Managerial Overconfidence and Share Repurchase
Pei-Gi Shu
Department of Business Administration,
Fu Jen Catholic University
Yin-Hua Yeh
Department of Finance and International Buiness,
Fu Jen Catholic University
Yu-Hui Su
Correspongind author
Department of Accounting,
Soochow University
Tsui-Lin Chiang
Graduate Institute of Business Administration,
Fu Jen Catholic University
Managerial Overconfidence and Share Repurchase
Abstract
We use the keywords in press portrayals to gauge the level of managerial
overconfidence. We argue the higher the level of managerial overconfidence, the more
likely managers feel their firms’ value is undervalued, and the higher intensity of share
repurchase programs being launched. Our empirical results using a data of 2,744
share-repurchase programs launched by 783 listed firms in Taiwan verify the positive
relation between managieral overconfidence and the program intensity manifested in
scale, execution, frequency, and price difference. The relation is sustainable after
controlling alternative motives and endogeneity issue. However, the market lends little
lenity to the share repurchase programs launched by overconfident managers. This is
due to the fact that firms with a high level of managerial overconfidence tend to be
firms that are not undervalued.
Keywords: Managerial Overconfidence, Share Repurchase
1
2
1. Introduction
Overconfidence is a prominent stylized fact from the social psychology literature
indicating that individuals tend to overstate their acumen relative to the average
(Larwood and Whittaker, 1977; Svenson, 1981; Alicke et al., 1985). This inclination is
further reinforced by the self-serving bias that portrays individuals’ custom of
attributing good outcomes to their actions and bad outcomes to luck (Miller and Ross,
1975). The notion of overconfidence in affecting managerial actions was first brought
by Roll (1986) who proposes the “hubris hypothesis” arguing that managers are
overconfident so as to overbid acquired targets. Heaton (2002) further elaborates the
effect of overconfidence in affecting managerial actions. Empirically, the impact of
managerial overconfidence has been examined in different corporate scenarios. For
example, Malmediar and Tate (2005b) illustrate overconfidence heightens the
sensitivity of corporate investment to cash flow and that is more pronounced to be
found among equity-dependent firms1. Ben-David et al. (2007) indicate that managerial
overconfidence results in more investments, a more sensitive investment-cash relation, a
lower cash dividend payout, and a higher long-term leverage.
1
Overconfident CEOs systematically overestimate the value of their investment projects and the current
value of the firm. If they have sufficient internal funds for investment and are not disciplined by the
capital market or corporate governance mechanisms, they overinvest relative to the first–best. If they do
not have sufficient internal funds, however, they are reluctant to issue new equity because they perceive
the stock of their company to be undervalued by the market. As a result, they curb their investment. This
would result in a tightened cash-investment relation.
3
In this study we investigate how managerial overconfidence is related to share
repurchase program. Share repurchase has only been popularly used by the U.S. firms
within the last two decades and was further fueled by an explosion in the use of open
market repurchase programs. In the 1990s, this movement went global as countries like
Canada and the U.K. also saw an increase in repurchase activity. Some countries such
as Germany, Taiwan, Hong Kong, and Japan, that formerly prohibited stock repurchases
adopted provisions allowing resident firms to repurchase equity in the open market for
the first time.
The magnitude of share repurchase programs was magnificent. The size
of announced intentions to repurchase in the U.S. market in 1995-1999 was roughly
$750 billion worth of stock. Moreover, in 1998 its size exceeded cash dividend for the
first time (Grullon and Michaely, 2002).
The rationale of relating the two constructs is intuitive in the sense that
overconfident managers tend to perceive their firms are undervalued and therefore to
launch a share repurchase program aiming to fixing the price discrepancy. The higher
the overconfidence level the larger the perceived price discrepancy to be fixed and a
higher intensity of the repurchase program. The intensity of share repurchase program
in this study is manifested in scale, execution rate, frequency, and price difference. We
expect to find a positive relation between degree of managerial overconfidence and
4
intensity of share repurchase program.
Our empirical results using 2,744 repurchase
programs launched by 783 listed firms in Taiwan basically support this postulation. The
positive relation between managerial overconfidence and the intensity of share
repurchase program is sustainable after controlling other discerning variables2 and the
possible endogeneity issue.
We further explore how market responds and to the share repurchase programs
launched by overconfident managers. We explore whether firms with overconfident
managers are undervalued so as to enhance the intensity of share repurchase programs.
The result shows that these overconfident share-repurchase launchers are less likely to
be undervalued. The result comes no surprise that the market responds negatively to
managerial overconfidence. Investors in the first beginning appreciate large-scale share
repurchase programs because the signal of undervaluation is reinforced. However, as
the passage of time up to the maturity of a share repurchase program, outside investors
realize that the intensified signal is affected by managerial overconfidence and therefore
attach lower valuation.
The potential contributions of this study are multifold. First, the relation between
2
The motives that firms engage in repurchasing shares are extenstively dicussed in literature. The first
one is related to agency concern arguing that repurchasing share is to distribute excess cash flow (Jensen,
1986). This arugment is supported by the finding of a positive relation between repurchases and levels of
cash flow (Stephens and Weisbach, 1998). The second one is related to signaling undervaluation
(Vermaelen, 1981). The third one is related to leverage adjustment arguing that repurchasing stock could
be used to increase firm’s leverage ratio (Bagwell and Shoven, 1988; Opler and Titman, 1996). The
fourth is related to fend off unwanted takeover attempts (Bagwell, 1991).
5
managerial overconfidence and share repurchase program has been sparsely explored in
the literature. If any, the prior studies informally indicate the two are positively
correlated without providing further empirical evidence. For example, Ben-David et al.
(2007) using top financial executives’ estimation of the stock market prospect as a
proxy of managerial overconfidence propose that overconfident firms are less likely to
pay dividends and more likely to repurchase shares. Our finding supports this
postulation. Taking a further step, we explore the relation between extent of managerial
overconfidence and intensity of share repurchase program. The exploration provides
readers a better understanding on how managerial inclination affects corporate policies.
Second, we advance the press-based measurement of overconfidence proposed by
Malmendiar and Tate (2005, 2008) and Brown and Sarma (2007).
Specifically, our
measure of managerial overconfidence tags along after the incumbent manager rather
than the firms that launch share repurchase programs.
Third, we find market responds negatively toward the programs launched by
overconfident managers. As the passage of time outside investors are able to discern the
overconfidence-induced intensified share repurchase programs and attach lower
valuation. Finally, we find that repeated share-repurchase launchers and/or
high-execution launchers are associated with lower market appraisal. The rest of this
6
paper is organized as follow. Section 2 reviews the related literature. Section 3 outlines
the data, variables, and empirical models. Section 4 reports the empirical results.
Section 5 discusses the robustness of the empirical results. Section 6 concludes.
2. Literature and Hypotheses
In this section we firstly brief share repurchase program in Taiwan, followed by the
literature review of share repurchase and overconfidence. Based on the literature, we
develop hypotheses to explore the relations between managerial overconfidence and
share repurchase program as well as investors reaction to open market share
repurchases.
2.1 Share Repurchase Programs in Taiwan
Comparing to other countries, Taiwan imposes stricter rules on repurchases
disclosure and a short execution period of two months.
The Article 28-2 of the
Securities and Exchange Law was initially approved by the Legislative Yuan of Taiwan
on June 30, 2000 and the Regulations Governing Share Repurchase by Exchange-Listed
and OTC-Listed Companies applied to all listed firms on August 7, 2000. According to
the rules, firms preparing to launch a repurchase program need to file their purposes that
7
are in accordance with at least one of the followings: (1) to prepare for employees’
bonus shares; (2) as reserves for the execution of derivatives such as warrants and
convertibles; and (3) to protect shareholders’ rights with the repurchased shares to be
written off against owners’ equity. The share repurchase announcement should be
made to public in 2 days after board approval. In the meanwhile, the repurchasing firms
should disclose the price range of the repurchase program. The ceiling price of the range
is set at 150% of the higher of the thirty-day average price and the ten-day average price
prior to the date of board approval. The floor price is set at the 70% of the close price at
the date of board approval. In general, open market repurchases will start 2-3 days after
public announcement, which is 4-5 days after board approval. The program should be
finalized in 2 months and reported to the Financial Supervisory Commission the exact
execution in 5 days after program expiration.
Another board approval is needed when
firms expect to extend their unexercised program.
The ceiling of a repurchase program
is confined to 10% of total issued shares and to the summation of retained earnings and
capital surplus.
The number of firms engaging in share repurchase programs was fast accumulated
to 783 listed firms and 2,744 programs in December 2008.
Quite a number of them
were repeated players, being recorded of more than 15 times in our sampling period.
8
Share repurchase is pervasively recognized a tool for saving the undervalued shares. It
is therefore welcome by the listed companies as well as the government endeavoring to
uphold the market.
A recent noted example is the share repurchase programs launch
by Asustek and Pegatron; the two firms had just split and on June 24, 2010. Asustek
launched a share repurchase program buying 10 million shares aiming to counterbalance
the negative news such as CEO changeover, auditor changeover, and losses in exchange.
Pegatron also claimed a share repurchase program of NT3.075 trillion buying back 75
million shares which is equivalent to 3.28% issued shares. The two programs haven’t
shown much of a pronounced impact in price rebound, however.
2.2. Motives of Share Repurchase
Prior studies propose several hypotheses to explain why firms would engage in
share repurchase programs. The first one is the excess capital hypothesis arguing that
firms having excess cash can distribute it to shareholders through repurchasing shares
(Easterbrook 1984; and Jensen 1986). Compared to dividend payout, repurchasing stock
is associated with the flexibility in distribution and tax advantage and is therefore
preferred to dividend payout3. We expect firms with high levels of excess cash or cash
flow to repurchase stock. The first two corresponding variables are free cash flow and
3
Brennan and Thakor (1990) and Lucas and McDonald (1996) present models in which repurchases are
preferred to dividends for larger distributions.
9
firm’s cash level.
The second hypothesis is the undervaluation hypothesis indicating that outsiders
undervalue the firm’s share due to information asymmetry. According to this hypothesis,
the market interprets share repurchase as an indication that the stock is undervalued (e.g.
