 2010 with a favorable market performance (0,039 for September 2009 and 0,067
for march 2010). Selling activity was supported along the year 2010.
These results provide evidence for contrary position of the insider vis-à vis the market. For
this reason, when market performance is high, they increase their sell transactions and when
the market is low they increase their insider trading purchased. This strategy is mainly chosen
during financial crisis period with possible crashes. The results of this part of our analysis are
supported by Seyhun (1990) findings. He investigated insider trading response to market
crash of 1987 and found a higher PRAT and SPRAT ratios (80% and 62% respectively)
during October 1987.
Reasons of insider trading
In this section, we examine the reasons of aggregate insider purchase activity during crisis
period by using cross sectional analysis. The reasons may be either related to contrarian
strategy of corporate insiders, the quality of information they hold about future firm
performance or both.
To examine these questions we construct a model which considers variables reflecting
contrarian strategy and future firm performance.
Summary statistics and variables correlations:
[Insert table 4 here]
Table 4 presents statistic summury (average, median and stdev) of insider trading activity
cross firms (NP, SP, NS, SS PRAT and SPRAT) and different variables (ROA, Beta, VO,
MV, MB and stock return). Our results show an average of 13.77 purchase transactions
(corresponding to 805117 share purchased) relative to 3.54 sell transaction (corresponding to
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144193 share selled) in 2008. This indicates an average PRAT and SPRAT ratio of the order
69% for 2008.
[Insert table 5 here]
Table 4 is completed by the infomation on table 5 in which we present the correlation matrix
between all variables studied. Based on Table 5, SPRAT present a negative significant
correlation with lnvo2008, MB2008, MV 2008 and current return and a positive significant
correlation with variation return and futur return. This correlation shows the same trend for
PRAT with no significant sign for current and futur returns. Results are in line with both
contrarian strategy and private information. Moreover, this indicates that insider activity is
more significant for small firms. We can conclude from the matrix correlation that insider
intensify their purchase activity on shares that are most undervaluated during the crisis period
(negative correlation with MB and return in 2008) and recover first post crisis (positive
correlation with return in 2009).
The results indicated on table 5 show a negative significant relation between MB ratio and the
variation of return. These observations are also made in Rozeff and Zaman (1998) and
Piotroski and Roulstone (2005) showing the ability of insider to detect overreaction and to
trade accordingly.
As shown in table 5, there is a negative relation between past volume traded and futur return.
This finding is supported by the resulst observde in Subrahmanyam and Anshuman (2001)
and Lei (2005) who show that stocks with lower trading volume provide higher expected
return.
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Cross sectional analysis:
We analyze cross sectional insider trading using this regression model to investigate the
reasons of insider purchases:
(Insider activity) i = β 0 + β 1 MB i + β 2 LNVO i + β 3 Return i + β 4 ROA i
+ β 5 Beta i + β 6 i + i
(Insider activity) i : Reflect PRAT and SPRAT ratios which denote the number of purchases
as a fraction of all insider transaction (sell and buy) and the number of share purchased as a
fraction of share purchased and sold repectively, MBi is the Market to Book ratio of firm i
during year 2008, LNVO i is average Turnover volume during year 2008, Return i is the
difference between average return during year 2009 and average return during year 2008,
ROA I is the difference between Return On Asset during year 2009 and Return On Asset
during year 2008 Beta is the market model slope coefficient using daily return from 2006 to
2007 and MVi is the firm market value of firm i in 2008. Regression results are represented
on table 5.
[Insert table 6 here]
Results show a negative significant relation between insider purchase activity and insider
ability to detect pricing error measured by MB ratio. This is in line with Rozeff and Zaman
(1998) findings as they found a high purchase ratio for highest BM portfolio and the lowest
purchase ratio for the lowest BM value. This is also observed by Piotroski and Roulstone
(2005) who show that insider purchase is inversely related to firm’s book to market ranking.
23
Furthermore, results show a negative significant relation between insider trading activity and
Lnvo2008, which reflects investor sentiment. Thus insider trade intensively on stocks trated
less (less liquid) on the market as they expect a market reversion.
Results on contrarian investor strategy are significant as it indicates that insiders can detect
pricing error on their own stocks and they trade accordingly. Moreover they trade against
investor sentiment in the anticipation for a futur reversal market.
Considring the regressionn analysis, our results show a positve non significant relation
between insider trading activity and variation on ROA. Thus insider trade more on stcoks
having good future performance prospects. Moreover, a positive relation between insider
purchase activity and return variation indciates that insider purchase more the stocks with
favorabler futur performance in the market. Howver, this relation is not significant.
