Firm size, timing, and earnings management of seasoned equity offerings

Firm size, timing, and earnings management of seasoned
equity offerings
Pei-Gi Shu, Sue-Jane Chiang
⁎
Department of Business Administration, Fu Jen Catholic University, Taiwan
article info abstract
Article history:
Received 28 April 2012
Received in revised form 18 March 2013
Accepted 8 May 2013
Available online xxxx
Rangan (1998),andTeoh, Wong, and Rao (1998) maintain that the short-term overperformance
and long-term underperformance of seasoned equity offerings (SEOs) are due to earnings
management, whereas Loughran and Ritter (1997), Baker and Wurgler (2002) and Cohen,
Papadaki, and Siougle (2007) attribute them to the timing of share placement by issuing firms.
The present authors propose that large and small firms treat their seasoned equity differently:
small firms time the market, whereas large firms use discretionary accruals to increase their
proceeds. We verify this hypothesis using a sample of 463 firms listed on the Taiwan stock
exchange. Specifically, for small firms, the timing effect is positively correlated with the firm's
short-term wealth and negatively correlated with its long-term wealth. For large firms, earnings
management (proxied as discretionary accruals gauged by the modified Jone's model) is
positively correlated with short-term wealth and negatively correlated with long-term wealth.
The separating equilibrium is unlikely to be conditioned by the issuing firm's flotation methods.
© 2013 Elsevier Inc. All rights reserved.
Keywords:
Firm size
Timing
Earnings management
SEOs
1. Introduction
Much academic attention has been attracted to the well-documented short-term overperformance (e.g., Asquith & Mullins,

1986; Korajczyk, Lucas, & McDonald, 1990) and long-term underperformance (e.g., Kang, Kim, & Stulz, 1999; Levis, 1995;
Loughran & Ritter, 1995, 1997; Mohan & Chen, 2001; Spiess & Affleck-Graves, 1995) of initial public offerings and seasoned equity
offerings (SEOs). Brous, Datar, and Kini (2001) and Denis and Sarin (2001) hypothesize that the long-term underperformance
arises from and therefore is employed to undo investors' overly optimistic expectations of the future performance of the issuing
firms. Why would investors have these overly optimistic expectations? Numerous studies based on information asymmetry
theory or agency theory suggest that the expectations are attributable to (a) the issuing firm's flotation methods (e.g., Eckbo &
Masulis, 1992; Slovin, Sushka, & Lai, 2000; Wang, Chen, & Huang, 2008), (b) their timing of share issuance, and (c) their degree of
earnings management. In this study, we focus on (b) and (c), which have been relatively unexplored in the literature.
By “timing,” we refer to when shares are offered to the public in the market. It has been established that this generally occurs
when the market is “hot” or investor sentiment is strongly positive (e.g., Asquith & Mullins, 1986; Baker & Wurgler, 2002;
Loughran & Ritter, 1995, 1997; Masulis & Korwar, 1986). For example, Cohen et al. (2007) find that firms that place SEOs
(hereafter SEO firms) purposely do so when the market is hot, which explains their long-term underperformance. Overly
optimistic investor sentiment can also result in short-term overvaluation of seasoned shares. For example, Brown and Cliff (2004)
find that prices are high when short-term investor sentiment is strongly positive. In other words, the stronger the positive
sentiment, the lower the long-term performance of the SEO firm is (Baker & Wurgler, 2006; Deng, Hrnjic, & Ong, 2012). This
timing argument has become one of the most prominent theoretical explanations for the anomaly associated with SEOs.
International Review of Economics and Finance xxx (2013) xxx–xxx
⁎ Corresponding author at: Department of Business Administration, Fu Jen Catholic University, New Taipei City, Taiwan. Tel.: +886 2 29053935.
E-mail address: (S J. Chiang).
REVECO-00832; No of Pages 18
1059-0560/$ – see front matter © 2013 Elsevier Inc. All rights reserved.
/>Contents lists available at SciVerse ScienceDirect
International Review of Economics and Finance
journal homepage: www.elsevier.com/locate/iref
Please cite this article as: Shu, P G., & Chiang, S J., Firm size, timing, and earnings management of seasoned equity offerings,
International Review of Economics and Finance (2013), />On the other hand, according to the earnings management hypothesis, issuing firms have an incentive to manage earnings
upwardly if the market fails to understand that the boosted earnings are only transitory. In the following periods, when the
earnings become losses, the market revises the valuation of the shares downward. This hypothesis, which is widely supported by
prior studies (e.g. Rangan, 1998; Teoh et al., 1998), predicts that issuers make unusually high pre-issue, income-increasing
accounting adjustments, as a result of which post-issue earnings and stock return performance are unusually poor. Nonetheless,

whether earnings management actually raises share prices is unclear. Shivakumar (2000) argues that investors are rational
enough to reduce the inflated values. Therefore, firms do not use earnings management to mislead investors but rather to undo
their discounting of the shares.
Shivakumar's (2000) argument is based on the premise that investors do not discount the inflated numbers equally, because
the issuers cannot credibly signal the absence of earnings management. However, this premise fails to explain why some firms
engage in earnings management more than others when placing their seasoned shares. Do issuing firms discount their shares
differently depending on how informative they find the firm's reported numbers, that is, how helpful the issuing firms find the
numbers for predicting the firm's future prospects? We therefore hypothesize that differences in the degree of earnings
management depend on differences in the investor's discounting or the information value of the reported earnings.
As the SEO anomaly remains an open issue, we include firm size in our model. By doing so, we hope to contrast the
mechanisms used by different firms. The extensively-studied firm-size effect is found to be negatively correlated with returns for
both nonfinancial firms (Fama & French, 1992, 2008; Lin & Wu, 2013; Pontiff & Woodgate, 2008) and financial firms (Barber &
Lyon, 1997) in different countries (e.g., Chan, Hamao, & Lakonishok, 1991) and in different time periods ( Davis, 1994). We relate
firm size to the SEO anomaly because small issuing firms are found to have much more negative long-term performance than
their larger counterparts (e.g., Brav, Geczy, & Gompers, 2000; Farinós, García, & Ibáñez, 2007; Loughran & Ritter, 1997). This
finding inspires us to investigate whether the firm-size effect for SEO firms is attributable to large and small issuing firms placing
their seasoned equity differently.
Using firm size as a predictor, our empirical results from 463 firms listed in the Taiwan stock market indicate that large issuing
firms tended to use earnings management, whereas small issuing firms tended to time the market in placing their seasoned
equity shares. For large firms, discretionary accruals, which serve as the proxy for earnings management, are positively correlated
with the short-term announcement effect and negatively correlated with the ex-post wealth effect. For small firms, the timing
dummy is positively correlated with the short-term announcement effect and negatively correlated with the ex-post wealth
effect. These results imply a separating equilibrium for the different approaches adopted by the different firms. A further question
is why this is the case and not the reverse. We find that the reported earnings predict the ex-post wealth effect for large firms but
not for small firms. This result provides a plausible explanation for why large firms engage in earnings management more than
small firms.
In addition to market timing and earnings management, the flotation method an issuing firm uses is commonly referred to as
having an impact on the SEO anomaly. A question might arise about whether the separating equilibrium found in the present
study is in fact conditioned by the flotation method a firm chooses.
1

For example, the timing argument is not applicable to cases in
which the existing shareholders do not renounce their pre-emption rights. Under such circumstances, the issuing firm has no
incentive to time the market if the existing shareholders subscribe for the new shares in proportion to their ownership stake at
the time of issuance. This possibility, if true, would jeopardize our interpretation of the findings that large issuing firms employ
earnings management and small issuing firms employ market timing.
However, we argue that our finding is less likely to be preconditioned by the flotation method adopted by issuing firms. Firstly,
from the perspective of information asymmetry, the adoption of a rights offer implies that the existing shareholders are willing to
subscribe for the new issued shares on a pro rata basis; this sends a positive signal to outside investors that the proceeds collected
from the issuance are being channeled to profitable investments (e.g., Eckbo, 1995; Eckbo & Masulis, 1992). Agency theory
focuses on whether the flotation method could additionally involve large-block shareholders, as this would improve the
management of the issuing firm (Demsetz, 1986; Pound, 1988; Shleifer & Vishny, 1986). Such improvement implies that the
announcement effect, when it involves block investors, is positive. However, block shareholders are less likely to invest if the offer
involves rights than if it involves bookbuilding (e.g., Aggarwal, Prabhala, & Puri, 2002; Hanley & Wilhelm, 1995; Wang et al.,
2008), private placement (e.g., Wruck, 1989; Wu, 2004), or public placement (e.g., Slovin et al., 2000).
Secondly, the two flotation methods adopted in Taiwan are fixed-price offers and bookbuilding offers. However, these are not
directly relevant to the aforementioned cases. With a fixed-price offer, the existing shareholders retain their pre-emption rights.
(In this respect, it is similar to a rights offer). With a bookbuilding offer, the shareholders renounce their pre-emption rights. (In
this respect, it is similar to public placing). However, the law in Taiwan stipulates that at least 10% of new shares must be placed
with outside investors. That is, outside investors are involved whichever flotation method is used. Moreover, our statistics show
that the proportion of small issuing firms that choose the bookbuilding approach (13%) does not differ significantly from the
proportion of large issuing firms that choose it (14%). This result implies that choice of flotation method is not predicted by firm
size. Therefore, based on both theoretical inference and the kinds of flotation methods adopted in Taiwan, we postulate that our
results are less likely to be dictated by the specific flotation method chosen by an issuing firm.
Using three valuation models, Jindra (2000) finds that overvaluation is commonly found in SEOs. Insiders who know that
seasoned shares are overvalued tend to engage in arbitrage. Moreover, Jindra (2000) finds earnings management to be positively
1
Using data from Hong Kong SEOs, Ching, Firth, and Rui (2006) find that the average announcement effect is positive for private placements and negative for
rights offers. Firms that adopt either method suffer inferior long-term performance.
2 P G. Shu, S J. Chiang / International Review of Economics and Finance xxx (2013) xxx–xxx
Please cite this article as: Shu, P G., & Chiang, S J., Firm size, timing, and earnings management of seasoned equity offerings,