Asquith and Mullins, 1986; Comment and Jarrell, 1991; Dann et al., 1991; Hertzel and
Jain, 1991; Lee et al., 1992). Ikenberry et al. (1995) imply that low market-to-book
firms are more likely to be undervalued and therefore followed by a significant positive
abnormal return up to 4 years subsequent to the repurchase announcement.
The
corresponding variable is book-to-market equity which is assumed to be positively
correlated firm’s launching share repurchase program.
The third hypothesis is the optimal leverage hypothesis indicating that firms might
use share repurchase to achieve the optimal capital structure when the current debt ratio
is below the target one (Bagwell and Shoven 1989; and Opler and Titman 1996). In this
paper we use debt deviation being calculated as the difference between current debt
ratio and target debt ratio of Hovakimain et al. (2004) as the corresponding variable for
this hypothesis.
The fourth hypothesis is management incentive hypothesis indicating managers
when holding more stock options are of particular interest in preserving price level
10
which could be attained via shares repurchases. Moreover, using treasury stocks
provided for exercised options would not dilute the per-share value of the firm (Dunsby
1994; Jolls 1996; and Fenn and Liang 1997). A firm that compensates its executives
with a large number of stock options may find it beneficial to repurchase stock. The
corresponding variable to this hypothesis is executive stock options.
The fifth hypothesis is the takeover deterrence hypothesis arguing that a repurchase
can be used as a takeover defense because a repurchase can increase the lowest price for
which the stock is available (Bagwell 1991). Thus, firms that are at a higher risk of
becoming takeover targets are more likely to repurchase stock. The corresponding
variable to this hypothesis is the takeover dummy.
All the aforementioned variables
are included in the models in examining the relation between managerial
overconfidence and share repurchase programs.
2.3. Managerial Overconfidence
Overconfidence relates to several streams of psychology literature. The first one is
the “better than average” effect which illustrates the tendency of individuals to think
themselves “above average” on positive characteristics (e.g. Kruger, 1999; Alicke et al.,
1995; Alicke et al., 1985; Svenson, 1981). The tendency has been extensively examined
and empirically supported (e.g. Svenson, 1981; Cooper et al., 1988). The “better than
11
average” effect is further reinforced by attribution bias which indicates that individuals
have a self-serving inclination as to attribute good outcomes to their actions and bad
outcomes to luck (Miller and Ross, 1975; Feather and Simon, 1971).
Overconfidence is particularly applied to top managers for several reasons. First,
skilled individuals who are in lack of an obvious comparison group tend to be
overconfident (Kruger, 1999; Camerer and Lovallo, 1999). Second, overconfidence is
more pronouncedly found when outcomes are abstractly defined (Moore and Kim, 2003;
Nisbett and Ross, 1980). Third, individuals are the most optimistic about outcomes in
which they believe are under their control (Langer, 1975) or to which they are highly
committed (Weinstein, 1980). These attributes perfectly fit for top managers so that
they persistently overestimate their own skills and are therefore too optimistic about the
outcomes of their decisions.
The overconfidence argument relating to managers is parallel to the “hubris”
hypothesis proposed by Roll (1986). It also relates to the frameworks of Heaton (2002)
and Landier and Thesmar (2004), who model managers who overestimate the
probability of project success. In corporate finance, this form of overconfidence has
been applied to different forums: contracting with managers (Gervais et al., 2003),
succession tournaments (Goel and Thakor, 2000), dividend policy (Deshmukh et al.,
12
2010), mergers (Malmendier and Tate, 2008), investment-cash sensitivity (Malmendier
and Tate, 2005).
The biggest challenge for empirical studies is to construct a plausible measure of
overconfidence. Malmendiar and Tate (2005) use CEOs’ personal portfolio transactions
to signal their beliefs about firm’s future performance. This approach is dubbed as
“revealed beliefs” approach which requires detailed information about CEOs’ personal
portfolio transactions in their companies’ stock and options.
Since CEOs’ human
capital is invested in their company, they should diversify their portfolios even for
modest risk aversion. CEOs against the rule of diversification such as holding more of
company’s stocks, reluctance to exercise deep-in-the-money options, or withholding the
exercise of options to the final year of duration, are deemed as overconfident.
Alternatively, they propose the press-based overconfidence measure which
captures how outsiders perceive the CEO. In this study we adopt this press-based
measure by tabulating the positive words against natural and negative words according
to the definition of Malmendiar and Tate (2008). Our measures are time varying and
tagging along after managers so that they are able to capture the notion of acquired
managerial overconfidence.
13
2.4. Managerial Overconfidence and Share Repurchase
The relation between managerial overconfidence and share repurchase is elaborated
as follows. Overconfident managers tend to overestimate firm’s future cash flow or
underestimate the volatility associated with the cash flow. As a result, they tend to
believe that the market misprices the value of the firm and the value of equity. Share
repurchase programs are therefore launched for the purpose of fixing the price
discrepancy gauged by overconfident managers. An extension of this argument is that
overconfident managers who believe the undervaluation premise tend to overinvest in
projects, such as value-detrimental mergers (Malmendiar and Tate, 2008), to prefer
internal sources of financing (Malmendiar and Tate, 2005), and to be less likely to pay
dividends (Deshmukh et al., 2010).
In this study we take an up-close look on how the level of overconfidence affects the
intensity of share repurchase programs. The level of managerial overconfidence is
gauged by the relative counts of the positive words of overconfidence to the words of
natural and passive words. In this sense, managerial overconfidence is a continuous
variable being able to contrast the degree of overconfidence specific to a certain
manager.
The intensity of share repurchase program in this study is ramified into scale
(percentage of shares repurchase and percentage of dollar amount repurchase),
14
execution, frequency, and price difference 4 .
The higher the level of managerial
overconfidence the larger the anticipated price discrepancy to be fixed, the much
intensified programs to be launched.
We therefore assume that the both are positively
correlated.
Hypothesis 1: The level of managerial overconfidence is positively correlated with the
intensity of share repurchase programs.
A noteworthy issue for further investigations is how investors’ response to the
share repurchases programs launched by overconfident managers.
Deshmukh et al.
(2010) find that the magnitude of the positive market reaction to a dividend-increase
announcement is lower for firms managed by overconfident CEOs. This implies that
investors are with reserve toward the signal that is jointly affected by the content of the
signal and managerial overconfidence. The positive effect of share repurchase would at
least be partially offset by managerial overconfidence. The extreme case is that
4
The price difference could be alternatively defined as the difference between the close price on the day
of board approval and the mid-price of announced price range. Unfortunately, the price range is preset in
the range between the cap of 150% of the reference price (higher of 10-day and 30-day average prior to
the announcement day) and the floor of 70% of the close price of the announcement day. The price
difference is therefore less meaningful to be further explored. In this study, we alternatively define the
price difference as the difference between the mid-price of the price range and the 3-day average price
after the execution of a share repurchase program. The price difference is used to signify program
intensity on one hand, and to capture market response on the other.
15
managerial overconfidence dominates the positive effect of share repurchase program
when investors find the firms launching share repurchase programs are firms that are
less likely to be undervalued.
That is, managers acquire overconfidence through their
successful experiences. They learn to be overconfident. Overconfidence in turn makes
them feel that the current price level is undervalued so as to launch share repurchase
programs aiming to fix the price discrepancy. However, this does not concur with
outside investors’ perception. The share repurchase program therefore is expected to
end up with a negative price effect.
Hypothesis 2: The market responds negatively toward the share repurchase programs
launched by overconfident managers. .
3. Data and Variables
Our data of share repurchases are collected from Taiwan Economic Journal (TEJ)
in the sampling period from August 2000 through December 2008. Share repurchase
program was firstly allowed for listed companies in August 2000. After excluding
financial firms which are subject to different regulations, the final sample consists of
16
2,744 share-repurchase programs launched by 783 listed firms.
Table 1 summarizes
the sample distribution based on industry breakdown (panel A), frequency (panel B),
and yearly breakdown (panel C). The results show that electronic appliance firms (379,
13.81%) comprise the most cases of the sample, followed by computer and peripheral
firms (354, 12.9%) and semiconductor firms (322, 11.73%). Around 30% of the firms
(233) only launch one share repurchase program in the sampling period. However, the
statistics also shows that 146 firms (19%) are frequent players that launch more than 5
share-repurchase programs in this period. The very extreme case is 36 programs being
announced in 8 years in the sampling period. The pervasive and repeated use of share
repurchase could be something beyond signaling undervaluation because the market is
less likely to undervalue shares at all time and across all firms. The industry breakdown
in panel A illustrates that share repurchase program is more applicable to high-tech
firms than firms in traditional manufacturing industry. For example, there are only 2
repurchase programs in the glass and ceramic industry.
<<Insert Table 1 Here>>
17
Referring to Malmendier and Tate (2005) and Brown and Sarma (2007), we use
the press portrayals to gauge managerial overconfidence.
The source of data is
collected from the “News Clip” file of Taiwan Economic Journal (TEJ) in the period
from January 1996 and October 2009. This file having not been available until January
1996 is a complied version of all press reports specific to each company. The measure is
associated with an advantage that it could capture the perception of outsiders so that any
strategic move made by the manager would be reflected in the market price which
mingles with the action itself and the manager’s behavioral inclination. Specifically, the
press-based managerial overconfidence (MOC) is defined as follows5.
MOC： a/(a+b) subject to managerial changeover
(1)
where (a) refers to the counts of the word “confident”and the word “optimistic”, and (b)
is the counts of words “not confident”, “not optimistic”, “reliable”, “cautious”,
“practical”, “frugal” and “steady”. We note that the measures are accumulated up to
the yearend prior to share repurchase announcement so that the overconfidence measure
for each manager are different through the passage of time. This might ameliorate the
concern of possible autocorrelation for overconfidence measures. Moreover, the
5
We also alternatively define managerial overconfidence as a/b, a/(a+b), a/b subject to managerial
changeover, a dummy that is assigned 1 when a>b and 0 otherwise, and a dummy that is subject to
managerial changeover and is assigned 1 when a>(a+b) and 0 otherwise. The results from alternative
definitions are qualitatively similar and are not reported for brevity,
18
measure is tagged along managerial changeover, meaning that the count of keywords
would start over when there is a managerial changeover.
The results in table 2 indicate that the average degree of overconfidence is 0.46.