The results show also that insider trading is positively correlated to firm risk and negatively
related to firm market value, although these are not significant. This may indicate that insider
invest more in small and risky firms.
Overall conclsuion is that insider purchase activity in crisis period is mainly motivated by
contrarian strategy based on detecting the error pricing rather than using private information.
It seems that insiders are able to detect overreaction and a rise of pessimism sentiment of
uninformed investor in the market which contribute to take away prices from their intrinsec
values and a decrease on traded volume. The fact that they act as contrarian investor, this may
rpovide a signal to the market and leads to a rapide price correction in favor of market
recovery.
24
Contribution and limits:
This study may have several contributions mainly because it is interested in the potentially
informed investor reaction in critical market conditions. During this period it is important to
study the response of specific category of market participants especially informed traders as
their behavior may provide a signal to other market participants. This may also be useful in
correcting the pricing error in market more rapidly. This study has also academic implications
for different reasons. First, most previous studies were conducted in English speaking
countries such as the U.S. and the UK. This research is conducted in the context of French
market which is one of the most important European financial centers. Besides that to our
knowledge there is no study in this area using an extensive database and variables employed
for French market. The study considers several variables related to contrarian investor
hypothesis and private information hypothesis and introduce a measure of investor feeling
(trading volume) as contrarian strategy proxy to reflect irrational investor pessimism during
the crisis period.
The study has several practical implications as it contributes to better understanding of market
participants mainly as it provides better insights into the effect of the informed investor during
the crisis and their contribution to market recovery. This may provide useful information for
the regulatory bodies and the organizations in charge of the market when supervising insider
transaction.
However, our research study is also subject to several limitations. The first is related to
sample size as the number of firm in this study is relatively low to other studies on U.S. This
is due to the difficulty related to data collection. Thus we did not dispose of insider database
and we need to collect transactions from AMF site. Secondly, our paper reflects insider
25
reaction in a critical period thus they may have different behavior in normal period than we
can enlarge our analysis by increasing analysis period to compare their reaction in normal and
critical periods.
Conclusion
The major objective of this study is to understand better about insider trading strategy in
medium-sized market such as France during financial crisis. We investigate the time series
trend change of corporate insider transactions to provide explanations about their behavior
and perceptions towards financial crisis. Results show that insider purchase activity is
negatively correlated to global market variation. Under favorable market conditions, they
increase their sell transactions, and when market performance falls they intensify their
purchase transactions. Seyhun (1990) shows the same insider behavior in US market
regarding the insider response to market crash of 1987.
We have examined a number of questions regarding the strategy of corporate insiders and the
reasons behind their strong intervention during the crisis period. Is it because they detect a
pricing error prorogated by deviation from fundamental value following noise trade? Is it
because they hold private information, view their positions and their proximity to private
information, about future firm performance? We used a model considering the two
assumptions and we use regression concerning insider purchase measures based on contrarian
strategy proxy and using the trading volume in 2008 and market to book ration in 2008. We
also test for private performance information measure proxy calculated by return variation
and the variation on ROA between 2009 and 2008. Results are significant for contrarian
strategy assumption as we find negative significant relation between insider trading ratios and
trading volume and market to book ration. Results on private performance information are
26
positive suggesting that insider trade intensively on stocks that perform well in future but are
not significant.
This supports the idea that corporate insiders have a clear strategy in terms of purchasing,
selling, the timing and conditions under which they make transactions in financial market.
The strategy based on anticipation is not obviously limited to corporate insiders and concerns
all categories of market participants. However, there are several major differences between
the quality and the conditions of insider trading and other market participants. One major
difference is related to the influential position of corporate insiders and informational
advantage they have compared to others. Another difference may be related to their
knowledge and expertise of market conditions and environmental factors. Is this added value
considered ‘private information’? Does this outstanding position affect their incentives to
intervene in market in specific period or time interval? Do they behave ethically and if not, to
what extent they are responsible for using private information to detriment of others. This
paper does not claim to provide answers to these questions. However, we have tried to shed
light on strategy of corporate insiders in relation to market conditions, the position of other
investors and regulatory framework.
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31
Table 1: Statistics summary of trading activity
NP is insider purchase number, NS is insider sell number, SP is number of shares purchased, SS is number of shares
sold, PRAT is number of purchases as a fraction of all insider transaction (sell and buy) and SPRAT is number of share
purchased as a fraction of share purchased and sold.