International Review of Economics and Finance (2013), />associated with overvaluation
2
of seasoned shares, although he does not address the long-term performance of seasoned shares.
Using Taiwanese SEO data from 1996 to 2008, Wang et al. (2008) find that the positive announcement effect of bookbuilding
offers is due to the introduction of block shareholders, who enhance the governance quality of the issuing firms; in contrast, they
find the announcement effect for fixed-price offers to be negative. Again, these authors cover only the short-term announcement,
not the long-term performance of the issuing firms.
The potential contribution of this study is our identification of the separating equilibrium for large and small issuing firms
when they place their seasoned shares. Even though earnings management and timing effects have been widely documented in
prior studies, to the best of our knowledge none of them has explored the coupling between large firms and earnings
management and between small firms and timing. We suggest that the information value of the reported earnings might offer a
clue to explaining the differences in the use of these mechanisms.
The rest of this paper is organized as follows. In Section 2 we discuss the SEO’s underwriting methods in Taiwan. In Section 3
we review the literature and develop our hypotheses. In Section 4 we describe our data sources and define the variables. In
Section 5 we report the empirical results. In Section 6 we present our conclusions.
2. Underwriting methods used by SEO firms in Taiwan
Until March 1995, fixed-price offering was the only underwriting method used in Taiwan for seasoned offerings. Since then,
firms have been able to choose between bookbuilding offers and fixed-price offers, depending on whether the existing
shareholders retain their pre-emption rights; these rights are preserved with fixed-price offers but not bookbuilding offers.
Taiwan's Company Law stipulates that at least 10% of the new shares in an SEO have to be publicly sold to outside investors,
and another 10–15% are reserved for employee subscriptions; the latter are intended to align employees' incentives with
shareholders' interest of the SEO firm. Therefore, with a fixed-price offer, the existing shareholders can purchase at most 75–80%
of the newly issued shares, the exact percentage depending on their ownership stake at the time of issuance. The offer price is
negotiated between the issuing firm and the lead underwriter. In case of oversubscription, the excess shares are distributed to the
public by means of a lottery using computer-generated random numbers. In each round of the lottery in Taiwan, each qualified
individual investor can submit purchase orders and is allowed to buy up to 1000 shares. In the case of a fixed-price offer, this
placement via public lottery is supposed to be fair to all participants. However, the price discrepancy between the offered price
and the last secondary market price provides arbitrage opportunities
3
that encourage sophisticated investors to borrow token

accounts to increase their odds of winning the lottery. In 1997, the government imposed several changes in the regulations to
mitigate this token investor problem.
4
The fixed-price offer in Taiwan is similar but not directly parallel to the rights offer in the U.K. First, as noted above, Taiwanese
regulations require that at least 10% of the newly issued shares must be sold to outside investors and another 10–15% made
available for employee subscription. We therefore consider the fixed-price offer to be a partial rights offer, because at least 10% of
the new shares are purchased by outside investors. This is not the case for the rights offer, which is used by most countries except
the U.S. In the U.K., for example, the rights offer allows existing shareholders to buy up to 100% of the newly issued shares
depending on their ownership stake. These pre-emption rights are renounceable, so outside investors can purchase them from
the market and then use them to buy new shares at the subscription price. Therefore, the total cost of one new share for an
outside investor is the sum of the subscription price per share and the market price of the pre-emption right. In Taiwan, when a
fixed-price offer is adopted, the pre-emption right owned by the existing shareholders is non-renounceable: the investor can
either take up the right or let it lapse. Once a right has elapsed, it no longer exists.
With a bookbuilding offer, the existing shareholders renounce their pre-emption rights at the shareholders' meeting. The
proportion of new shares sold to new investors can be 85–90%. Because numerous shares are sold to the market, the target
investors of a bookbuilding offer are usually qualified institutional investors, each of which is allowed to buy up to 10% of the
newly issued shares.
A feature shared by U.K. private placement, U.S. commitment offers, and Taiwan bookbuilding is that the issuing firm must obtain
the approval of shareholders at a general meeting to avoid a violation of the pre-emption requirements. However, there are several
noteworthy differences among the three. First, with bookbuilding offers in Taiwan, the underwriters and issuing firms negotiate a
possible price range within which outside investors can buy interest. The final offer price is set after review by the lead underwriter
and the issuing firm. Because the shares are sold mainly to institutional investors, the bookbuilding offer usually attracts external
block investors. Unlike their counterparts in the U.S., where the lead underwriters purchase new shares from issuing firms at a
specified price and then sell them mainly to institutional investors to earn their placement fee, underwriters in Taiwan do not
purchase the new shares from the issuing firm in advance. Rather, they bridge the sale of the new shares from the issuing firm to the
outside block investors. Second, in Taiwan, the lead underwriters of bookbuilding offers create an order book, gather information
about the market demand for the offering, and negotiate the final offer price with the issuing firm. In contrast, in the U.S., lead
2
Elliott, Koeter, and Warr (2007) indicate that overvaluation of shares by matching firms implies high growth potential for these firms.
3

SEO shares tend to be greatly underpriced because the underwriting period, the time between the offer-price-settlement day and the last payment day for
successful share allocation, averages 80 days (Chen, Shu, & Chiang, 2011).
4
First, each individual investor can subscribe SEO shares at only one brokerage house. Either duplicate subscription or an insufficient deposit in the brokerage
house's bank account disqualifies the subscription. Moreover, the lottery processing fee paid to underwriters for each subscription is reduced from NT$30 to NT
$17.5.
3P G. Shu, S J. Chiang / International Review of Economics and Finance xxx (2013) xxx–xxx
Please cite this article as: Shu, P G., & Chiang, S J., Firm size, timing, and earnings management of seasoned equity offerings,
International Review of Economics and Finance (2013), />underwriters have no specific information about the market demand for the newly issued shares. Thus, they cannot subsequently
change the value of the proceeds received by the issuing firm (e.g., Barnes & Walker, 2006; Ho, 2005; Slovin et al., 2000). To protect
the existing shareholders' rights, the new shares cannot be discounted by more than 10% of the prevailing market price.
Both the bookbuilding and fixed-price offering approaches provide positive and negative information to outside investors. If a
firm adopts a fixed-price offer, the existing shareholders retain their pre-emption rights when subscribing the new shares, which
send a positive signal to outside investors (e.g., Eckbo, 1995; Eckbo & Masulis, 1992). However, it could be case that existing
shareholders are overly optimistic when subscribing the new shares (e.g., Andrikopoulos, 2009). A bookbuilding offer, on the
other hand, sends a negative signal to existing shareholders, making them reluctant to buy the new shares, which are placed
mainly with block institutional investors. The introduction of these new block shareholders, who, as a result of the change in
ownership structure play an active monitoring role, is deemed a positive signal (Wruck, 1989). Therefore, the short-term and
long-term effects associated with SEO firms are not necessarily dictated by their flotation approaches, because both approaches
send positive or negative signals to outside investors.
3. Literature and hypotheses
3.1. Earnings management, SEO anomalies, and firm size
Most managers use accounting accruals to conceal poor performance, postpone a portion of unusually good earnings to future
years (DeAngelo, 1988; DeAngelo, DeAngelo, & Skinner, 1994; Perry & Williams, 1994; Warfield, Wild, & Wild, 1995), and release
value-relevant information (Francis, Maydew, & Sparks, 1999; Healy & Palepu, 1993).
It seems intuitively desirable to relate the use of discretionary accounting choices to SEOs, because a firm's profitability influences
the success of its issues. Prior studies indicate that firms tend to opportunistically manipulate earnings upward before placing their
SEOs. However, the accruals used to boost these earnings tend to reverse in latter reporting periods (Dechow, Sloan, & Hutton, 1996;
Rangan, 1998; Teoh et al., 1998). Furthermore, Marquardt and Wiedman (2004) show that when such SEO firms engage in earnings
management, they prefer to accelerate the recognition of their revenues or to defer the recognition of their expenses.