The average number of share repurchase programs is 3.74. The average percentage of
repurchased shares is 2.03% with respect to total outstanding shares and 1.63% with
respect to total equity value. On average, the announced programs were executed 70%
of what they have been announced. The median execution rate is 85%.
We define the price difference as difference between the mid-price of announced
price range (MP) and the average price three days after the program (P+3) divided by the
average price three days after the program.
Price-Difference= ( (MP-P+3)/P+3)
(2)
This measure is to gauge the price decline after share repurchase programs. If share
repurchase programs were motived by managerial overconfidence, we would expect to
find the number is positive and is positively correlated with the level of managerial
overconfidence. The average price difference is 17.8%.
19
The statistics of the rest control variables are also reported in Table 2. The
average book-to-market equity is 0.92. The average free cash flow and cash level are
0.04 and 0.15; the two are surrogates of excess capital with which firms could distribute
excess cash through share repurchase.
The optimal leverage hypothesis indicates that firms use share repurchase
programs to achieve the optimal capital structure when the current debt ratio is below
the target one (Bagwell and shoven, 1988; Opler and Titman, 1996). Debt deviation is
the difference between current debt level and optimal debt level which is estimated via
the following regression:
Debt*it= β0 + β1 MBi,t + β2 SRTi(t-1) + β3 ROAit + β4 NOLCit + β5 Size it+ β6 TanAit + β7
SEit +β8 RDEit +β9 ILit + εit
(5 )
where Debt* is the optimal debt level, MB is the yearend market-to-book equity;
SRT is the annual return, ROA is the net income divided by averaged total assets;
NOLC is deferred taxes divided by total assets; Size is the nature logarithm of yearend
total assets; TanA is the fixed assets minus depreciation and divided by total assets; SE
is the selling and administrative expenses divided by revenue; RDE is R&D expenses
20
divided by total revenue; IL is the median debt-to-assets ratio for all firms in the same
industry. The average debt deviation is -2.5%, implying that on average firms are below
the target debt level and that urges firms to raise debt ratio through share repurchase
programs, according to the optimal leverage hypothesis.
The averaged stock option is 1%. The literature indicates that stock option could be
one of the manager’s concerns for preventing diluting share price. In our sampling
period, 2% of the sampling firms are associated with rumors of mergers. When being
potential targets, firms repurchasing shares could raise the margin price if the demand
curve of shares is negatively sloped. The average payout being perceived as an
alternative conduit of expending cash other than share repurchase is 45.8%.
Using the traditional event study approach, we calculate the abnormal returns in
different windows. Alternative windows (-1, 1), (-5, 5), (0, 20), (0, 40), and (0, 60) are
selected to capture the information impact around the dates of repurchase program. The
window (-5, 5) is to capture the impact from board approval to open market repurchase
which usually takes place 4-5 days after approval. The window (0, 40) is to cope with
the 2-month duration of a repurchase program. The window (0, 60) is selected to
capture the overall market reaction after the execution of a share repurchase program.
The corresponding averaged cumulative abnormal returns for the 5 windows are 1.16%,
21
-0.29%, 4.97%, 6.10% and 6.70%, respectively. The result illustrates a monotonic
increase in abnormal returns.
<<Insert Table 2 Here>>
4. Empirical Results
In table 3 we investigate managerial overconfidence and valuation. In panel A we
divide the sampling firms into quintiles based on size and market-to-book equity, and
calculate the mean measures of press-based overconfidence. The purpose of so doing is
to have a glimpse of how these overconfident firms or managers are characterized. The
results show that in general the firms of median size and with high growth potential
(high market-to-book equity) are associated with the highest overconfidence measure.
Assuming that firms follow the life cycle paradigm, the statistics indicate that managers
of firms in the stage of accelerated growth or of firms that have grown up to median
scale exhibit the highest overconfidence. It could be case that managers in these firms
have accumulated experiences of successes and therefore are nurtured to be
overconfident. They have a strong sense that the firm’s shares are undervalued and
therefore are motivated to launch repurchase programs. However, as compared with
22
firms with low market-to-book equity, firms with high market-to-book equity tend to be
glamour stocks that are less likely to be undervalued.
In panel B we evaluate the firm’s instrinsic value and investigate how managerial
overconfidence is related to the valuation. We use two approaches to gauge the fair
value of share repurchasing firms. The first one refers to Purnanandam and
Swaminathan (2004) that the fair value for share repurchasing firms are calculated using
price multiples, such as price-to-book and price-to-sales, of non-announced industry
peers that are close in size, and then compare this fair value (V) to the average
pre-announced price in the window (-10,-6) (P).
[ (P/V )Book = (P/B) Stock Repurchase Firm/(P/B)Matching Firm]
[ (P/V )Sales = (P/S) Stock Repurchase Firm/(P/S)Matching Firm]
(4 )
The second approach refers to Rhodes-Kropf et al.（2005）, the fair value is gauged
by conducting the following cross-section regression
＋
V it =α0 + α1 b it + α2 NI
it
+ α3 I(<0) (NI)+it + α4 LEV it + εi,
23
(5 )
where b denotes book value of assets, NI denotes net income and LEV denotes leverage
ratio. (P/V)CS denotes the ratio of the average price in the window (-10, -6) to the fair
value estimated from the cross sectional regression. The value (P/V )Book ,(P/V )Sales and
(P/V)CS denotes overvaluation when they are higher than 1 and undervaluation when
they are lower than 1.
The results illustrated in panel B indicate that the average (P/V)book for high-MOC
firms (1.188) is significantly highr than that for low-MOC firms (1.051). The average
(P/V)sales for high-MOC firms (1.279) is also higher than that for low-MOC firms
(1.252), albeit the difference is insignficant. Using the alternative metric referring to
Rhodes-Kropf et al.（2005）we find that the average (P/V)CS is higher for high-MOC
firms than for their low-MOC counterparts. The overall result indicates that firms with
overconfident managers are less likely to be undervalued.
In panel C we further investigate the relation between managerial overconfidence
and the attributes of a share repurchase program. The attributes of interest include
number of repurchases, percentage of shares repurchase, percentage of amount
repurchase, percentage of execution, and price difference. The result from the univariate
test that high-MOC firms are associated with more share repurchase programs (4.315)
24
than that of low-MOC firms (3.804). The percentage of share repurchase is higher for
high-MOC firms (2.066%) than for low-MOC firms (1.898%). The price difference,
being defined as the scaled difference between the mid-price of announced price range
and the average price three days after the program, is higher for high-MOC firms (0.214)
than for low-MOC firms (0.155). High-MOC firms on average are aslo associated with
a higher percentage of dollar amount and a higher rate of execution than those of
low-MOC firms. However, the differences are insignficant.
The overall result from table 3 indicates high-MOC firms are less likely to be
undervalued than low-MOC firms. High-MOC firms are more active to launch more
share repurchase programs, to claim a higher percentage of shares to be repurchased,
and set a higher target price.
We also conduct tests of differences in medians. The
overall picture in intact.
<<Insert Table 3 Here>>
The empirical model referred to Dittmar (2000) is formulated as follow.
25
SRit =β0 + β1MOCi,t + β2Sizei,t + β3ROEi,t + β4BMi,t + β5Deviationi,(t-1) + β6 Options i,(t-1)
+ β7Cashi,t + β8FCFi,t+ β9INVOi,t+ β10D(Takeover)i,(t-1) + β11Payouti,(t-1) +
β12CGIi,t + εi,t
(6)
where SR denotes the attributes of share repurchase program, MOC denotes managerial
overconfidence, size denote the nature logarithm of firm’s assets, BM denotes
book-to-market equity, ROE is return on earrings, FCF denotes free cash flow being
defined as earning before taxes and depreciation minus taxes, interest and cash
dividends and divided by initial assets, Cash denotes cash divided by initial assets.
Stock option is the expected employee stock options divided by the total outstanding
shares in the prior yearend. INVO is the sum of market equity and total debt divided by
total assets in the yearend. D (takeover) is a dummy that is assigned the value 1 when
the underlying firm is associated with the rumor of being an acquirer or a target in the
year or previous year and 0 otherwise. These variables are included in the models for
controlling the alternative motives of launching share repurchase programs.
Corporate governance index (CGI) being included in the model is to explore
whether corporate governance plays a counterbalance role in deterring managerial
overconfidence in launching share repurchase programs. Consolidating different
dimensions into a composite index is to comprehensively capture the overall quality of a
26
firm’s governance structure (Boehren and Oedegaard, 2003).
The
index is
constructed by summing the following dummies: board control (1 for smaller than
sample median and 0 otherwise), supervisory control (1 for smaller than sample median
and 0 otherwise), voting-cash deviation (1 for smaller than sample median and 0
otherwise), pledge ratio (1 for smaller than sample median and 0 otherwise), related
party sales ((1 for smaller than sample median and 0 otherwise), related party purchase
(1 for smaller than sample median and 0 otherwise), related party loan (1 for smaller
than sample median and 0 otherwise), related party guarantee (1 for smaller than sample
median and 0 otherwise)，cash flow rights (1 for higher than sample median and 0
otherwise), cash/voting ratio (1 for higher than sample median and 0 otherwise).
Therefore, CGI is in the range between 0 and 10. Deviation refers to the difference
between firm’s debt ratio and optimal debt ratio estimated via the model of Hovakimain
et al. (2004).
In table 4 we conduct tobit regressions of the percentage of share repurchased. The
results indicate that MOC is positively correlated with the percentage of shares
repurchased. Moreover, firm size, the natural logarithm of firm’s assets, is negatively
correlated with the claimed portion of shares repurchase. This could be due to the
possibility that large firms are more likely to be the focal point of investors and are
27
therefore less likely to be undervalued by the market.
We also find that firms with high book-to-market equity tend to launch a higher
large portion of shares repurchased, which is consistent with the undervaluation
hypothesis. Again, we find that debt deviation is positively correlated with the
percentage of share repurchase programs, which is inconsistent with the optimal
leverage hypothesis while consistent with the overconfidence hyothesis.