DATE LNRM NP SP NS SS PRAT SPRAT
Sum 2007-2010 - 4140 3278 279542078 140674971 - -
average 2007-2010 -0,0069 86 68 5823793 2930729 0,53085 0,57807
median 2007-2010 -0,0060 73 67 2367954 1248040 0,48429 0,67461
stdev 2007-2010 0,0641 57 40 9232702 6367672 0,24030 0,33564
sum 2007 - 1198 947 133828335 33605695 - -
Average 2007 -0,0002 100 79 11152361 2800475 0,55848 0,70468
Median 2007 0,0021 96 64 7580370 1776463 0,52820 0,78074
stdev2007 0,0342 39 38 13710029 3784584 0,16076 0,22665
sum 2008 - 1735 446 101444722 18168377 - -
Average 2008 -0,0458 145 37 8453727 1514031 0,78092 0,80008
Median 2008 -0,0273 146 37 6488898 844115 0,81766 0,91982
stdev2008 0,0700 56 20 8890843 1639817 0,13381 0,24399
Sum 2009 - 715 804 36858205 10106768 - -
Average 2009 0,0174 60 67 3071517 842231 0,46440 0,57378
Median 2009 0,0429 37 70 1381215 751660 0,36835 0,68831
stdev2009 0,0752 43 42 4490619 640371 0,25635 0,36044
Sum 2010 - 492 1081 7410817 78794130 - -
Average 2010 0,0010 41 90 617568 6566178 0,31962 0,23373
Median 2010 -0,0100 38 77 371381 1604999 0,30196 0,17540
stdev2010 0,0586 18 38 829960 11594863 0,12131 0,19974
32
Table 2: Insider activity comparison between periods
NP is insider purchase number, NS is insider sell number, SP is number of shares purchased, SS is number of shares
sold, PRAT is number of purchases as a fraction of all insider transaction (sell and buy) and SPRAT is number of share
purchased as a fraction of share purchased and sold. This table presents the difference between average insider
purchases and sells activity in the same year and between different years of study.
NP2008 t-stat SP2008 t-stat SP2007 t-stat SP2009 t-stat SP2010 t-stat
SP2008 107* 5,7
SP2007 66* 3,05 -42* -4,14
SP2009 77* 3,8 -30* -2,68 12 0,66
SP2010 54* 2,85 -53* -4,7 -11 -0,63 -23 -1,26
NP2007 45* 2,074 -63* -4,82 -21 -1,11 -33* -2,2 -10 -1,26
NP2009 85* 4,87 -23* -1,57 19 1,55 7 0,34 30* 2,04
NP2010 103* 5,1 -4 -0,77 38* 3,82 26* 2,1 49* 3,9
NS 2008 t-stat SS 2008 t-stat SS 2007 t-stat SS2009 t-stat SS2010 t-stat
SS2008 7E+06* 2,59
SS2007 6E+06* 2,068 -1,00E+06 -1,04
SS2009 8E+06* 2,84 7,00E+05 1,5 2,00E+06 1,7
SS2010 2,00E+06 0,41 -5,00E+06 -1,44 -4,00E+06 -0,98 -6,00E+06 -1,7
NS2007 -3,00E+06 -0,58 -1E+07* -2,35 -8E+06* -2,1 -1E+07* -2,6
-
5,00E+06 -1,04
NS2009 5E+06* 2,87 -2,00E+06 -1,3 -3,00E+05 -0,15 -2,00E+06 -1,61 3,00E+06 0,9
NS2010 8E+06* 2,96 9,00E+05 1,73 2,00E+06 1,9 2,00E+05 1,31 6,00E+06 1,7
PRAT 2008 t-stat PRAT 2007 t-stat PRAT 2009 t-stat
PRAT 2007 0,23* 4,41
PRAT 2009 0,32* 3,91 0,09 0,87
PRAT 2010 0,47* 7,41 0,24* 3,77 0,18 1,59
SPRAT 2008 t-stat SPRAT 2007 t-stat SPRAT 2009 t-stat
SPRAT 2007 0,1 1,2
SPRAT 2009 0,23 1,78 0,13 0,88
SPRAT 2010 0,57* 5,9 0,47 0,23 0,31* 2,63
*significant at 5% level
33
Table 3: Insider trading activity in 128 firms from 01/01/2007 to 31/12/2010
NP is insider purchase number, NS is insider sell number, SP is number of shares purchased, SS is number of shares
sold, PRAT is number of purchases as a fraction of all insider transaction (sell and buy) and SPRAT is number of share
purchased as a fraction of share purchased and sold and LNRM is log return of market (SBF120).