If investors cannot see through these accounting practices, they will be induced to buy the seasoned stocks at higher prices.
However, Shivakumar (2000) argues that because issuers cannot credibly signal the absence of earnings management, investors
treat all firms as having overstated prior earnings when they announce an offering. As a result, they discount their stock prices.
This average price drop at the time SEOs are announced is consistent with this investor-conditioning process.
If the processes described above actually occur, why would issuing firms engage in earning management when investors undo
its effects at the time the offer is announced? Shivakumar (2000) suggests that earnings management prior to equity offerings is
not used to mislead investors, but instead it is a rational response to anticipated market behavior at the time the offering is
announced; the issuers overstate the earnings, at least to the extent expected by the market.
However, Shivakumar's argument fails to explain why some firms engage more in earnings management than others. We
argue that the motive for SEO firms to engage in earnings management is based on whether the boosted earnings provide
sufficient information to predict the firm's growth. If they are, it is more likely that investors will take the reported numbers at
face value, which in turns motivates the firms to engage in a large degree of earnings management. If the issuing firm does so,
investors are in a better position to evaluate whether the firm's earnings report has reference value.
We postulate that the earnings reported by large issuing firms have higher reference value than those reported by small
issuing firms. This argument is based on the following rationale. First, large firms tend to be associated with more prestigious
accounting firms and/or underwriters than small firms. Because of the good reputations of these financial intermediaries, the
firms' reported earnings are more credible and informative. Second, large firms are more likely than small firms to have a stable
stream of earnings. This stability implies that the reported earnings are good predictors of the issuing firm's growth prospects.
Third, large firms are more likely than small firms to keep records of their SEOs, which gives investors greater confidence in the
reported earnings. Because these reported earnings have reference value, large SEO issuing firms are motivated to engage in
earnings management practices aimed at increasing their proceeds from the equity issues.
Hypothesis 1. When placing their seasoned shares, large firms are more likely than small firms to engage in a large degree of
earnings management.
3.2. Timing, SEO anomalies, and firm size
Loughran and Ritter (1995, 1997), Spiess and Affleck-Graves (1995), and Baker and Wurgler (2002) argue that firms tend to
issue equity and take advantage of the opportunistic time window to improve their poor financial performance when their equity
is substantially overvalued. Graham and Harvey (2001) suggest that managers are concerned about the appropriate timing of
issuing equity. Eckbo, Masulis, and Norli (2007) indicate that the facts concerning SEOs' stock price dynamics prove that firms
engage in managerial timing of these issues during the brief periods when they are overvalued.
This market timing hypothesis suggests that managers have an incentive to time the market so they can sell newly issued

shares at the highest price possible. Research by Cohen et al. (2007) supports the timing hypothesis. These authors find that the
market trend prior to the issuance of SEOs is the only variable that significantly explains post-SEO returns. There is no significant
4 P G. Shu, S J. Chiang / International Review of Economics and Finance xxx (2013) xxx–xxx
Please cite this article as: Shu, P G., & Chiang, S J., Firm size, timing, and earnings management of seasoned equity offerings,
International Review of Economics and Finance (2013), />relationship between discretionary accruals and post-issue stock returns. Greenwood and Hanson (2012) show that firms tend to
issue equity prior to periods when other stocks with similar characteristics are performing poorly.
We assume that issuing firms prefer earnings management to timing. This assumption is based on the following. First, if the
accounting numbers are assumed by the market to be credit-worthy, issuing firms can reap larger proceeds by selling the new
shares at a higher price. Second, issuing firms that use earnings management are not constrained by time, meaning that they can
place their SEOs whenever they wish. This is not the case for firms that don't use earnings management.
If earnings management is considered preferable by issuing firms, why don't they all employ it? Specifically, why does
earnings management tend to be eschewed by small firms? The reason is that, unlike large firms, small firms lack the traceable
records that would make their reported earnings informative. Moreover, because small firms tend to be in the growth stage of
their lifecycle, their earnings tend to be volatile, which further reduces the reference value of their reported earnings.
Alternatively, from the perspective of market demand, earnings management by small issuing firms is less likely to be accepted by
the market than earnings management by large issuing firms; this means that in the small firm case, investors are relatively
unable to predict the short-term and long-term performance of SEO firms. We therefore postulate that small firms tend to time
the market if earnings management is not accessible to them.
Hypothesis 2. When placing their seasoned shares, small firms are more likely than large firms to time the market.
4. Sample and variables
4.1. The sample
We collect our sample of SEO firms in the 1996–2010 period from the Taiwan Economic Journal (TEJ), published by a data
company in Taiwan. To accurately gauge earnings management by discretionary accruals, we require that there be at least 5 years
of accounting data in the quarterly TEJ database for each firm in the sample. We exclude utilities and financial companies, owing
Table 1
Sample distribution. The sample of 463 non-financial SEOs in 1996–2010 is jointly collected from company prospectus, Taiwan Securities Association, Market
Observation Post System, and Taiwan Economic Journal (a database company in Taiwan). Panel A summarizes the sample distribution by yearly breakdown. Panel
B summarizes the distribution by industry breakdown.
Panel A: Yearly breakdown
Year Fixed price Bookbuilding Total No. (%)

1996 55 3 58 12.52
1997 90 18 108 23.32
1998 53 12 65 14.03
1999 31 2 33 7.13
2000 10 3 13 2.81
2001 3 0 3 0.65
2002 19 2 21 4.54
2003 8 3 11 2.38
2004 11 2 13 2.81
2005 15 2 17 3.67
2006 13 3 16 3.46
2007 25 6 31 6.7
2008 9 0 9 1.94
2009 24 5 29 6.26
2010 34 2 36 7.78
Total 400 63 463 100.00
Panel B: Industry breakdown
Industry No. (%) Industry No. (%)
Cement 3 (0.65) Semiconductor 41 (8.86)
Foods 18 (3.89) Computer and peripherals 29 (6.26)
Plastic 9 (1.94) Optoelectronics 44 (9.5)
Fiber and textile 31 (6.7) Communication 8 (1.73)
Electronic machinery 20 (4.32) Electronic components 37 (7.99)
Electronic appliance and cable 9 (1.94) Information service 14 (3.02)
Chemistry 9 (1.94) Other electronics 20 (4.32)
Biotechnology 8 (1.73) Construction 45 (9.72)
Glass and ceramics 5 (1.08) Transportation 15 (3.24)
Papers 2 (0.43) Tourism 2 (0.43)
Iron 54 (11.68) Trade and merchandise 10 (2.16)
Rubber 2 (0.43) Utilities 2 (0.43)

Automobile 2 (0.43) Others 24 (5.18)
Total 463 (100)
5P G. Shu, S J. Chiang / International Review of Economics and Finance xxx (2013) xxx–xxx
Please cite this article as: Shu, P G., & Chiang, S J., Firm size, timing, and earnings management of seasoned equity offerings,
International Review of Economics and Finance (2013), />to the high degree of regulation imposed on these firms, which could limit their ability to engage in earnings management.
Delisted firms and firms suspended from trading are also excluded. The final sample comprises 463 SEOs.
The sample distribution summarized in Table 1 is not balanced, because there are more fixed-price offers (400) than
bookbuilding offers (63).
5
The yearly breakdown in Panel A indicates no obvious clustering pattern in the sampling years. The
industry breakdown in Panel B shows that the top three SEO industries are iron (54; 11.68%), construction (45; 9.72%), and
optoelectronics (44; 9.5%).
4.2. Hot markets and earnings management
The first variable of interest we call the “hot-market period” defined by Ibbotson and Jaffe (1975) and Ritter (1984) as a period
of high new-issue volume and high initial returns. The results in Table 2 show that 1996–1999, 2007, 2009, and 2010 are the
hot-market periods and 2000–2006 and 2008 are the cold-market periods.
6
Following previous research, we use abnormal accruals in the quarters surrounding an equity offering announcement as our
measure of managerial discretion in reported earnings ( DeAngelo, 1986; DeFond & Jiambalvo, 1994; Healy, 1985; Jones, 1991;
Rangan, 1998; Teoh et al., 1998). For our model, we define the estimates of total accruals (AC) as the reciprocals of firm size (1/TA)
and change in sales (△ Sales/TA) as well as plant property and equipment (PPE).
AC
i;t
TA
i;t−1
¼ α
i
1
TA
i;t−1

!
þ β
1i
ΔSales
i;t
TA
i;t−1
!
þ β
2i
PPE
i;t
TA
i;t−1
!
þ ε
i;t
; ð1Þ
Nondiscretionary accruals are gauged by estimated coefficients as follows:
NDAC
i;p
TA
i;p−1
¼
^
α
i
1
TA
i;p−1

!
þ
^
β
1i
ΔSales
i;p
TA
i;p−1
−
ΔREC
i;p
TA
i;p−1
!
þ
^
β
2i
PPE
i;p
TA
i;p−1
!
; ð2Þ
where NDAC represents nondiscretionary accruals and ΔREC is the change in receivables. Discretionary accruals (DAC) are
estimated by subtracting nondiscretionary accruals from total accruals.
DAC
i;p
TA

i;p−1
¼
AC
i;p
TA
i;p−1
!
−
NDAC
i;p
TA
i;p−1
!
; ð3Þ
4.3. Short-term and long-term performance of SEO firms
4.3.1. Announcement effect of SEOs
For announcement effects, we use the two-stage residual technique proposed by Fama, Fisher, Jensen, and Roll (1969) to
measure the change in shareholders' wealth from the day the certificate of the right to place new shares is issued to the payout
day of the stocks. The event day is defined as the day the board meets to announce an SEO. We begin by estimating the coefficients
α and β for the capital assets pricing model (CAPM) from 31 to 120 days before the announcement date:
R
i;t
¼ α
i
þ β
i
R
m;t
þ ε
i;t

; t ¼À120 to À 31; ð4Þ
where R
i,t
is the return of SEO equity i on day t. R
m,t
is the return of the value-weighted TSEC index, a proxy for market return.
Next, an abnormal return is calculated as the difference between the raw return and the expected return derived from the
market model, with the parameters α and β estimated by regressing the underlying firm's raw returns on the market
returns.
AR
i;t
¼ R
i;t
−
⌊
^
α
i
þ
^
β
i
R
m;t
⌋
; t ¼À5to5: ð5Þ
5
As bookbuilding has become the dominant underwriting method in IPOs, why fixed-price offers are more popular than bookbuilding offers in the Taiwan
stock market is puzzling. Chen et al. (2011) extend the wealth-loss measure proposed by Barry (1989) and find that after considering the preemption rights held
by the existing shareholders, the average loss of value of fixed-price offerings is less than that of the bookbuilding offerings.