<<Insert Table 4>>
In table 5 we conduct tobit regressions of the percentage of the dollar amount
repurchased, an alternative measure of the scale of share repurchase program that
simultaneously considers the number of shares and per share price. The results show
that overconfidence is positively correlated with the proportion of dollar amount of
share repurchase. The results from the rest control variables are qualitatively similar to
the results from table 4. The only exception is that the takeover dummy is positively
correlated with the dollar amount of share repurchase, indicating that firms that
encounter the threat of takeover tend to launch large-scale share repurchase programs.
28
The results from table 4 and table 5 support our speculation that managerial
overconfidence is one of major driving forces for managers to launch large-scale share
repurchase program. Moreover, checking with the possible hypotheses that dictate
firm’s launching share repurchase program we find the undervaluation hypothesis
receives supporting evidence in the sense that firms having been neglected by the
market (high book-to-market equity and low investment potential) tend to launch
large-scale. Moreover, the takeover deterrence hypothesis is also supported that firms
being as merger targets tend to launch large-scale share repurchase program for
deterring possible raiders. However, the excess capital hypothesis, the leverage
adjustment hypothesis and management incentive hypothesis are not supported herein.
These hypotheses might affect firms’ decision of whether to launch share repurchase
program but not the decision of program scale. Since a large portion of the listed firms
in our sampling have experiences of launching share repurchase programs, it would be
less sensible to investigate the issue of whether firms would like to launch share
repurchase programs.
<<Insert Table 5 Here>>
29
In table 6 we investigate how managerial overconfidence is related to the
percentage of execution of the repurchase program. The result is consistent with our
intuition that overconfident managers tend to execute a high portion of what they have
announced. MOC is significantly and positively correlated with the execution rate.
Moreover, the investment opportunity is negatively correlated with the execution rate,
which further renders supporting evidence to the undervaluation hypothesis because
firms with insufficient investment opportunities tend to be out-of-favor stocks having
shares been undervalued by the market. In order to uphold the price level to the
anticipated level, overconfident managers tend to execute a high percentage of the
claimed repurchased shares.
The result also indicates that takeover dummy is negatively correlated with the
percentage of execution. One possibility is that the repurchase signal is strong enough
so that the anticipated price level set by overconfident managers would soon be attained.
The spare cash from unexercised program could be saved for alternative promising
investments. Since a low execution of the repurchase program could attain the
anticipated price level, the firm could exempt from the threat of takeover.
<<Insert Table 6 Here>>
30
In table 7 we investigate how managerial overconfidence effects on the number of
share repurchase programs. The statistics in table 1 shows that more than 70% of
announcement firms launching more than 1 share repurchase program. It is intuitively
appealing to investigate the issue of how managerial overconfidence is related to the
times of repurchase programs. The acquired theorists indicate that managers could learn
to be overconfident through prior experiences. If this is the case, the successes from
prior share repurchase programs will enhance the level of overconfidence and therefore
further encourages the managers to launch another repurchase program. However, the
result in table 7 fails to exhibit a significant positive correlation between number of
repurchase program and the level of managerial overconfidence, albeit the regression
coefficient is positive as expected.
The results from the rest control variables such as size, book-to-market equity, and
investment opportunity are consistent with prior findings that small-size and
out-of-favor stocks need more runs of repurchases to reach the anticipated price level
set by the overconfident managers. Moreover, firm’s return on equity is negatively
correlated with the number of programs, implying that good performing firms are less
likely to be undervalued and therefore necessitate few runs of repurchase programs.
31
Free cash flow is negatively correlated with the number of repurchase programs, which
is inconsistent with the prediction of excess capital hypothesis indicating firms having
excess cash tend to distribute it to shareholders through repurchasing shares. Without
jeopardizing the whole picture, one possibility to account for this phenomenon is that
firms concentrate their use of free cash in the first few runs of repurchase programs.
Moreover, we find that debt deviation is negatively correlated with the number of
repurchases. This is consistent with the optimal leverage hypothesis implying the more
deviation from the optimal capital structure the more runs of repurchase programs to fill
in the gap. However, the result is inconsistent with the findings in table 5 where debt
deviation is positively correlated with the percentage of dollar amount repurchased. A
possible reconciliation is that firms aiming to adjust capital structure through share
repurchase are through piecemeal repurchases rather than one-shot repurchase. This is
also consistent with the general understanding that an abrupt adjustment in capital
structure is associated with cost.
Moreover, the takeover dummy is negatively
associated with number of repurchase programs. Combining with the finding in table 5,
we find that firms confronting with takeover threat might engage in one-shot
large-amount repurchase to resist the threat.
32
<< Insert Table 7 Here>>
In table 8 we explore how managerial overconfidence is related to price difference,
being defined the price rebound from the mid-price of announced price range to the
average price after the program. The price difference is supposed to be positively
correlated with the level of managerial overconfidence because the market would
sooner or latter come to its sense that the exaggerated signal emitted by overconfident
managers need to be rectified. The higher the level of managerial overconfidence, the
larger the rectification is needed.
The result basically supports our conjecture. Managerial overconfidence is
positively correlated with the price difference. Moreover, debt deviation is also
positively correlated with the price difference. We find that firms with a higher debt
ratio are more zealous to engage in share repurchase programs. In other words, high
leverage could be another manifest of overconfidence in the sense that managers are
reluctant to issue undervalued equity and that results in a high debt ratio, or that they are
confident about firm value as to issue more debt to finance the repurchase programs.
High level of overconfidence is therefore associated with a significant price rebound.
Finally, the takeover dummy is positively correlated with the price difference. This
33
could be due to the fact that outside investors interpret the share repurchase program is
more for managerial entrenchment than for signaling undervaluation.
<<Insert Table 8 Here>>
In table 9 we further relate managerial overconfidence and the number of share
repurchase programs to the announcement returns in different windows. The regression
results show that managerial overconfidence is negatively correlated with CAR (0, 40)
and CAR (0, 60). The relations between managerial overconfidence and short event
windows, such as CAR (-1, 1), CAR (-5, 5) and CAR (0, 20), are insignificant. This
implies that the market is relatively neutral to the share repurchase announcements
made by overconfident managers. As the passage of time up to the deadline of the
program execution, the market is able to discern managerial overconfidence and
attaches lower valuation to the share repurchase programs launched by overconfident
managers. Moreover, we find that the number of programs is negatively correlated with
CAR (-1, 1) and CAR (-5, 5). This could be due to the case that managers intermittently
issue promising news such as share repurchases to enjoy the positive price effect.
34
However, the marginal positive effect decreases as the number of signals accumulated.
The results from the other control variables indicate that book-to-market equity is
positively correlated with the announcement returns. This is consistent with the
undervaluation argument that small-size and high book-to-market firms tend to be
undervalued and therefore are associated with higher announcement returns. Moreover,
we find that free cash flow is positively correlated with CAR (-5, 5), CAR (0, 40) and
CAR (0, 60). Cash level is also positively correlated with CAR. The result is consistent
with the excess capital hypothesis of Easterbrook (1984) and Jensen (1986), implying
that repurchasing stock is flexible approach to distribute excess cash and to fix the
agency problem embedded in the excessive cash.
Moreover, we find investment opportunity is negatively correlated with the
announcement returns. This could be explained by the undervaluation hypothesis that
firms with high growth potentials are less likely to be undervalued, so their share
repurchase programs are associated with lower valuation. From an alternative
perspective, the market assumes that these high-growth firms should have alternative
investment opportunities better than share repurchase programs and therefore attaches a
lower appraisal on the share repurchase programs launched by high-growth firms.
Finally, the takeover dummy is negatively associated with the returns, implying that the
35
share repurchase programs aiming to entrenching management are less welcomed by the
market.
<<Insert Table 9 Here>>
We also include managerial overconfidence and the attributes of a share repurchase
program, one at a time, in the regression analysis. The depedent variables are the
announcment returns in various windows. All the other control variables are the same as
in table 9.
For brevity we only report the regression coefficient of managerial
overconfidence and the coefficient of the attribute variables in table 10. The result
shows that MOC is significantly negative in the regression of CAR (0, 40) and CAR (0,
60) when the attribute variables are in turn being included in the models.
The result indicates that the percentage of shares claimed to be repurchased and the
percentage of dollar amount are positively correlated with CAR (-1, 1) and CAR (-5, 5),
while are negatively correlated with CAR (0, 20) and CAR (0, 40). Moreover, the
percentage of execution is negatively correlated with CAR (0, 20), CAR (0, 40) and
CAR (0, 60).
This could be due to case that in the first beginning the firms that launch
36
large-scale repurchase programs, in terms of percentage of shares and percentage of
dollar amount, draw favorable market appraisal in that outside investors interpret the
embedded signal to be credible.
However, as the passage of time the market in general
realize the the large-scale repurchase is more for managerial overconfidence than for
signal of credibility. As a matter fact, both the regression coefficient of MOC and the
regression coefficient of scale variables are signficnatly negatively in the regression
analysis of CAR (0, 40) and CAR (0, 60). We find that the percentage of execution is
significantly negative in the regression analysis of CAR (0, 20), CAR (0, 40), and CAR
(0, 60).
We provide a possible explanation to this: the execution of a share repurchase
program is costly and should be stopped when the anticipated price level is met. High
percentage of execution, from the ex-post perspective, indicates the program is not that
welcomed by the market and therefore associated with a lower abnormal return. In an
unreported result we also explore the possible interactions between managerial
overconfidence and the attributes of share repurchase programs, and include the
interactions into the regression analysis of the announcement return. We find that the
interaction between MOC and ln (times) is negative. The interaction between MOC and
the percentage of shares repurchased is also negative. However, the interaction between
between MOC and the percentage of execution is positive. Since all the interactions are
37
only marginally significant at 10% level, we would not overemphasize their effects on
the announcement returns.
<<Insert Table 10 Here>>
5. Robustness Check
In the prior sections we deem managerial overconfidence is an exogenous variable.
However, if managerial overconfidence is an acquired nature that is affected by other
firm’s characteristics, the result that managerial overconfidence drives the impulse to
launch large-scale, numerous and high-execution programs might not be sustainable.
For robustness, we conduct two-stage regression and use the first-stage regression to
isolate the residual managerial overconfidence that is unrelated to other firm’s
characteristics. The first regression model is as follows.
MOCi,t =β0+ β1 SIZE i,t + β2 ROEi,t + β3 BMi,t + β4FCFi,t+ εi.