DATE LNRM NP NS SP SS PRAT SPRAT
january-07 0,017876 69 83 8955112 1933500 0,4539 0,8224
february-07 -0,02728 63 115 2580082 3743071 0,3539 0,4080
march-07 0,025991 97 68 1637226 1619426 0,5879 0,5027
april-07 0,056474 71 97 1307221 1368085 0,4226 0,4886
may-07 0,020987 99 139 18749400 2266267 0,4160 0,8922
june-07 -0,01821 108 148 12261140 3512941 0,4219 0,7773
july-07 -0,06628 94 49 19062240 14306572 0,6573 0,5713
august-07 0,00859 146 35 10433738 834988 0,8066 0,9259
september-07 -0,00446 74 59 1271263 2348332 0,5564 0,3512
october-07 0,032298 60 60 1855704 510701 0,5000 0,7842
november-07 -0,03885 192 34 6205628 335707 0,8496 0,9487
december-07 -0,00994 125 60 49509581 826104 0,6757 0,9836
january-08 -0,12827 249 20 32518771 1657219 0,9257 0,9515
february-08 -0,03609 125 19 17788282 366215 0,8681 0,9798
march-08 -0,00752 173 39 9496182 879814 0,8160 0,9152
april-08 0,074862 61 52 729512 5557232 0,5398 0,1160
may-08 -0,00776 79 69 3234921 1260871 0,5338 0,7195
june-08 -0,12803 156 48 6930685 2858819 0,7647 0,7080
july-08 -0,01859 136 30 7015420 564160 0,8193 0,9256
august-08 0,026801 90 10 2918132 93041 0,9000 0,9691
september-08 -0,09205 167 69 6047111 3383120 0,7076 0,6412
october-08 -0,15583 222 17 2323697 161067 0,9289 0,9352
november-08 -0,07331 169 34 2553503 578403 0,8325 0,8153
december-08 -0,00432 108 39 9888506 808417 0,7347 0,9244
january-09 -0,09342 97 18 14966406 74475 0,8435 0,9950
febrary-09 -0,10594 134 37 3937402 168646 0,7836 0,9589
march-09 0,057065 140 20 2536175 107567 0,8750 0,9593
april-09 0,133189 37 20 8885229 1256550 0,6491 0,8761
may-09 0,046428 48 71 145715 2199430 0,4034 0,0621
june-09 -0,04977 82 93 2412210 802289 0,4686 0,7504
july-09 0,080609 32 64 1588022 406864 0,3333 0,7960
august-09 0,069886 23 82 237931 987440 0,2190 0,1942
september-09 0,039367 36 171 343840 1517382 0,1739 0,1847
october-09 -0,05511 29 69 1174408 701030 0,2959 0,6262
november-09 0,027965 30 81 170463 621492 0,2703 0,2152
december-09 0,059029 27 78 460403 1263603 0,2571 0,2671
january-10 -0,05284 22 82 206250 1033932 0,2115 0,1663
februay-10 0,007539 25 48 335744 529760 0,3425 0,3879
march-10 0,06771 36 175 296718 1989687 0,1706 0,1298
april-10 -0,04383 49 130 529962 1826544 0,2737 0,2249
may-10 -0,08327 85 66 3171408 1239530 0,5629 0,7190
june-10 -0,02751 54 69 755385 1383455 0,4390 0,3532
july-10 0,080077 43 60 200618 886815 0,4175 0,1845
august-10 -0,04414 55 75 407018 681694 0,4231 0,3739
september-10 0,061721 40 92 448573 4028744 0,3030 0,1002
october-10 0,038551 17 67 74966 36864565 0,2024 0,0020
november-10 -0,05538 32 138 720345 4006581 0,1882 0,1524
december-10 0,063017 34 79 263831 24322823 0,3009 0,0107
34
Figure 1: Daily insider trading number of buy and sell and return market stock in 128 firms from 01/01/2007 to
31/12/2010
NP is insider purchase number, NS is insider sell number and LNRM is the log of SBF120 market return
35
Figure 2: Daily insider trading number of share purchased and sold and return market stock in 128 firms from
01/01/2007 to 31/12/2010
SP is number of shares purchased, SS is number of shares sold and LNRM is the log of SBF120 market return
36
Figure 3: Daily insider trading activity (ratio) and return market stock 128 firms from 01/01/2007 to 31/12/2010
PRAT is number of purchases as a fraction of all insider transaction (sell and buy) and SPRAT is number of share
purchased as a fraction of share purchased and sold and LNRM is the log of SBF120 market return
37
Table 4: Statistics summary of Cross sectional study
NP is insider purchase number, NS is insider sell number, SP is number of shares purchased, SS is number of shares
sold, PRAT is number of purchases as a fraction of all insider transaction (sell and buy) and SPRAT is number of share