6
Prior studies utilize different variables besides the combination of issue volume and initial returns to define hot versus cold markets (e.g., Baker, Stein, &
Wurgler, 2003; Baker and Wurgler, 2002; Huang & Ritter, 2009; Loughran & Ritter, 1995). Our results are qualitatively similar regardless of which definition we
use.
6 P G. Shu, S J. Chiang / International Review of Economics and Finance xxx (2013) xxx–xxx
Please cite this article as: Shu, P G., & Chiang, S J., Firm size, timing, and earnings management of seasoned equity offerings,
International Review of Economics and Finance (2013), />We average the abnormal returns of the sample firms for each day in the event window to obtain the daily-average abnormal
return (AAR) and the cumulative average abnormal return (CAR).
AAR tðÞ¼
X
n
i¼1
AR
i;t
n
; t ¼À5to0: ð6Þ
CAR t
1
; t
2
ðÞ¼
X
t
2
t¼t
1
AAR tðÞ; À 5≤t
1
≤t
2

≤0: ð7Þ
We alternatively use the one-week average excess return (CAR(-5, 0)) and the one-day average excess return (CAR(0, 0)) as
the announcement effect measure.
4.3.2. Discounting, initial returns, and overvaluation of SEOs
Discounting (DI), a procedure used to attract investors to subscribe to the issued shares (see Mola & Loughran, 2004), is
defined as follows:
DI ¼ P
T0
−P
T
ðÞ=P
T
; ð8Þ
where P
T
denotes the offer price and P
T0
denotes the close price of issued shares on the price-setting day.
The initial return (IR) is defined as follows:
IR ¼ P
I
−P
T
ðÞ=P
T
; ð9Þ
where P
I
denotes the first close price on the day that the certificates of payment are publicly traded, and P
T

denotes the offer price.
Further, we define overvaluation (OV) as the difference between the initial return and discounting.
OV ¼
P
I
−P
T0
P
T
¼
P
I
−P
T
P
T
−
P
T0
−P
T
P
T
¼ IR−DI: ð10Þ
We also investigate the long-term performance of post-seasoned equity offerings. Based on Ritter (1991), we calculate a
wealth ratio as the investor's buy-and-hold returns 1–5 years post SEO divided by the corresponding market measures.
WR
12n
¼
1 þ

∏
12Ãn
t¼ 1
1 þ r
SEO
s;t

−1

1 þ
∏
12Ãn
t¼1
1 þ r
m;t

−1

; n ¼ 1; 2; 3; 4; 5; ð11Þ
where r
m, t
denotes the return from the market index.
Table 2
Hot versus cold issues. According to Ibbotson and Jaffe (1975) and Ritter (1984), hot issue is defined as markets at periods of high new issue volume and high
level of initial returns (IR). In Table 2 we list the years that are characterized as hot issues versus cold issues based on number of issues and initial returns. The
result shows that the issues in 1996–1999, 2007, 2009, and 2010 are hot issues, and the issues in 2000–2006 and 2008 are cold issues.
Year SEO no. IR (%)
Hot issues
1996 58 56.921
1997 108 36.136

1998 65 21.538
1999 33 46.317
2007 31 23.779
2009 29 27.807
2010 36 19.759
Average 51.4 33.180
Cold issues
2000 13 11.732
2001 3 −3.427
2002 21 14.425
2003 11 18.664
2004 13 9.172
2005 17 12.417
2006 16 23.233
2008 9 −6.039
Average 12.9 10.020
7P G. Shu, S J. Chiang / International Review of Economics and Finance xxx (2013) xxx–xxx
Please cite this article as: Shu, P G., & Chiang, S J., Firm size, timing, and earnings management of seasoned equity offerings,
International Review of Economics and Finance (2013), />4.4. Other control variables
The underwriter's reputation has been found to correlate positively with the market return and performance indicators of IPO
firms (e.g., Carter, Dark, & Singh, 1998; Carter & Manaster, 1990). This variable is represented by a dummy, coded 1 if the lead
underwriter is among the top six underwriters in Taiwan and 0 otherwise. In a similar vein, we include the auditor's reputation
(Michaely & Shaw, 1995), which again is a dummy coded 1 if the auditor is one of the top four accounting firms in Taiwan and 0
otherwise. Finally, the flotation method is represented by a dummy coded 1 for bookbuilding and 0 otherwise.
Ritter (1991) notes that proceeds have been found to be negatively related to initial returns and positively related to
long-term performance. The larger the issuing firm's size, the smaller the information asymmetry between that firm and outside
investors. We therefore include the natural logarithm of firm size and the natural logarithm of proceeds in the model. Moreover,
we use board shareholdings as a proxy for the agency cost. This can also be construed as a proxy for the interest alignment effect,
in the sense that the greater the board's shareholdings, the lower the agency cost associated with this structure.
5. Empirical results

5.1. Descriptive statistics
The summary statistics reported in Table 3 indicate that 78% of the issues in our sampling period are recognized as placed
during a hot market. The value of the average discretionary accrual is only 0.11% of the value of the total assets. The average
announcement effect of an SEO firm is defined as the market-adjusted abnormal return for one day or one week. The mean
(median) one-week return of 0.27% (−0.28%) and the mean (median) one-day return of 0.08% (−0.09%) do not differ
significantly from 0. The mean (median) underpricing of 18.25% (18.21%) is significantly different from 0, indicating that the offer
price tended to be set significantly lower than the close price on the price-setting day. The average initial return of 29.56%
indicates that SEO investors earned handsome profits by subscribing the newly issued shares. The average overvaluation of the
stock is 11.31%, indicating that the price increased from the offer price-setting day to the SEO firm's share-listing day. This
increase can be interpreted as investor overreaction (or over-optimism) leading to short-term overperformance. We note that the
tests of discounting, initial return, and overvaluation against the null hypothesis of 0 are all significant. The tests of the wealth
ratios (WR
12
,WR
24
,WR
36
,WR
48
,WR
60
) against the null of 1 are also all significant, indicating that the SEO firms experienced
prolonged performance deterioration.
The results indicate that 49% (79%) of the SEO firms are associated with the top underwriters (auditors), which the reader will
recall are used as proxies for institutional reputation. On average, the board shareholdings were 24.84% and the EPS was 1.71.
Table 3
Summary statistics. This table reports the summary statistics of variables. Hot issue is a dummy variable that is assigned the value 1 as the markets at periods of
high new issue volume and high level of initial return and 0 otherwise. Earnings management is gauged by the nondiscretionary accruals of the modified Jone's
model proposed by Dechow, Sloan and Sweeney (1995). Announcement effect is alternatively gauged by one-week and one-day market adjusted abnormal
returns on the announcement date, i.e. CAR (−5, 0) and CAR (0, 0), respectively. Discounting is defined as (P

T0
-P
T
)/P
T
, Initial return is defined as (P
I
-P
T
)/P
T
,
Overvaluation is defined as (P
I
-P
T0
)/P
T
, where P
T
, P
T0
and P
I
denote offer price, the close price of issued shares on price setting date and the first close price on the
day that the certificates of payment are publicly traded. Underwriter (auditor) reputation is a dummy that is assigned 1 if the lead underwriter (associated
auditor) is one of the top six underwriters (top four auditors) in Taiwan and 0 otherwise. Underwriter method is 1 if SEO firms adopt bookbuilding and 0
otherwise. WR
12n
denotes n-year market adjusted performance and is defined as: WR

12n
¼ 1 þ
∏
12Ãn
t¼1
1 þ r
SEOs;t

−1

,
1 þ
∏
12Ãn
t¼1
1 þ r
m;t

−1

. Both means
and medians of one-week return, one-day return, discounting, initial return, and overvaluation are tested against with the null hypothesis of 0 and WRs are tested
against with the null hypothesis of 1. ***, **, and * denote the significance levels of 1%, 5%, and 10%, respectively.
Mean Median Min. Max. S.D.
Hot issue 0.78 1.00 0.00 1.00 0.42
Earnings management (%) 0.11 0.05 −1.66 3.24 0.34
One-week return 0.27 −0.28 −19.43 26.69 6.17
One-day return 0.08 − 0.09 −7.06 8.40 2.56
Discounting (%) 18.25*** 18.21*** −19.10 48.95 10.35
Initial return (%) 29.56*** 21.88*** −84.18 667.86 49.46

Overvaluation (%) 11.31*** 4.49*** −85.38 638.57 46.88
WR
12
1.01 0.93*** 0.05 4.03 0.49
WR
24
0.94* 0.76*** 0.04 4.38 0.68
WR
36
0.87*** 0.65*** 0.00 5.65 0.79
WR
48
0.91* 0.63*** 0.01 8.67 0.93
WR
60
0.88*** 0.66*** 0.00 3.74 0.76
Underwriter reputation 0.47 0.00 0.00 1.00 0.50
Auditor reputation 0.79 1.00 0.00 1.00 0.41
Underwriter method 0.14 0.00 0.00 1.00 0.34
Ln (size) 7.00 6.94 5.74 8.63 0.48
Ln (proceeds) 4.55 4.48 3.00 5.90 0.48
Board shareholdings 24.84 21.74 4.69 75.33 13.73
EPS 1.71 1.52 −19.85 19.76 3.39
8 P G. Shu, S J. Chiang / International Review of Economics and Finance xxx (2013) xxx–xxx
Please cite this article as: Shu, P G., & Chiang, S J., Firm size, timing, and earnings management of seasoned equity offerings,
International Review of Economics and Finance (2013), />Table 4
Test in differences. The table reports the tests in differences of variables. In Panel A, the sample is divided based on previous-yearend firm size: large versus small.
In panel B, the sample is divided based on underwriting methods: fixed price versus bookbuilding. In Panel C, the sample is divided based on earnings
management: high versus low EM. In Panel D, the sample is divided based on market condition: cold versus hot market. All variables are defined in Table 3.In
each panel, we report the test in means and in medians against the null of 0 for one-week return, one-day return, discounting, initial return, and overvaluation,