(7)
The residual term is then included in the second stage regression as follows.
38
SRit =β0+β1 Residual-MOC+ β2 Deviation i(t-1) +β3 Optionsi(t-1) +β4 Cashit +β5 INVOit
+β6 Takeoveri(t-1)+β7 Payouti(t-1)+β8 CGIit+εit
(8)
The result summarized in table 11 is qualitative similar to the previous findings. A
noteworthy issue is that corporate governance becomes positively correlated with the
size of repurchase program and negatively correlated with times of repurchase program.
From an alternative perspective, corporate governance might play a positive role in
affecting share repurchase program when the managerial overconfidence measure
isolates its common variation with corporate governance index. Firms with a good
governance structure tend to launch a large-scale repurchase program. However, share
repurchase programs are associated with execution cost which deters firms with a good
governance structure from repeatedly launching programs.
<<Insert Table 11 Here>>
Moreover, someone might argue that share repurchase programs taking place in
period of 2008 financial tsunami might be more for upholding price level than for
managerial overconfidence. We also rerun all the tables by excluding the sample in
39
2008. An unreported result from the subsample yields a qualitative similar result. Our
story of relating managerial overconfidence to share repurchase therefore remains intact
after taking the concern of the impact of the 2008 financial tsunami.
We find positive relations between managerial overconfidence and the intensitiy
of share repurchase program that is manifested in scale and execution of the program.
The only exception is frequency. We conduct a robustness check by recounting the
frequency that tags along after managerial changeover. In so doing, the independent
variable (managerial overconfidence) and the dependent variable (frequency) could be
indebted to managers. However, the result remains insignificant.
We find that the result from debt deviation obviously contradicts the prediction of
optimal leverage hypothesis. To ensure the result holds water, we degenerate the
variable of debt deviation into a dummy by assigning the value 1 when the debt ratio is
below the optimal debt ratio and 0 otherwise. This is to see if firms below the optimal
debt level would act differently in adjusting their capital structure from firms that are
above. If the optimal leverage hypothesis prevails, we would expect to find the
regression coefficient is significantly positive. Unfortunately, the regression coefficient
is significantly negative. Therefore, our results lend little lenity to the optimal leverage
hypothesis.
40
6. Concluding Remarks
In this paper we examine how the level of managerial overconfidence affects the
intensity of share repurchase programs ramified into scale, execution, and frequency.
And how market respond to the share repurchase programs launched by overconfident
managers. Our results are easily summarized as follows. The level of managerial
overconfidence is positively correlated with the intensity of share repurchase programs.
The market in general negatively appraises managerial overconfidence, at least partly
attributed to the fact that firms with overconfident managers are less likely to be
undervalued. Firms that launch intensified share repurchase programs are positivley
appraised in the first beginning. However, as the passage of time up to 2 to 3 months
post the program, firms launching intensified share repurchase programs are negatively
appraised.
Our paper also contributes to the growing literature on behavioral corporate
finance. This thread of studies examines the relation between behavioral characteristics
of corporate managers and corporate policies (e.g. Baker, Ruback, and Wurgler, 2007;
Ben-David, Graham, and Harvey, 2007; Hackbarth, 2008; Malmendier and Tate, 2005,
2008; Malmendier, Tate, and Yan, 2010). We find that managerial overconfidence does
41
affect the intensity of a share repurchase program. However, respectable investors are
not gullible by the managerial impulse in launching large-scale and intensified share
repurchase programs.
42
References
Asquith, P., and D. Mullins (1986) Signalling with Dividends, Stock Repurchases, and
Equity Issues. Financial Management, 15(3): 27-44.
Alicke, M. D., M. L. Klotz, D. L. Breitenbecher, T. J. Yurak, et al. (1985) Global
Self-Evaluation as Determined by the Desirability and Controllability of Trait
Adjectives. Journal of Personality and Social Psychology, 49: 1621-1630.
Alicke, M., M. Klotz, D. Breitenbecher, and T. Yurak, (1995). Personal Contact,
Individuation, and the Better-than-Average Effect. Journal of Personality & Social
Psychology, 68: 804-825.
Bagwell, L. S. (1991). Share Repurchase and Takeover Deterrence. Rand Journal of
Economics, 22(1): 72-88.
Bagwell, L. S., and John B. Shoven, (1989). Cash Distribution to Shareholders. Journal
of Economic Perspectives, 3: 129-140.
Baker, Malcolm, Richard S. Ruback, and Jeffrey Wurgler (2007). Behavioral Corporate
Finance: A Survey. Handbook of Corporate Finance: Empirical Corporate Finance,
Volume 1: 145-178.
Ben-David, I., Graham, J. R., & Harvey, C. R. (2007). Managerial overconfidence and
corporate policies. Working paper, American Finance Association 2007 Meetings.
Bens, D. A., V. Nagar, and M. H. F. Wong, (2002). Real Investment Implications of
Employee Stock Option Exercises. Journal of Accounting Research, 40: 359-393.
Boehren, O. and B. Oedegaard (2003). Governance and Performance Revisited,
European Corporate Governance Institute. Working Paper, No. 28.
Brennan, M. J., and A.V. Thakor (1990) Shareholder Preferences and Dividend Policy.
Journal of Finance, 45: 993-1019.
Brown, R., & Sarma, N. (2007). CEO overconfidence, CEO dominance and corporate
acquisition. Journal of Economics and Business, 59(5), 358-379.
Camerer, Colin, and Dan Lovallo (1999). Overconfidence and excess entry: An
experimental approach. American Economic Review, 89: 306-318.
Comment, R., & Jarrell, G. A. (1991). The relative Signaling Power of Dutch-Auction
and Fixed-Price Self-Tender Offers and Open-Market Share Repurchases. Journal
43
of Finance, 46(4): 1243-1271.
Cooper, A. C., Woo, C. Y., & Dunkelberg, W. C. (1988). Entrepreneurs’ perceived
chances for success. Journal of Business Venturing, 3(2): 97-109.
Dann, L. Y., R. W. Masulis, and D. Mayers, (1991) Repurchase Tender Offers and
Earnings Information. Journal of Accounting and Economics, 14: 217-251.
Deshmukh Sanjay, Anand M. Goel, and Keith M. Howe (2010). CEO Overconfidence
and Dividend Policy. Working Paper.
Dittmar, A. K. (2000). Why do firms repurchase stock? Journal of Business, 73(3):
331-355.
Dunsby, Adam (1994). Share Repurchases, Dividends, and Corporate Distribution
Policy. Working paper. Philadelphia: The Wharton School of the University of
Pennsylvania.
Easterbrook, Frank H., (1984) Two Agency Cost Explanations of Dividends.
American Economic Review, 74: 650-659.
Feather, N. T. and Simon, J. G. (1971). Attribution of responsibility and valence of
outcome in relation to initial confidence and success and failure of self and other.
Journal of Personality & Social Psychology, 18(2): 173-188.
Fenn, George W., and Liang, Nellie. (1997). Good News and Bad News about Share
Repurchases. Working paper, Washington, D. C.: Board of Governors of the
Federal Reserve.
Gervais, S., & Odean, T. (2003). Overconfidence, investment policy, and executive
stock options. Working Paper, Rodney L. White Center for Financial Research.
Goel, Anand M., and Anjan V. Thakor (2008). Overconfidence, CEO selection, and
corporate governance, Journal of Finance, 63: 2737–2784.
Grullon, G., and R. Michaely, (2002) Dividends, Share Repurchases, and the
Substitution Hypothesis. Journal of Finance, 57(4): 1649-1684.
Hackbarth, D. (2008) Managerial traits and capital structure decisions, Journal of
Financial and Quantitative Analysis, 43: 843–881.
Heaton, J. B., (2002). Managerial Optimism and Corporate Finance. Financial
Management 31: 33–45.
44
Hertzel, M. and P.C., Jain (1991). Earnings and Risk Cchanges Around Stock
Repurchase Tender Offers. Journal of Accounting and Economics, 14: 253-274.
Hovakimain, A., Hovakimain, G., & Tehranian, H. (2004). Determinants of Target
Capital Structure: The Case of Dual Debt and Equity Issues. Journal of Financial
Economics, 71: 517-540.
Ikenberry, David, Josef Lakonishok, and Theo Vermaelen, (1995). Market
Underreaction to Open Market Share Repurchases. Journal of Financial
Economics, 39: 181-208.
Jensen, M. C. (1986). Agency Costs of Free Cash, Corporate Finance, and Takeovers.
American Economic Review, 76(2): 323-329.
Jolls, Christine (1996). The Role of Compensation in Explaining the Stock-Repurchase
Puzzle. Working paper. Cambridge, Mass.: Harvard Law School.
Kruger, J. (1999). Lake Wobegon be gone! The below-average effect and the egocentric
nature of comparative ability judgments. Journal of Personality and Social
Psychology, 77(2): 221–232.
Landier, A. and Thesmar, D. (2004). Financial contracting with optimistic entrepreneurs:
theory and evidence. Working paper, University of Chicago.
Langer, Ellen J. (1975). The illusion of control, Journal of Personality and Social
Psychology, 32: 311-328.
Larwood, L., and W. Whittaker, (1977). Managerial Myopia: Self-Serving Biases in
Organizational Planning. Journal of Applied Psychology 62: 194-198.
Lee, D.S, W. H Mikkelson and M.M. Partch (1992). Managers' Trading Around Stock
Repurchases. Journal of Finance, 37(5): 1947-1961.
Lucas. D. J., McDonald, R. L. (1996) Shareholder Heterogeneity, Adverse Selection,
and Payout Policy. Working paper.
Malmendier, U., & Tate, G. (2005a). CEO Overconfidence and Corporate Investment.
Journal of Finance, 60(6): 2661-2700.
Malmendier, U., & Tate, G. (2005b). Does overconfidence affect corporate investment?
CEO overconfidence measures revised. European Financial Management, 11(5):
649-659.
45
Malmendier, Ulrike, and Geoffrey Tate, (2008). Who makes acquisitions? CEO
overconfidence and the market’s reaction. Journal of Financial Economics, 89(1):
20-43.
Malmendier, Ulrike, Geoffrey Tate, and Jun Yan, (2010). Managerial beliefs and
corporate financial policies, NBER, Working Paper 15659.