purchased as a fraction of share purchased and sold, ROA 2008 is Return On Asset of 2008, ROA 2009 is Return On
Asset of 2009, ROA is the difference between return ROA 2009 and ROA 2008, BETA is the market model slope
coefficient using daily return from 2006 to 2007, Lnvo 2008 is the log of 2008 volume, MV is the firm Market Value,
lnr2008 is the contemporaneous 12 months market-adjusted return and is calculated as firm is 12 months log return for
2008 less the corresponding 12 months on the value weighted market index, lnr2009 is future 12 months adjusted return
measured as firm is 12 months log return for 2009 less the corresponding 12 months on the value weighted market index
and Return is the difference between lnr2009 and lnr2008 and MB 2008 is the Market to Book ratio in 2008. For each
of these variables we present statistics (average, median and standard deviation)
Average
median stdev
NP 13,77 4 23,80
SP 3,54 1 5,95
NS 805116,84 17478,696 3662387,35
SS 144193,47 1310,006 546006,79
PRAT 0,69 0,828 0,36
SPRAT 0,69 0,950 0,40
ROA 2008 2,78 3,790 7,32
ROA 2009 1,69 3,040 10,44
ROA -1,09 -0,075 7,92
BETA 0,12 0,101 0,31
lnvo2008 4,32 4,456 2,87
lnr2008 -0,00072 -0,00035 0,00189
m2b2008 1,81 1,540 1,61
mv2008 7380,00 1078,558 15863,53
Lnr 2009 0,00077 0,00057 0,001527
Return 0,00149 0,00088 0,0031
38
Table 5: Sample Cross Sectional correlations
PRAT is number of purchases as a fraction of all insider transaction (sell and buy) and SPRAT is number of share
purchased as a fraction of share purchased and sold, BETA is the market model slope coefficient using daily return from
2006 to 2007, Ln vo 2008 is the log of 2008 volume, MV is the firm Market Value, lnr2008 is the contemporaneous 12
months market-adjusted return and is calculated as firm is 12 months log return for 2008 less the corresponding 12
months on the value weighted market index and Return is the difference between lnr2009 and lnr2008 and MB 2008 is
the Market to Book ratio in 2008.
PRAT SPRAT ROA BETA LNVO MB REND lnr2009 lnr2008
PRAT 1
SPRAT 0.919** 1
ROA 0.087 0.079 1
BETA 0.148 0.147 0.086 1
lnvo -0.345** -0.354** -0.051 -0.069 1
MB -0.354** -0.347** 0.33** -0.079 0.104 1
Return 0.178* 0.243** -0.014 0.27** -0.166 -0.240** 1
lnr2009 0.172 0.225* 0.013 0.219* -0.150 -0.200* 0.907** 1
lnr2008 -0.159 -0.225* 0.034 -0.275** 0.157 0.240** -0.940** -0.71** 1
126 126 126 126 126 126 126 126
** Correlation is significant at 0.01 levels (bilateral) and * Correlation is significant at 0.05 levels (bilateral)
39
Table 6: Insider trading reasons: regression analysis
(Insider activity) i = β 0 + β 1 MB i + β 2 Volume i + β 3 Return i + β 4 ROA i + β 5 Beta i + β 6 i + i
Insider activity i is the insider trading activity for firm I during 2008 represented by PRAT and SPRAT, PRAT is number
of purchases as a fraction of all insider transaction (sell and buy) and SPRAT is number of share purchased as a fraction
of share purchased and sold, MB is the Market to Book ratio for firm i in 2008, Lnvo 2008 is the log of 2008 volume,
Return is the difference between lnr2009 and lnr2008 ROA is the difference between return ROA 2009 and ROA
2008, BETA is the market model slope coefficient using daily return from 2006 to 2007, MV is the log of firm Market
Value in 2008, observation nb indicates the number of observation per regression and R2 is R-squared for the regression.
Values in parenthesis indicate t-stat.
Insider trading activity
PRAT SPRAT
β 0
MB
Ln VO
Return
ROA
Beta
MV
Observation nb
R2
0,94* 0,95*
(14,0) (12,97)
-0,07* -0,077*
(-3,54) (-3,32)
-0,030* -0,033*
(-2,47) (-2,43)
2,07 11,09
(0,21) (1,09)
0,00008 0,00033
(0,02) (0,08)
0,086 0,07
(0,89) (0,64)
-2,461e-06 -2,95e-06
(-1,06) (-1,15)
126 126
0.24 0,25
*significant at 5% level
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