the test in means and medians against the null of 1 for WRs, and the test in differences of means and medians for all variables. ***, **, and * denote the significance
levels of 1%, 5%, and 10%, respectively.
Panel A: Large vs. small firms
Small firms Large firms Difference test
Mean Median Mean Median t-test z-test
Hot issue 0.68 1.00 0.67 1.00 0.196 −0.196
Earnings management (%) 0.08 0.05 0.13 0.06 −1.707* −1.907*
One-week return −0.43 −0.87** 0.97** 0.05 −2.467** −2.308**
One-day return −0.02 −0.03 0.18 −0.10 −0.849 −0.744
Discounting (%) 17.82*** 17.55*** 18.69*** 18.56*** −0.895 −0.751
Initial return (%) 26.74*** 21.88*** 32.41*** 22.32*** −0.527 −0.454
Overvaluation (%) 8.92*** 5.77** 13.72*** 3.81* −1.099 −0.042
WR
12
1.03 0.94** 1.00 0.92*** 0.766 −0.190
WR
24
0.91* 0.73*** 0.97 0.82*** −0.827 −1.337
WR
36
0.82*** 0.57*** 0.92 0.74**** −1.243 −2.406**
WR
48
0.89 0.55*** 0.93 0.72*** −0.351 −2.081**
WR
60
0.85 ** 0.63*** 0.91 0.70*** −0.714 −1.107
Underwriter reputation 0.46 0.00 0.47 0.00 −0.316 −0.316
Auditor reputation 0.76 1.00 0.81 1.00 −1.402 −1.399
Underwriter method 0.13 0.00 0.14 0.00 −0.461 −0.461

Ln (size) 6.63 6.69 7.37 7.27 −26.36*** −18.61***
Ln (proceeds) 4.41 4.40 4.69 4.70 −6.559*** −6.827***
Board shareholdings 24.53 21.49 25.14 22.29 −0.473 −0.154
EPS 1.05 1.21 2.39 2.23 −4.306*** −5.120***
Panel B: Fixed-price offer vs. bookbuilding offer
Fixed-price Bookbuilding Difference test
Mean Median Mean Median t-test z-test
Hot issue 0.78 1.00 0.76 1.00 0.320 −0.321
Earnings management (%) 0.11 0.05 0.08 0.04 0.718 −0.860*
One-week return 0.19 −0.31 0.78 0.00 −0.715 −0.831
One-day return 0.03 −0.10 0.41 0.05 −1.107 −0.766
Discounting (%) 19.55*** 19.76*** 10.02*** 8.81*** 7.151*** −7.441***
Initial return (%) 32.03*** 23.69*** 13.85*** 7.00*** 4.282*** −3.953***
Overvaluation (%) 12.48*** 6.65*** 3.82 −2.63 2.069** −1.812*
WR
12
1.00 0.93*** 1.08 0.93 −0.972 −0.621
WR
24
0.95 0.77*** 0.86* 0.76** 0.877 −0.678
WR
36
0.86*** 0.64*** 0.93 0.75** −0.564 −0.807
WR
48
0.89** 0.65*** 1.05 0.60* −0.868 −0.481
WR
60
0.88*** 0.66*** 0.85 0.66** 0.242 −0.466
Underwriter reputation 0.47 0.00 0.46 0.00 0.106 −0.106

Auditor reputation 0.78 1.00 0.84 1.00 −1.254 −1.146
Ln (size) 6.98 6.92 7.09 6.95 −1.691* −1.512
Ln (proceeds) 4.52 4.48 4.72 4.70 −3.101*** −3.218***
Board shareholdings 25.18 22.56 22.65 18.37 1.363 −1.944**
EPS 1.84 1.60 0.91 0.88 2.035** −2.846**
Panel C: High vs. low earnings management
Low EM High EM Difference test
Mean Median Mean Median t-test z-test
Hot issue 0.81 1.00 0.75 1.00 1.653* −1.650*
One-week return 0.58 −0.23 −0.05 −0.45 1.099 −0.689
One-day return 0.18 0.19 −0.03 −0.29* 0.893 −1.588
Discounting (%) 18.33*** 18.45*** 18.17*** 17.61*** 0.162 −0.134
Initial return (%) 28.55*** 21.25*** 30.56*** 22.51*** −0.436 −1.308
Overvaluation (%) 10.22*** 2.66 12.39*** 7.43*** −0.496 −1.831*
WR
12
1.03 0.94*** 1.00 0.92** 0.738 −0.285
WR
24
0.94 0.75*** 0.94 0.80*** −0.042 −0.760
WR
36
0.82*** 0.59*** 0.91 0.70*** −1.097 −2.061**
WR
48
0.88 0.60*** 0.94 0.73*** −0.592 −1.495
WR
60
0.83*** 0.62*** 0.93 0.70*** −1.167 −1.389
Underwriter reputation 0.49 0.00 0.44 0.00 0.974 −0.974

(continued on next page)
9P G. Shu, S J. Chiang / International Review of Economics and Finance xxx (2013) xxx–xxx
Please cite this article as: Shu, P G., & Chiang, S J., Firm size, timing, and earnings management of seasoned equity offerings,
International Review of Economics and Finance (2013), />5.2. Univariate analyses
5.2.1. SEO firm size and performance
In Panel A of Table 4 we report difference tests comparing large-issuing and small-issuing SEO firms on the variables. We
divide the sample into halves at the median of the firm's assets one year prior to SEO issuance. The results show that the large
firms had higher discretionary accruals (0.13%) than the small firms (0.08%). Over the short-term, the mean (median) one-week
return 0.97% (0.05%) for the large firms is significantly higher than that of −0.43% (−0.87%) for the small firms. The other
indicators, namely, discounting, initial return, and overvaluation, are all significantly different from 0. However, these variables do
not differ significantly for the large and small firms. Over the long term, both the large and small firms suffered ex-post wealth
losses, and the losses became larger with the passage of time. Moreover, the large firms lost less wealth than the small firms. The
median 3-year (4-year) wealth ratio of 0.74 (0.72) for large firms is significantly greater than ratio of 0.57 (0.55) for small firms.
These results are consistent with those of Loughran and Ritter (1997), who find that both their large- and small-issuing firms
underperformed in the long term and the underperformance was greater for the small firms.
The results from the other control variables show that large firms had a higher average EPS (2.39) than small firms (1.05). It
comes as no surprise that large firms had greater assets and proceeds than median and small firms. The overall statistics basically
portray the differences in how large and small firms issue seasoned equity.
5.2.2. Underwriting methods and SEO firm's performance
In Panel B of Table 4, we divide the sample by flotation method. Because the existing shareholders retain their preemption
rights in a fixed-price offer, they get a higher discount than they would get with a bookbuilding offer. This positive signal,
accompanied by the high discount, made the initial returns significantly higher with fixed-price offers than with bookbuilding
offers. However, there is no significant difference between the two kinds of offer in the long-term wealth they generated. We note
that the pattern illustrated in Panel A is different from that in Panel B, implying that the flotation method is less likely to predict
the results related to firm size.
5.2.3. Earnings management and SEO firm's performance
In Panel C of Table 4, we divide the sample at the median of the discretionary accruals (EM). The results indicate that issuing
firms in the high EM group were more overvalued and had a higher three-year wealth ratio (WR
36
) than firms in the low EM

group.
Table 4 (continued)
Panel C: High vs. low earnings management
Auditor reputation 0.77 1.00 0.81 1.00 −1.043 −1.043
Underwriter method 0.14 0.00 0.13 0.00 0.154 −0.154
Ln (size) 6.95 6.90 7.04 6.98 −2.033** −1.842*
Ln (proceeds) 4.62 4.60 4.47 4.48 3.584*** −3.641***
Board shareholdings 22.79 18.48 26.87 23.82 −3.235*** −3.307***
EPS 0.70 0.96 2.72 2.32 −6.694*** −7.205***
Panel D: Cold vs. hot market
Cold market Hot market Difference test
Mean Median Mean Median t-test z-test
Earnings management (%) 0.17 0.07 0.09 0.05 2.172** −2.455**
One-week return 0.06 −0.25 0.33 −0.31 −0.355 −0.235
One-day return −0.31 −0.47 0.19 0.03 −1.598 −1.796*
Discounting (%) 15.23*** 14.59*** 19.12*** 19.09*** −3.403*** −3.021***
Initial return (%) 12.60*** 6.67*** 34.41*** 24.52*** −6.036*** −5.250***
Overvaluation (%) −2.62 −3.96** 15.29*** 7.11*** −5.158*** −4.313***
WR
12
0.96 0.95 1.03 0.93*** −1.422 −0.244
WR
24
1.01 0.91* 0.91** 0.75*** 1.184 −1.895*
WR
36
1.01 0.86 0.82*** 0.60*** 1.857* −3.313***
WR
48
1.15 0.89 0.83*** 0.56*** 2.747*** −4.110***