Miller, D. T., and Ross, M. (1975), Self-Serving Bias in Attribution of Causality: Fact or
Fiction? Psychological Bulletin 82: 213-225.
Moore, D. A., and T. G. Kim, (2003). Myopic social prediction and the solo
comparison effect. Journal of Personality and Social Psychology, 85: 1121-1135.
Nisbett, R E and L R Ross. (1980). Human inference: Strategies and shortcomings of
social judgment. Englewood Cliffs, NJ: Prentice-Hall.
Opler, T. and S. Titman (1996). The Debt-Equity Choice: An Analysis of Issuing Firms,
Working paper, Columbus: Ohio State University.
Purnanandam, A. and Swaminathan, B. (2004), Are IPOs Really Underpriced? Review
of Financial Studies, 17, 811-848.
Rhodes-Kropf M., Robinson, D., and Viswanathan, S. (2005), Valuation waves and
merger activity: The empirical evidence, Journal of Financial Economics , 77,
561-603.
Roll, Richard, (1986). The Hubris Hypothesis of Corporate Takeovers. Journal of
Business 59(2): 197-216.
Sevnson, O., (1981) Are We All Less Risky and More Skillful Than Our Fellow Drivers?
Acta Psychologica 47: 143-148.
Stephens, C. P., and M. S. Weisbach, (1998). Actual Share Reacquisitions in
Open-Market Repurchase Programs. Journal of Finance, 53: 313-334.
Vermaelen, T. (1981). Common Stock Repurchases and Market Signaling: An
Empirical Study. Journal of Financial Economics, 9(2): 139-183.
Weinstein, N., (1980). Unrealistic Optimism about Future Life Events. Journal of
Personality and Social Psychology, 39: 806-820.
46
47
Table 1: Sample Distribution
This table reports the sample distribution of share repurchases in the sampling period from August 2000
through December 2008. Panel A reports the distribution by industry breakdown. Panel B reports the
frequency distribution for firms that engaged in share repurchase programs. Panel C reports the
distribution by yearly breakdown.
Panel A: by industry
Industry
No.
Electronic appliance
379
Computer and peripheral
%
Industry
No.
%
13.81 Trade and merchandise
54
1.97
354
12.90 Electric appliance and cable
53
1.93
Semiconductor
322
11.73 Plastic
49
1.79
Optical electronics
233
8.49 Biomedical
35
1.28
Other electronics
179
6.52 Transportations
34
1.24
Telecommunication
160
5.83 Food
28
1.02
Information service
119
4.34 Managed stocks (Gui-Tai)
27
0.98
Electronics channel
112
4.08 Paper
26
0.95
Electronic mechanics
107
3.90 Cement
23
0.84
Textile and fiber
101
3.68 Rubber
16
0.58
Construction
92
3.35 Gas and fuel
16
0.58
Others
78
2.84 Truism
11
0.40
Iron
66
2.41 Automobile
9
0.33
Chemistry
59
2.15 Glass and ceramic
2
0.07
2,744
100.00
Total
Panel B: by frequency
No. of Rep.
Firms
%
No. of Rep.
Firms
%
1
233
29.78%
4
66
8.43%
2
154
19.67%
5
54
6.90%
3
130
16.60%
6 and above
146
18.65%
Total
783
100.00%
Panel C: by year
Year
No.
%
Year
No.
%
2000
217
7.91
2005
285
10.39
2001
213
7.76
2006
231
8.42
2002
173
6.30
2007
217
7.91
2003
191
6.96
2008
783
28.54
2004
434
15.82
48
Total
2,744
49
100.00
Table 2: Summary Statistics
The sample in the period from August 2000 through December 2008 is collected from the Treasury Stock
Module from the Taiwan Economic Journal (TEJ), a data company in Taiwan. The effective sample after
excluding financial companies comprises of 2,744 share repurchase announcements. MOC denotes
managerial overconfidence which is defined as a/(a+b), where a denotes the the number of the words of
“confident” and “optimistic” and b denotes the number of words of
“reliable”, “cautious”,
“conservative”, “practical”, “frugal”, “steady”, “not confident”, and “not optimistic” from press
portrayals. The calculation is subject to the adjustment of managerial turnover. The source of data is from
the Company News Clip from TEJ. Number of repurchases is the accumulated times of repurchases.
Percentage of share repurchase is the number of repurchased shares in proportion to the total outstanding
shares in prior yearend. Percentage of amount repurchase is the dollar amount repurchased in proportion
to total equity market value in prior yearend. Percentage of execution is the repurchased shares in
proportion to the announced shares to be executed.
Price difference denote the difference between the
mid-price of announced price range and the average price three days after the program divided by the
average price three days after the program ( (MP-P+3)/P+3)
B/M equity is the ratio of book equity to
market equity in the prior yearend. Return on equity (ROE) is net income divided by average book equity.
Free cash flow is defined as earnings before depreciation minus taxes, interest experiences, preferred
dividend, and cash dividend, and divided by beginning total assets. Cash is defined as the sum of ending
cash and short term investment and divided by ending total assets. Debt deviation is the difference
between current debt level and optimal debt level which is estimated via the following regression:
Debt*it= β0 + β1 MBi,t + β2 SRTi(t-1) + β3 ROAit + β4 NOLCit + β5 Size it+ β6 TanAit + β7 SEit +β8 RDEit +β9
ILit + εit ，where Debt* is the optimal debt level, MB is the the yearend market-to-book equity; SRT is the
annual return, ROA is the net income divided by averaged total assets; NOLC is deferred taxes divided by
total assets; Size is the nature logarithm of yearend total assets; TanA is the fixed assets minus
depreciation and divided by total assets; SE is the selling and administrative expenses divided by revenue;
RDE is R&D expenses divided by total revenue; IL is the median debt-to-assets ratio for all firms in the
same industry. Stock option is the expected employee stock options divided by the total outstanding
shares in the prior yearend. INVO is the sum of market equity and total debt divided by total assets in the
yearend. D (takeover) is a dummy that is assigned the value 1 when the underlying firm is associated with
the rumor of being an acquirer or a target in the year or previous year and 0 otherwise. Corporate
governance index (CGI) is composite corporate governance index that is constructed by summing the
following dummies: board control (1 for smaller than sample median and 0 otherwise), supervisory
control (1 for smaller than sample median and 0 otherwise), voting-cash deviation (1 for smaller than
sample median and 0 otherwise), pledge ratio (1 for smaller than sample median and 0 otherwise), related
party sales ((1 for smaller than sample median and 0 otherwise), related party purchase (1 for smaller than
sample median and 0 otherwise), related party loan (1 for smaller than sample median and 0 otherwise),
50
related party guarantee (1 for smaller than sample median and 0 otherwise)，cash flow rights (1 for higher
than sample median and 0 otherwise), cash/voting ratio (1 for higher than sample median and 0
otherwise). Therefore, CGI is in the range between 0 and 10. The abnormal returns in different windows
are gauged via traditional event study with the estimation of αand β using the returns of 250 trading
days prior to announcement. Payout is defined as cash dividend divided by net income. The abnormal
returns in different windows are gauged via traditional event study with the estimation of αand β
using the returns of 250 trading days prior to announcement..
No.
Mean
Q1
Q2
Q3
S.D.
MOC
2094
0.46
0.25
0.50
0.67
0.32
No. of repurchases
2744
3.74
1.00
3.00
5.00
3.69
% of shares repurchase (%)
2607
2.03
0.84
1.65
2.77
1.79
% of amount repurchase (%)
2607
1.63
0.55
1.20
2.21
1.59
% of execution (%)
2743
70.08
41.53
85.06
100.00
33.91
Price difference
2204
0.178
-0.028
0.113
0.323
0.351
B/M equity
2674
0.92
0.53
0.80
1.191
0.57
ROE
2721
9.65
3.01
8.54
16.09
11.79
FCF
2721
0.04
0.00
0.03
0.07
0.08
Cash
2721
0.15
0.05
0.11
0.21
0.14
Debt deviation
2727
-2.50
-9.58
-0.60
4.40
12.10
Stock option
2667
0.01
0.00
0.00
0.00
0.03
INVO
2588
1.36
0.90
1.14
1.56
0.78
D(takeover)
2744
0.02
0.00
0.00
0.00
0.15
CGI
2737
5.829
5.00
6.00
7.00
1.97
Dividend payout
2721
0.458
0.00
0.37
0.63
1.72
CAR(-1,1)
2498
1.16
-2.60
1.43
5.34
7.01
CAR(-5,5)
2498
-0.29
-7.32
0.10
6.61
12.34
CAR(0,20)
2498
4.97
-3.56
4.97
13.26
15.39
CAR(0,40)
2498
6.10
-7.16
5.94
19.00
23.25
CAR(0,60)
2498
6.70
-11.46
6.69
22.81
30.41
51
Table 3: Managerial Overconfidence and Valuation
This table reports managerial overconfidence (MOC) and valuation. In panel A, the sample is dividied
into quintiles based on size and market-to-book equity, respectively. The averaged MOC for each size and
market-to-book quintile is reported. In panel B, managerial overconfidence is divided into high and low
groups based on the sample median. Th test in difference of the valuation metrics between high and low
managerial overconfidence is reported accordingly. The valuation metrics, referring to Purnanandam and
Swaminathan(2004), are calculated as the ratio of the average pre-announced price of the
share-repurchase firm in the window (-10,-6) (P) to the fair value that is guagued using price multiples,
such as price-to-book and price-to-sales, of non-announced industry peer that is close in size (V). That is,
[ (P/V )Book = (P/B) Stock Repurchase Firm/(P/B)Matching Firm] and [ (P/V )Sales = (P/S) Stock Repurchase Firm/(P/S)Matching
Firm]. The third measure is referred to Rhodes-Kropf et al.（2005）, the fair value is gauged by conducting
the following cross-section regression; V it =α0 + α1 b it + α2 NI＋ it + α3 I(<0) (NI)+it + α4 LEV it + εi, where b
denotes book value of assets, NI denotes net income and LEV denotes leverage ratio. (P/V)CS denotes the
ratio of the average price in the window (-10, -6) to the fair value estimated from the cross sectional
regression. The value (P/V)Book ,(P/V )Sales and (P/V)CS denotes valuation metrics in the sense that firms
are overvalued (undervalued) when they are higher (lower) than 1. Panel C reports the tests in differences
in means of the attribute variables for high and low managerial overconfidence. The attribute variables
include number of repurchases, percentage of shares repurchase, percentage of dollar amount repurchase,
and percentage of execution, and price difference). ***, **, and * denotes the significance level of 1%,
5%, and 10%, respectively.
Panel A: MOC in Different Quintiles
Size
M/B
1
0.4148
0.4147
2
0.4475
0.4645
3
0.5002
0.4607
4
0.4799
0.4718
5
0.4624
Panel B: Managerial Overconfidence and Valuation
(P/V)Book
MOC
0.5019
(P/V)Sales
(P/V)CS
Mean
t-value
Mean
t-value
Mean
t-value
H
1.188
1.279
1.051
.511
(.609)
1.151
L
2.410
(.016)**
2.410
(.016)**
1.252
1.061
Panel C: Managerial Overconfidence and Attributes of Share Repurchase
MOC
t
H
L
No. of repurchase
4.315
3.804
2.953***
% of shares repurchase
2.066
1.898
2.544**
% of amount repurchase
1.626
1.549
1.524
% of execution
70.87
69.432
0.969
Price difference
0.214
0.155
3.511***
52
Table 4: Percentage of Shares Repurchase and Managerial Overconfidence
This table reports the regression of percentage of shares repurchase on managerial overconfidence. The
dependent variable is the number shares repurchased in proportion to total outstanding shares in the
previous yearend. The independent variable, MOC, and other variables are defined in Table 2. In each
cell the regression coefficient and z-statistics in parentheses are reported in the upper and lower case,
respectively. ***, **, and * denote the significance level of 1%, 5%, and 10%, respectively.
Intercept
MOC
Size
Model 1
(N=2003)
7.031
Model 2
(N=2003)
6.305
Model 3
(N=2003)
6.455
Model 4
(N=2003)
6.329
Model 5
(N=2003)
6.967
(13.713)***
(12.115)***
(12.435)***
(12.097)***
(13.067)***
0.262
0.240
0.241
0.243
0.247
(2.301)**
(2.099)**
(2.107)**
(2.123)**
(2.178)**
-0.329
-0.316
-0.314
-0.316
-0.320
(-11.549)***
(-10.855)***
(-10.789)***
(-10.853)***
(-11.075)***
0.176
0.161
-0.055
(2.202)**
(1.854)*
(-0.577)
-0.005
-0.002
0.007
(-1.266)
(-0.442)
(1.739)*
0.367
0.303
0.434
0.834
(0.599)
(0.482)
(0.687)
(1.321)
0.443
0.348
0.462
0.797
(1.464)
(1.163)
(1.512)
(2.570)**
0.005
0.006
0.005
0.006
0.005
(1.638)
(2.016)**
(1.746)*
(2.058)**
(1.661)*
0.276
0.057
-0.027
0.051
0.192
(0.288)
(0.059)
(-0.028)
(0.053)
(0.201)
BM
ROE
FCF
Cash
Debt deviation
Stock option
INVO
D(Takeover)
CGI
Dividend Payout
Yearly Fixed effect
2
Adjusted R
-0.207
-0.378
(-4.318)***
(-5.328)***
0.296
0.288
0.269
0.284
0.249
(1.325)
(1.280)
(1.196)
(1.263)
(1.115)
0.015
0.016
0.020
0.016
0.012
(0.670)
(0.681)
(0.883)
(0.695)
(0.551)
0.003
0.003
0.006
0.004
0.003
(0.154)
(0.193)
(0.331)
(0.214)
(0.148)
yes
yes
yes
yes
yes
0.074
0.067
0.065
0.067
0.079
53
Table 5: Dollar Amount Repurchased and Managerial Overconfidence
This table reports the regression of percentage of dollar amount repurchased on managerial
overconfidence. The dependent variable is the dollar amount repurchased in proportion to total market
value of equity in the previous yearend. The independent variable, MOC, and other variables are defined
in table 2. In each cell the regression coefficient and z-statistics in parentheses are reported in the upper
and lower case, respectively. ***, **, and * denote the significance level of 1%, 5%, and 10%,
respectively.
Intercept
MOC
Size
Model 1
(N=2003)
Model 2
(N=2003)
Model 3
(N=2003)
Model 4
(N=2003)
Model 5
(N=2003)
5.614
4.527
4.989
4.576
4.973
(11.558)***
(9.232)***
(10.105)***
(9.284)***
(9.861)***
0.306
0.306
0.307
0.312
0.315
(2.841)***
(2.843)***
(2.821)***
(2.898)***
(2.934)***
-0.278
-0.268
-0.262
-0.268
-0.271
(-10.284)***
(-9.779)***
(-9.474)***
(-9.776)***
(-9.900)***
0.554
0.523
0.389
(7.372)***
(6.413)***
(4.330)***
-0.013
-0.004
0.002
(-3.725)***
(-0.961)
(0.531)
-0.522
-0.813
-0.385
-0.136
(-0.902)
(-1.361)
(-0.647)
(-0.228)
0.432
0.100
0.471
0.678
(1.515)
(0.350)
(1.635)
(2.313)**
0.001
0.006
0.002
0.006
0.005
(0.422)
(1.910)*
(0.852)
(2.023)**
(1.757)*
0.071
0.030
-0.236
0.017
0.106
(0.078)
(0.033)
(-0.258)
(0.019)
(0.117)
BM
ROE
FCF
Cash
Debt deviation
Stock option
INVO
D(Takeover)
CGI
Dividend Payout
Yearly Fixed effect
2
Adjusted R
-0.333
-0.235
(-7.323)***
(-3.506)***
0.413
0.481
0.424
0.473
0.451
(1.953)*
(2.269)**
(1.983)**
(2.232)**
(2.135)**
0.031
0.025
0.039
0.026
0.024
(1.453)
(1.168)
(1.826)*
(1.199)
(1.104)
0.006
0.002
0.010
0.003
0.002
(0.365)
(0.133)
(0.577)
(0.179)
(0.135)
yes
yes
yes
yes
yes
0.106
0.109
0.090
0.109
0.114
54
Table 6: Execution of Repurchase and Managerial Overconfidence
This table reports the regression of percentage of execution of share repurchase on managerial
overconfidence. The dependent variable is the percentage of execution of share repurchase program. The
independent variable, MOC, and other variables are defined in table 2. In each cell the regression
coefficient and z-statistics in parentheses are reported in the upper and lower case, respectively. ***, **,
and * denote the significance level of 1%, 5%, and 10%, respectively.
Intercept
MOC
Size
Model 1
(N=2003)
Model 2
(N=2003)
Model 3
(N=2003)
Model 4
(N=2003)
Model 5
(N=2003)
80.032
74.332
74.625
76.005
86.450
(7.181)***
(6.631)***
(6.694)***
(6.748)***
(7.439)***
6.208
6.130
6.290
6.372
6.139
(2.512)**
(2.491)**
(2.554)**
(2.585)***
(2.480)**
-0.673
-0.453
-0.531
-0.450
-0.660
(-1.085)
(-0.724)
(-0.852)
(-0.721)
(-1.048)
-1.400
-2.457
-5.171
(-0.810)
(-1.310)
(-2.496)**
-0.101
-0.121
0.012
(-1.314)
(-1.450)
(0.125)
-19.860
-13.582
-15.107
-6.704
(-1.509)
(-1.008)
(-1.115)
(-0.488)
-9.447
-5.972
-8.170
-3.103
(-1.457)
(-0.934)
(-1.249)
(-0.459)
0.024
-0.014
0.022
-0.002
-0.018
(0.389)
(-0.215)
(0.328)
(-0.024)
(-0.264)
35.275
33.383
34.483
33.041
34.211
(1.690)*
(1.595)
(1.646)*
(1.580)
(1.639)
BM
ROE
FCF
Cash
Debt deviation
Stock option
INVO
D(Takeover)
CGI
Dividend Payout
Yearly Fixed effect
2
Adjusted R
-3.138
-4.944
(-3.015)***
(-3.197)***
-12.397
-12.101
-12.066
-12.355
-12.770
(-2.551)**
(-2.477)**
(-2.464)**
(-2.529)**
(-2.621)***
-0.377
-0.276
-0.237
-0.249
-0.283
(-0.766)
(-0.559)
(-0.483)
(-0.504)
(-0.573)
0.635
0.662
0.639
0.690
0.673
(1.642)
(1.704)*
(1.643)
(1.775)*
(1.739)*
yes
yes
yes
yes
yes
0.018
0.016
0.016
0.016
0.019
55
Table 7: Number of Repurchases and Managerial Overconfidence
This table reports the regression of the number of share repurchase programs on managerial
overconfidence. The dependent variable is the natural logarithm of the number of share repurchases
programs. The independent variable, MOC, and other variables are defined in table 2. In each cell the
regression coefficient and z-statistics in parentheses are reported in the upper and lower case, respectively.