WR
60
1.04 0.88 0.83*** 0.62*** 2.025** −2.763***
Underwriter reputation 0.47 0.00 0.47 0.00 −0.012 −0.012
Auditor reputation 0.84 1.00 0.77 1.00 1.783* −1.640
Underwriter method 0.15 0.00 0.13 0.00 0.320 −0.321
Ln (size) 6.93 6.88 7.02 6.96 −1.485 −1.928*
Ln (proceeds) 4.49 4.30 4.56 4.56 −1.128 −2.752**
Board shareholdings 27.09 24.47 24.19 20.80 1.894* −1.945*
EPS 1.82 1.65 1.68 1.48 0.363 −0.546
Table 4 (continued)
10 P G. Shu, S J. Chiang / International Review of Economics and Finance xxx (2013) xxx–xxx
Please cite this article as: Shu, P G., & Chiang, S J., Firm size, timing, and earnings management of seasoned equity offerings,
International Review of Economics and Finance (2013), />5.2.4. Timing and SEO firm's performance
In Panel D of Table 4, the sample firms are divided into two groups based on the condition of the market. We find with respect
to discounting, initial returns, and overvaluation that both short-term overperformance and long-term underperformance are
more significant in a hot market than in a cold market. This result is consistent with Chen, Chen, Chen, and Huang (2013) finding
that the market timing theory helps explain the behavior of the Taiwan stock market between 1990 and 2001.
A synopsis of the univariate tests indicates that differences in long-term underperformance are primarily attributable to the
differences in market condition. First, WR
24
to WR
60
for the issues are significantly lower if the market was hot than if it was cold.
Second, the differences in firm size are significantly lower for small issuing firms than for large issuing firms. Third, the degree of
earnings management (WR36) was significantly less for high-EM than low-EM firms. The comparison of flotation methods fails to
yield a significant difference in long-term underperformance.
5.2.5. Timing, firm size, and SEO firm's performance
In Table 5 we report the results of nested difference tests on market size. We divide the sample based on market condition
(cold vs. hot) and then compare the small and large firms on the relevant variables. These tests reveal an interesting pattern. In a

cold market (Panel A), the average 3-year, 4-year, and 5-year wealth ratios (WR
36
,WR
48
,WR
60
) are significantly greater for small
firms (1.14, 1.40, and 1.26) than for large firms (0.78, 0.77, and 0.65). In contrast, in a hot market (Panel B), the 2-year, 3-year,
4-year, and 5-year wealth ratios are significantly smaller for small firms (0.85, 0.70, 0.74, and 0.69) than for large firms (1.04, 0.93,
0.95, and 0.94).
Another notable point is that the difference in wealth between cold and hot markets is more pronounced in small firms than in
large firms. In terms of the wealth ratios, the value of the seasoned shares issued by small firms increased in cold markets and
decreased in hot markets, but there is no obvious pattern for large firms. The results indicate that small firms were more likely
than large firms to time the hot markets to increase proceeds when placing their seasoned shares or to sell the shares at higher
prices. By selling their shares when the market was hot, the small firms exhibited a decrease in the ex-post wealth effect: after
5 years, the wealth effects were worth only 69% as much as they were at the time of issue.
Although not reported here, we also conduct market-flotation two-way nested difference tests on market flotation. The results
indicate that the discounts, initial returns, and overvaluation were higher with fixed-price offers than with bookbuilding offers,
and these differences are more significant when the market was hot than when it was cold. The long-term performance measures
are not significantly different between fixed-price offers and bookbuilding offers regardless of whether the market was hot or
cold.
Table 5
Difference tests between small and large firms in cold and hot markets. In this table, we segregate the contrast in variables for cold market (Panel A) and hot
market (Panel B) to test the differences of variables between large firms and small firms. All variables are defined in Table 3. In each panel, we report the test in
means and in medians, respectively. ***, **, and * denote the significance levels of 1%, 5%, and 10%, respectively.
Panel A: Cold market
Small firms Large firms Difference test
Mean Median Mean Median t-test z-test
Earnings management (%) 0.14 0.05 0.15 0.07 −0.10 −1.03
One-week return −0.35 0.17 1.22 1.10 −0.98 −0.70

One-day return −0.87 −0.71 0.57 0.06 −2.12** −1.88*
Discounting (%) 14.39 13.83 16.58 17.12 −0.88 −0.64
Initial return (%) 10.38 3.48 12.26 6.78 −1.15 −0.44
Overvaluation (%) −4.02 −4.86 −4.32 −6.77 0.06 −0.22
WR
12
0.98 0.97 0.94 0.92 0.44 −0.30
WR
24
1.08 0.96 0.86 0.81 1.35 −1.16
WR
36
1.14 1.10 0.78 0.78 2.02** −1.99**
WR
48
1.40 1.25 0.77 0.71 2.05** −2.49**
WR
60
1.26 1.25 0.65 0.61 3.36*** −3.02***
Panel B: Hot market
Small firms Large firms Difference test
Mean Median Mean Median t-test z-test
Earnings management (%) 0.00 0.03 0.12 0.05 −3.13*** −1.93*
One-week return −0.22 −0.87 1.28 0.22 −1.86* −1.83*
One-day return 0.30 0.09 0.17 −0.01 0.40 −0.32
Discounting (%) 18.37 17.80 18.96 18.35 −0.45 −0.30
Initial return (%) 28.26 23.20 38.64 23.69 −0.16 −0.21
Overvaluation (%) 9.89 7.30 19.68 5.26 −1.42 −0.05
WR
12

1.05 0.88 1.04 0.95 0.19 −0.77
WR
24
0.85 0.74 1.04 0.92 −1.84* −1.95*
WR
36
0.70 0.50 0.93 0.81 −2.37** − 2.71**
WR
48
0.74 0.53 0.95 0.70 −1.72* −2.34**
WR
60
0.69 0.55 0.94 0.69 −2.11** − 1.96*
11P G. Shu, S J. Chiang / International Review of Economics and Finance xxx (2013) xxx–xxx
Please cite this article as: Shu, P G., & Chiang, S J., Firm size, timing, and earnings management of seasoned equity offerings,
International Review of Economics and Finance (2013), />5.2.6. Earnings management, firm size, and SEO performance
In Table 6 we report the results of nested difference tests for EM size. We divide the sample at the EM median and then
compare the small and large firms on the relevant variables. The results show that if the degree of earnings management was low,
the ex-post wealth ratios are higher for large firms than for small firms. The median 2-, 3-, 4-, and 5-year wealth ratios for large
firms (0.91, 0.82, 0.67, and 0.66) are significantly larger than the corresponding ratios (0.68, 0.45, 0.42, and 0.48) for small firms.
This dominance of large firms disappears if the degree of earnings management was high.
Thus, these results suggest that large firms tended to use earnings management when issuing their seasoned shares. By using
large discretionary accruals, large firms adjusted their reported earnings so it appears that their seasoned shares did not differ
significantly in value from those issued by small firms. This result echoes Jindra's (2000) finding that earnings management is
positively associated with the overvaluation of seasoned shares, and Shivakumar's (2000) finding that firms use earnings
management to undo the discounts created by investors. Moreover, because they used high discretionary accruals, the large firms
in our study incurred significant wealth losses after issuance. For example, their average 5-year wealth ratio is lower if
discretionary accruals were high (0.81) than if they were low (0.94). This effect of earnings management on the ex-post wealth
ratio is not found for small firms.
Also not reported here are the results of nested difference tests comparing EM flotation methods. These results indicate that

fixed-price offerings are associated with higher discounts than bookbuilding offers, regardless of EM level. However, the two
types of offer do not differ significantly on our long-term performance measures regardless of whether the market was cold or
hot.
5.3. Regression analyses
5.3.1. Short-term performance of SEO firms
The univariate analyses create the simple picture that large firms engaged in earnings management and small firms timed hot
markets when placing their SEOs. In Table 7 we report the results of an OLS regression to investigate how short-term
performance, including the announcement effect (one-day and one-week returns), discounting, initial returns, and overvaluation
of SEOs, were affected by a hot market and earnings management. The results in Panel B show that for small firms, the hot-market
dummy is positively correlated with the short-term announcement effect, discounting, initial returns, and overvaluation. This
implies that the small firms took advantage of the hot-market window to place their seasoned shares.
Table 6
Difference tests between small and large firms based on earnings management. In this table, we segregate the contrast in variables for low EM (Panel A) and high
EM (Panel B) to test the differences of variables between large firms and small firms. The classification of EM is based on sample median. All variables are defined
in Table 3. In each panel, we report the test in means and in medians, respectively. ***, **, and * denote the significance levels of 1%, 5%, and 10%, respectively.
Panel A: Low EM
Small firms Large firms Difference test
Mean Median Mean Median t-test z-test
Hot issue 0.66 1.00 0.69 1.00 −.353 −.175
One-week return 0.16 −0.30 1.84 0.67 −1.64 −1.46
One-day return 0.10 − 0.09 0.23 0.19 −0.29 −0.67
Discounting (%) 17.99 19.16 19.49 18.27 −0.94 −0.45
Initial return (%) 25.58 22.00 38.52 19.21 −1.11 −0.15
Overvaluation (%) 7.60 4.83 19.03 −1.12 −1.01 −0.12
WR
12
0.99 0.93 0.99 0.93 −0.04 −0.04
WR
24
0.75 0.68 1.07 0.91 −2.36** − 2.37**

WR
36
0.70 0.45 0.93 0.82 −1.50 −2.18**
WR
48
0.72 0.42 0.96 0.67 −1.25 −2.94***
WR
60
0.70 0.48 0.94 0.66 −1.42 −1.76*
Panel B: High EM
Small firms Large firms Difference test
Mean Median Mean Median t-test z-test
Hot issue 0.61 1.00 0.63 1.00 −0.25 −1.96*
One-week return −0.76 −0.54 0.78 0.22 −1.52 −1.36
One-day return −0.07 −0.24 0.25 −0.19 −0.82 −0.47
Discounting (%) 19.91 21.40 17.62 17.45 1.30 −1.43
Initial return (%) 37.41 28.23 29.11 22.01 1.28 −1.17
Overvaluation (%) 17.50 10.08 11.49 6.25 1.03 0.25
WR
12
0.99 0.86 1.04 0.97 −0.74 −0.86
WR
24
1.01 0.74 0.93 0.92 0.69 −0.55
WR
36
1.03 0.70 0.87 0.77 1.06 −0.51
WR
48
0.98 0.76 0.86 0.72 0.81 −0.03