***, **, and * denote the significance level of 1%, 5%, and 10%, respectively.
Intercept
MOC
Size
Model 1
(N=2004)
Model 2
(N=2025)
Model 3
(N=2038)
Model 4
(N=2025)
Model 5
(N=2004)
-0.939
-1.702
-1.418
-1.524
-1.115
(-3.256) ***
(-5.802) ***
(-4.899) ***
(-5.223) ***
(-3.693) ***
0.048
0.046
0.074
0.071
0.067
(0.744)
(0.706)
(1.141)
(1.099)
(1.037)
-0.174
-0.182
-0.187
-0.182
-0.177
(-10.895) ***
(-11.128) ***
(-11.521) ***
(-11.251) ***
(-10.898) ***
0.300
0.188
0.064
(6.619) ***
(3.863) ***
(1.167)
-0.016
-0.013
-0.008
(-7.986) ***
(-5.886) ***
(-3.358) ***
-1.154
-0.821
-0.664
-0.428
(-3.293) ***
(-2.308) **
(-1.862) *
(-1.191)
-0.231
-0.252
-0.097
0.008
(-1.358)
(-1.513)
(-0.573)
(-0.045)
-0.011
-0.01
-0.01
-0.009
-0.01
(-6.886) ***
(-5.827) ***
(-5.924) ***
(-5.065) ***
(-5.537) ***
-0.511
-0.522
-0.635
-0.568
-0.529
(-0.926)
(-0.943)
(-1.147)
(-1.032)
(-0.963)
BM
ROE
FCF
Cash
Debt deviation
Stock option
INVO
D(Takeover)
CGI
Dividend Payout
Yearly Fixed effect
2
Adjusted R
-0.33
-0.208
(-11.044) ***
(-4.717) ***
-0.49
-0.417
-0.465
-0.447
-0.468
(-3.862) ***
(-3.247) ***
(-3.630) ***
(-3.504) ***
(-3.693) ***
-0.013
-0.016
-0.008
-0.013
-0.012
(-1.022)
(-1.244)
(-0.589)
(-1.014)
(-0.921)
0.008
0.006
0.012
0.009
0.008
(0.787)
(0.619)
(1.175)
(0.906)
(0.842)
yes
yes
yes
Yes
yes
0.267
0.248
0.261
0.264
0.273
56
Table 8: Price Difference and Managerial Overconfidence
This table reports the regression of the price difference on managerial overconfidence. The dependent
variable (the price difference) and the independent variable (MOC) and other variables are defined in
table 2. In each cell the regression coefficient and z-statistics in parentheses are reported in the upper
and lower case, respectively. ***, **, and * denote the significance level of 1%, 5%, and 10%,
respectively.
Intercept
MOC
Size
Model 1
(N=1642)
Model 2
(N=1649)
Model 3
(N=1656)
Model 4
(N=1649)
Model 5
(N=1642)
0.452
0.554
0.541
0.556
0.466
(4.103)***
(4.953)***
(4.873)***
(4.953)***
(4.051)***
0.049
0.051
0.049
0.052
0.049
(2.005)**
(2.118)**
(2.012)**
(2.125)**
(2.016)**
-0.005
-0.009
-0.009
-0.009
-0.007
(-0.880)
(-1.453)
(-1.392)
(-1.446)
(-1.158)
-0.008
-0.010
0.014
(-0.486)
(-0.529)
(0.692)
0.000
0.000
-0.001
(-0.169)
(-0.211)
(-1.280)
0.135
0.156
0.142
0.048
(1.031)
(1.173)
(1.051)
(0.354)
-0.078
-0.067
-0.075
-0.108
(-1.208)
(-1.053)
(-1.158)
(-1.623)
0.002
0.002
0.002
0.002
0.002
(3.541)***
(3.023)***
(3.221)***
(3.021)***
(3.245)***
0.164
0.188
0.194
0.187
0.177
(0.845)
(0.965)
(1.001)
(0.963)
(0.912)
BM
ROE
FCF
Cash
Debt deviation
Stock option
INVO
D(Takeover)
CGI
Dividend Payout
Yearly Fixed effect
2
Adjusted R
0.021
0.043
(2.011)**
(2.857)***
0.100
0.099
0.099
0.099
0.102
(2.083)**
(2.050)**
(2.058)**
(2.042)**
(2.120)**
-0.005
-0.005
-0.005
-0.005
-0.004
(-0.940)
(-1.000)
(-0.983)
(-0.988)
(-0.914)
-0.012
-0.012
-0.012
-0.012
-0.011
(-1.731)*
(-1.683)*
(-1.676)*
(-1.662)*
(-1.563)
yes
yes
yes
yes
yes
0.197
0.195
0.194
0.194
0.198
Table 9: Announcement Returns and Managerial Overconfidence
This table reports the regressions of the abnormal returns of repurchase announcements in different
57
windows (CAR) on managerial overconfidence (MOC) and other control variables. In each cell the
regression coefficient and t-statistics in parentheses are reported in the upper and lower case, respectively.
***, **, and * denote the significance level of 1%, 5%, and 10%, respectively.
Intercept
MOC
Ln(No.)
Size
BM
ROE
FCF
Cash
Debt
Option
INVO
Takeover
CGI
Payout
2
Adjusted R
CAR(-1,1)
CAR(-5,5)
CAR(0,20)
CAR(0,40)
CAR(0,60)
(N=1937)
(N=1937)
(N=1937)
(N=1937)
(N=1937)
6.039
8.489
13.920
13.753
.419
(2.700)***
(2.205)**
(2.806)***
(1.877)*
(.043)
.350
.563
-1.313
-4.460
-5.155
(.712)
(.665)
(-1.204)
(-2.769)***
(-2.422)**
-.796
-1.321
-.257
-1.074
-1.147
(-3.894)***
(-3.756)***
(-.567)
(-1.604)
(-1.296)
-.286
-.619
-.703
-.641
.033
(-2.249)**
(-2.828)***
(-2.491)**
(-1.537)
(.060)
.822
2.440
2.263
4.123
5.639
(2.104)**
(3.629)***
(2.613)***
(3.222)***
(3.335)***
-.012
-.050
-.081
-.079
-.117
(-.644)
(-1.573)
(-1.989)**
(-1.323)
(-1.470)
2.027
9.991
4.338
24.643
35.963
(.753)
(2.155)**
(.726)
(2.793)***
(3.084)***
.929
5.738
4.145
9.899
15.959
(.695)
(2.494)**
(1.398)
(2.260)**
(2.758)***
-.038
-.065
-.034
-.059
-.063
(-2.816)***
(-2.770)***
(-1.146)
(-1.320)
(-1.078)
-5.770
-5.656
-.158
-11.490
-18.908
(-1.411)
(-.804)
(-.017)
(-.858)
(-1.068)
-.343
-1.510
-.700
-2.674
-2.675
(-1.126)
(-2.878)***
(-1.035)
(-2.678)***
(-2.028)**
-2.851
-3.767
-5.364
-5.110
-7.482
(-2.924)***
(-2.245)**
(-2.481)**
(-1.600)
(-1.773)*
-.057
.083
.234
.495
.736
(-.699)
(.590)
(1.284)
(1.839)*
(2.068)**
.062
.094
.211
.434
.449
(.810)
(.714)
(1.242)
(1.726)*
(1.350)
.024
.052
.027
.043
.037
58
Table 10: Summary of Regression Ceofficients
This table summarizes the regression coefficients of managerial overconfidence and attributes of share
reputchase including the natural logarithm of number of repurchases, the percentage of shares repurchases,
the percentage of amount repurchase, and the percentage of execution. The other control variables are
identical to those in Table 9 and are not reported for brevity. In each cell the regression coefficient and
t-statistics in parentheses are reported in the upper and lower case, respectively. ***, **, and * denote the
significance level of 1%, 5%, and 10%, respectively.
MOC
Ln(No.)
MOC
% of Shares
MOC
% of Amount
MOC
% of Execution
CAR(-1,1)
CAR(-5,5)
CAR(0,20)
CAR(0,40)
CAR(0,60)
(N=1937)
(N=1937)
(N=1937)
(N=1937)
(N=1937)
.350
.563
-1.313
-4.460
-5.155
(.712)
(.665)
(-1.204)
(-2.769)***
(-2.422)**
-.796
-1.321
-.257
-1.074
-1.147
(-3.894)***
(-3.756)***
(-.567)
(-1.604)
(-1.296)
.118
.112
-1.348
-4.668
-5.338
(.240)
(.133)
(-1.243)
(-2.913)***
(-2.525)**
.228
.580
-.212
-.575
-1.265
(2.277)**
(3.375)***
(-.959)
(-1.758)**
(-2.933)***
.090
.023
-1.340
-4.597
-5.190
(.183)
(.027)
(-1.235)
(-2.870)***
(-2.460)**
.336
.955
-.214
-.848
-1.824
(3.248)***
(5.384)***
(-.933)
(-2.507)**
(-4.090)***
.176
.255
-1.018
-4.242
-4.852
(.359)
(.301)
(-.950)
(-2.674)***
(-2.315)**
-.005
-.012
-.072
-.101
-.133
(-1.129)
(-1.498)
(-7.137)***
(-6.803)***
(-6.756)***
59
Table 11: Exogenous Overconfidence and Share Repurchase
This table reports the tobit regression of the variables of interest (% of shares repurchased, % of amount
of repurchased, % of execution, and the natural logarithm of times of repurchases, price difference) on
exogenous overconfidence which is defined as the residual term of the following regression: MOCi,t =β0+
β1 SIZE i,t + β2 ROEi,t + β3 BMi,t + β4FCFi,t+ εi. In each cell the regression coefficient and t-statistics in
parentheses are reported in the upper and lower case, respectively. ***, **, and * denote the significance
level of 1%, 5%, and 10%, respectively.
Intercept
Residual (MOC)
Cash
Debt deviation
Stock option
INVO
D (takeover)
CGI
Dividend payout
Yearly Fixed effect
Adjusted R2
% Shares Rep.
% Amt. Rep.
% Execution
Ln(times)
PD
(N=2003)
(N=2003)
(N=2003)
(N=2004)
(N=1642)
1.531
1.012
71.297
2.048
0.383
(8.772)***
(6.146)***
(19.297) ***
(20.314)***
(10.662)***
0.233
0.320
5.868
0.080
0.051
(1.989)**
(2.904)***
(2.369) **
(1.194)
(2.080)**
1.463
1.016
-0.320
-0.393
-0.104
(4.700) ***
(3.460)***
(-0.049)
(-2.226)**
(-1.597)
0.009
0.004
0.029
-0.012
0.002
(2.907) ***
(1.432)
(0.444)
(-7.139)***
(3.090)***
0.244
0.070
35.590
-0.562
0.180
(0.247)
(0.075)
(1.703) *
(-0.981)
(0.929)
-0.255
-0.353
-2.772
-0.329
0.031
(-4.736) ***
(-6.954)***
(-2.432) **
(-9.767)***
(2.747)***
-0.044
0.128
-12.975
-0.311
0.094
(-0.192)
(0.595)
(-2.693) ***
(-2.395)**
(1.989)*
0.076
0.084
-0.248
-0.047
-0.003
(3.390) ***
(3.933)***
(-0.519)
(-3.701)***
(-0.668)
0.007
0.010
0.647
0.005
-0.011
(0.406)
(0.581)
(1.672) *
(0.499)
(-1.648)*
yes
yes
yes
yes
yes
0.021
0.063
0.017
0.215
0.198
60