WR
60
1.04 0.85 0.81 0.68 1.45 −1.06
12 P G. Shu, S J. Chiang / International Review of Economics and Finance xxx (2013) xxx–xxx
Please cite this article as: Shu, P G., & Chiang, S J., Firm size, timing, and earnings management of seasoned equity offerings,
International Review of Economics and Finance (2013), />Table 7
Regression of short-run effect on earnings management and hot issue. This table reports the regression of small firms in Panel A and the regression of large firms
in Panel B. All variables are defined in Table 3. In each cell, the regression coefficient is reported in the upper case and p-value in parentheses is reported in the
lower case. ***, **, and * denote the significance levels of 1%, 5%, and 10%, respectively.
One-day return One-week return Discounting Initial Return Overvaluation
Panel A: All firms
Constant −2.380
(0.198)
−11.084**
(0.013)
−7.774
(0.255)
−14.985
(0.653)
−7.240
(0.828)
Underwriter reputation −0.004
(0.988)
−0.920
(0.110)
0.104
(0.907)
7.898*
(0.068)
7.896*

(0.068)
Auditor reputation 0.166
(0.581)
0.772
(0.284)
−0.698
(0.529)
8.329
(0.124)
8.498
(0.117)
Underwriter method 0.372
(0.290)
0.095
(0.911)
8.919***
(b 0.001)
−3.030
(0.651)
−7.999
(0.209)
Ln(size) −0.057
(0.851)
0.989
(0.171)
−3.760***
(0.001)
−1.332
(0.808)
0.389

(0.943)
Ln (proceeds) 0.392
(0.214)
0.943
(0.213)
4.578***
(b 0.001)
1.119
(0.847)
−1.758
(0.758)
Board Shareholdings 0.013
(0.160)
−0.036*
(0.094)
−0.110***
(0.001)
−0.188
(0.249)
−0.156
(0.331)
EPS 0.106**
(0.014)
0.123
(0.232)
0.131
(0.410)
1.696**
(0.029)
1.303

(0.096)
One-day return 0.154
(0.376)
−1.290
(0.130)
Discounting (%) −1.503***
(b 0.001)
Hot issue 0.617**
(0.037)
−0.587
(0.401)
−4.267***
(b 0.001)
17.938***
(0.001)
20.139**
(b 0.001)
Earnings management (%) −0.127
(0.756)
1.186*
(0.059)>
0.425
(0.466)
1.600
(0.574)
11.687
(0.115)
Hot issue * earnings management −0.252
(0.116)
0.004

(0.995)
0.425
(0.531)
−2.386
(0.472)
−3.054
(0.290)
Adj. R
2
0.013 0.020 0.175 0.145 0.042
Panel B: Small firms
Constant −3.700
(0.587)
−0.874
(0.938)
−12.231
(0.629)
−87.603
(0.768)
−93.339
(0.211)
Underwriter reputation 0.033
(0.935)
−0.227
(0.766)
−1.476
(0.324)
2.988
(0.500)
2.737

(0.533)
Auditor reputation −0.238
(0.602)
0.270
(0.761)
−2.184
(0.199)
9.323*
(0.067)
8.589*
(0.087)
Underwriter method 0.035
(0.958)
−1.149
(0.333)
−6.705**
(0.007)
0.839
(0.910)
−0.184
(0.980)
Ln(size) 0.610
(0.573)
−1.348
(0.453)
9.888**
(0.015)
15.336
(0.202)
13.276

(0.262)
Ln (proceeds) −0.218
(0.797)
2.390
(0.112)
−8.303**
(0.009)
−5.649
(0.547)
−1.971
(0.831)
Board shareholdings 0.001
(0.937)
−0.073**
(0.017)
0.161**
(0.006)
0.173
(0.318)
0.114
(0.502)
EPS −0.007
(0.951)
0.181
(0.312)
−0.176
(0.680)
0.843
(0.506)
0.419

(0.739)
One-day return −0.603*
(0.053)
−0.936
(0.310)
Discounting (%) −22.091***
(b 0.001)
Hot issue 2.326***
(b 0.001)
−1.551*
(0.074)
8.470***
(b 0.001)
15.074**
(0.034)
13.457**
(0.022)
Earnings management (%) 0.835
(0.285)
0.717
(0.409)
2.117
(0.467)
−1.412
(0.870)
1.774
(0.834)
Hot issue * earnings management −1.840***
(0.001)
0.734

(0.340)
−4.633**
(0.028)
2.504
(0.687)
1.119
(0.858)
Adj. R
2
0.057 0.020 0.198 0.209 0.031
Panel C: Large firms
Constant −3.622
(0.543)
−6.582
(0.484)
−1.861
(0.929)
336.609
(0.153)
304.749
(0.168)
Underwriter reputation 0.161
(0.722)
−1.412
(0.109)
2.135
(0.177)
3.622
(0.590)
4.203

(0.518)
Auditor reputation 0.573
(0.408)
1.848
(0.123)
2.879
(0.235)
2.051
(0.795)
−0.636
(0.934)
Underwriter method 1.013
(0.109)
1.096
(0.372)
−10.891***
(b 0.001)
−11.492
(0.265)
−12.935
(0.168)
(continued on next page)
13P G. Shu, S J. Chiang / International Review of Economics and Finance xxx (2013) xxx–xxx
Please cite this article as: Shu, P G., & Chiang, S J., Firm size, timing, and earnings management of seasoned equity offerings,
International Review of Economics and Finance (2013), />In contrast, for large firms (Panel C), we find the key predictor to be discretionary accruals rather than the hotness of the
market. Discretionary accruals are positively correlated with discounting, initial returns, and overvaluation. These results indicate
that large firms tended to engage in earnings management when planning to issue seasoned shares. Because the market buys
such manipulated earnings at face value, it attaches a high valuation on the shares.
Based on the finding that earnings management is more important than timing for large firms and vice versa for small firms,
we explore whether the interaction of these two variables can provide an additional explanation of the announcement effect. To

do so, we add an interaction term to our model. The results in Panel B show that for small firms the interaction is negatively
correlated with both the announcement effect and discounting. This result implies that the timing effect is diluted for the small
firms that engaged in earnings management practices. The results in Panel C illustrate that the interaction is negatively correlated
with discounting for large firms, implying that the positive association between earnings management and discounting is
somewhat diluted when the firms also took advantage of timing. In general, these results illustrate that the short-term effects of
earnings management and timing on SEOs offset each other.
5.3.2. Long-term performance of SEO firms
In this section, we report the results of a further investigation of the effects of timing and earnings management on the ex-post
worth of SEO firms. The results of the regression are summarized in Table 8.
7
For small firms (Panel B), we find the hot-market
dummy to be negatively correlated with the 2-year, 3-year, 4-year, and 5-year wealth ratios. These results further corroborate the
previous finding that small firms took advantage of the opportunity window to time the issuing of their seasoned shares. For small
firms that issued seasoned shares when the market was hot, the ex-post wealth ratios declined after the shares were issued.
Specifically, the average 2–5 year wealth ratios are 0.85, 0.70, 0.74, and 0.69, respectively. Panel B also shows that the initial
returns are negatively correlated with the 4- and 5-year wealth ratios.
For large firms (Panel C), the level of discretionary accruals is negatively correlated with the 2–5-year wealth ratios.
Specifically, the large firms that had large discretionary accruals had 2–5-year wealth ratios of 0.93, 0.87, 0.86, and 0.81,
respectively. Moreover, we find that for large firms the wealth ratios are also associated with EPS; this is not the case for small
firms.
The overall findings so far create a clear picture that small firms and large firms traveled different routes in their pursuit of
larger proceeds or higher prices when placing their seasoned shares. These results reinforce the conclusion that the small firms
tended to time the market whereas the large firms tended to engage in earnings management practices. An examination of the
short-term announcement effect and the long-term wealth ratios lend support to this argument, because the timing dummy
(earnings management) is positively correlated with the short-term announcement effect and negatively correlated with
long-term wealth for small (large) firms.
A secondary question is why the mechanisms that small and large firms adopted when placing their seasoned shares are so
different. A possible explanation is that investors are more likely to take at face value the accounting numbers reported by large
firms than those reported by small firms. Evidence for this explanation can be found in Table 7, where we find that EPS is
significantly positively correlated with the announcement effect for large firms but not small firms. Then why do investors pay

more attention to accounting information prepared by large firms? Are they rational in their belief that the data provided by such
Table 7 (continued)
One-day return One-week return Discounting Initial Return Overvaluation
Panel C: Large firms
Ln(size) −0.269
(0.724)
0.180
(0.895)
4.959*
(0.064)
−41.185
(0.229)
−39.329
(0.223)
Ln (proceeds) 0.805*
(0.072)
0.890
(0.348)
−4.345***
(0.006)
−8.358
(0.429)
−3.968
(0.698)
Board shareholdings 0.008
(0.638)
−0.004
(0.886)
0.037
(0.535)

−0.281
(0.286)
−0.359
(0.161)
EPS 0.144**
(0.021)
0.112
(0.398)
−0.288
(0.191)
1.368
(0.348)
1.405
(0.318)
One-day return 0.303
(0.299)
−1.934
(0.160)
Discounting (%) −22.465***
(0.002)
Hot issue 0.099
(0.894)
0.182
(0.879)
4.315
(0.100)
15.364
(0.138)
14.106
(0.103)

Earnings management (%) −0.450
(0.661)
1.824*
(0.061)
6.339*
(0.078)
19.411**
(0.030)
16.561*
(0.062)
Hot issue * Earnings management −0.182
(0.778)
−0.746
(0.495)
−3.741*
(0.098)
8.381
(0.339)
12.401
(0.144)
Adj. R
2
0.007 0.003 0.192 0.161 0.076
7
We include the short-term effect in the regression of long-term performance. However, because one-day and one-week returns are highly correlated and
discounting, initial returns, and overvaluation by definition are multicollinear, we include these variables in the regression models. The results (unreported) are
qualitatively similar.
14 P G. Shu, S J. Chiang / International Review of Economics and Finance xxx (2013) xxx–xxx
Please cite this article as: Shu, P G., & Chiang, S J., Firm size, timing, and earnings management of seasoned equity offerings,
International Review of Economics and Finance (2013), />Table 8

Regression of long-run performance on earnings management and hot issue. This table reports the regression of small firms in Panel A and the regression of large
firms in Panel B. All variables are defined in Table 3. In each cell, the regression coefficient is reported in the upper case and p-value in parentheses is reported in
the lower case. ***, **, and * denote the significance levels of 1%, 5%, and 10%, respectively.
WR
12
WR
24
WR
36
WR
48
WR
60
Panel A: All firms
Constant 1.149***
(0.001)
1.077**
(0.046)
1.382**
(0.034)
2.057**
(0.014)
1.409**
(0.046)
Underwriter reputation 0.117**
(0.012)
0.099
(0.155)
0.114
(0.168)

0.142
(0.178)
0.080
(0.377)
Auditor reputation 0.063
(0.275)
0.036
(0.668)
0.084
(0.408)
0.172
(0.190)
0.100
(0.383)
Underwriter method 0.159**
(0.025)
0.039
(0.720)
0.186
(0.143)
0.283*
(0.085)
0.034
(0.816)
Ln (size) −0.188***
(0.001)
−0.012
(0.891)
0.033
(0.745)

−0.146
(0.274)
−0.120
(0.292)
Ln (proceeds) 0.163***
(0.009)
−0.061
(0.505)
−0.207*
(0.061)
−0.082
(0.564)
0.029
(0.810)
Board Shareholdings 0.003*
(0.099)
0.003
(0.268)
0.003
(0.289)
0.002
(0.640)
0.003
(0.346)
EPS 0.038***
(b 0.001)
0.032**
(0.024)
0.034*
(0.050)

0.040
(0.120)
0.049**
(0.038)
One-day return 0.000
(0.962)
0.002
(0.910)
−0.007
(0.651)
−0.011
(0.582)
−0.017
(0.351)
Discounting (%) −0.007***
(0.009)
−0.003
(0.440)
0.001
(0.796)
−0.005
(0.431)
−0.001
(0.857)
Initial return (%) 0.000
(0.683)
0.002***
(0.008)
0.002**
(0.022)

0.000
(0.869)
0.000
(0.596)
Hot issue 0.086
(0.143)
−0.159*
(0.066)
−0.207**
(0.048)
−0.307**
(0.019)
−0.161
(0.157)
Earnings management (%) −0.011
(0.707)
−0.085*
(0.057)
−0.053
(0.322)
−0.040
(0.552)
0.007
(0.903)
Hot issue * Earnings management −0.047
(0.187)
0.078
(0.146)
0.075
(0.235)

0.057
(0.487)
0.012
(0.862)
Adj. R
2
0.065 0.051 0.059 0.027 0.006
Panel B: Small firms
Constant 2.708
(0.102)
2.045
(0.274)
1.801
(0.223)
8.696**
(0.015)
6.273**
(0.004)
Underwriter reputation 0.207**
(0.044)
0.144
(0.222)
0.165
(0.119)
0.300
(0.170)
0.212
(0.126)
Auditor reputation 0.113
(0.324)

0.001
(0.994)
0.081
(0.507)
0.258
(0.282)
0.191
(0.190)
Underwriter method 0.174
(0.304)
−0.114
(0.552)
0.420*
(0.088)
0.407
(0.226)
0.193
(0.414)
Ln (size) −0.297
(0.282)
−0.249
(0.436)
0.108
(0.646)
−0.963*
(0.096)
−0.679*
(0.058)
Ln (proceeds) 0.001
(0.996)

0.107
(0.700)
−0.392*
(0.052)
−0.212
(0.671)
−0.163
(0.620)
Board Shareholdings 0.003
(0.423)
0.005
(0.294)
0.009*
(0.072)
0.003
(0.744)
0.008
(0.159)
EPS −0.002
(0.937)
0.041
(0.322)
0.024
(0.566)
0.019
(0.804)
0.021
(0.657)
One-day return 0.002
(0.914)

−0.010
(0.666)
0.011
(0.625)
−
0.012
(0.775)
−0.012
(0.654)
Discounting (%) −0.034
(0.745)
−0.039
(0.755)
−0.051
(0.688)
−0.190
(0.399)
0.054
(0.709)
Initial return (%) −0.066
(0.595)
−0.049
(0.728)
−0.153
(0.316)
−0.493*
(0.067)
−0.241
(0.155)
Hot issue 0.080

(0.501)
−0.300**
(0.039)
−0.659***
(b 0.001)
−0.516*
(0.087)
−0.843***
(b 0.001)
Earnings management (%) −0.062
(0.613)
−0.170
(0.218)
−0.128
(0.360)
0.109
(0.672)
0.122
(0.468)
Hot issue * Earnings management −0.044
(0.723)
0.100
(0.477)
0.081
(0.558)
−0.050
(0.856)
0.021
(0.905)
Adj. R

2
−0.017 − 0.018 0.194 0.048 0.247
Panel C: Large firms
Constant 1.086
(0.233)
1.909
(0.230)
1.358
(0.388)
1.936
(0.264)
1.575
(0.396)
Underwriter reputation 0.024
(0.734)
−0.053
(0.675)
0.024
(0.850)
−0.0995
(0.481)
−0.144
(0.346)
(continued on next page)
15P G. Shu, S J. Chiang / International Review of Economics and Finance xxx (2013) xxx–xxx
Please cite this article as: Shu, P G., & Chiang, S J., Firm size, timing, and earnings management of seasoned equity offerings,
International Review of Economics and Finance (2013), />firms are more informative? We believe the answer is yes, because the earnings per share revealed in the financial statements of
large firms, but not small firms, accurately predict the ex-post wealth effect (Panel C). Because the earnings reported by small
firms are less informative, these firms chose an alternative path to large proceeds by timing the market when placing their
seasoned shares. Thus, the decrease in wealth ratios verifies the timing effect for small firms.

6. Summary of main conclusions
The results of our study suggest that small firms and large firms adopt different approaches when placing their seasoned
shares in the Taiwan market. Aiming for larger proceeds, small firms tend to time the market whereas large firms tend to use
discretionary accruals. When timing the market, small firms have a higher announcement return, less underpricing, and higher
initial returns. The timing effect predicts a decline in the ex-post wealth ratios. In contrast, the tendency of large firms to adjust
their reported earnings when using their discretionary accruals is associated with a larger short-term announcement effect and a
lower ex-post wealth effect. Thus, the results suggest that there is a separating equilibrium for the use of different approaches. As
a possible explanation for this equilibrium, we propose that the accounting numbers of large firms, which suggest good prospects
for their future growth, are caused at least in part by their use of discretionary accruals when issuing seasoned shares. On the
other hand, small firms, whose accounting numbers are less predictive of their growth, tend to take advantage of the opportunity
window to time their placement of seasoned shares.
Finally, we note that our findings can be applied specifically to the Taiwan market, whose flotation methods are not the same
as those applied by other markets. Further studies could profitably explore the generalizability of this finding to markets in which
the SEO anomaly is not preconditioned by the flotation methods the associated firms adopt.
Acknowledgments
The authors thank the National Science Council of R.O.C. for the research support under Contract No. 101-2914-I-030-003-A1. The
authors would also like to thank the anonymous reviewers and the Editor (Carl R. Chen) for valuable comments.
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Table 8 (continued)
WR
12
WR

24
WR
36
WR
48
WR
60
Panel C: Large firms
Auditor reputation −0.094
(0.386)
−0.105
(0.582)
0.071
(0.714)
−0.037
(0.872)
−0.203
(0.399)
Underwriter method −0.060
(0.585)
−0.123
(0.524)
−0.078
(0.686)
0.087
(0.673)
0.073
(0.737)
Ln (size) −0.182
(0.133)

−0.112
(0.591)
−0.060
(0.773)
−0.246
(0.283)
−0.259
(0.298)
Ln (proceeds) 0.226***
(0.002)
0.024
(0.846)
−0.028
(0.822)
0.142
(0.308)
0.246
(0.103)
Board shareholdings 0.005*
(0.089)
0.004
(0.405)
0.006
(0.191)
0.009*
(0.078)
0.009
(0.121)
EPS 0.042***
(b 0.001)

0.052***
(0.007)
0.052**
(0.012)
0.082***
(0.007)
0.082**
(0.012)
One-day return −0.005
(0.731)
0.010
(0.688)
−0.020
(0.397)
−0.009
(0.741)
−0.032
(0.256)
Discounting (%) −0.084
(0.306)
−0.230
(0.121)
−0.085
(0.564)
−0.190
(0.246)
−0.237
(0.185)
Initial return (%) −0.080
(0.424)

−0.179
(0.330)
−0.030
(0.875)
0.125
(0.550)
0.197
(0.371)
Hot issue 0.198**
(0.022)
0.193
(0.265)
0.100
(0.570)
0.186
(0.470)
0.267
(0.376)
Earnings management (%) −0.047
(0.602)
−0.386**
(0.016)
−0.351**
(0.027)
−0.398**
(0.025)
−0.387**
(0.039)
Hot issue * Earnings management 0.046
(0.612)

0.174
(0.262)
0.221
(0.150)
0.272
(0.121)
0.304
(0.106)
Adj. R
2
0.092 0.068 0.052 0.087 0.107
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