J. Serv. Sci. & Management, 2008, 1: 135-142
Published Online August 2008 in SciRes (www.SRPublishing.org/journal/jssm)
BBEmpirical Study on the Performance of Initial Public
Offerings in China
Liang Peng
Graduate School of Economics and Business Administration, Hokkaido University, Japan, 060-0809
School of Management, Central South University, Changsha, P.R.China, 410083
P
ABSTRACT
We study the long-run performance of 166 IPOs listed on China’s Shanghai Stock Exchanges from 2000 to 2002. We
find that the average market-adjusted cumulative return and buy-and-hold return over the three years after listing are
-32.02% and -20.88%, which are both significantly negative. What’s more, as an additional robustness check, we cal-
culate wealth relatives. One year after listing, WR less than 1 and we obtain a three-year wealth relative of 0.6826,
consistent with the CAR and BHAR estimates. We then u se a cross-sectional ana lysis to explain the long-run und erper-
formance of Chinese IPOs. The results show that the aftermarket performance is positive after listing (6 months) but
thereafter returns decline. Buying A-share IPOs immediately after listing and holding the investment for three years
results in negative returns and wealth relatives less than one.
Keywords: Initial Public Offering, Long-run Performance, Market Efficiency
1. Introduction
Since Ritter’s [19] has presented convincing empirical
evidence that IPOs underperform in the long-run, a num-
ber of corresponding studies have sought to reveal the
existence the sever aftermarket underperformance for
issuers in different countries. Aggarwal [1] and Loughran
et al. [11] examine the returns on IPOs during the three
years after going public for a number of countries. They
equally-weight the IPOs in their respective samples and
both find underperformance. Comparable results have
also been found for IPOs in economies under transition
such as China. From table 1, the aftermarket underper-
formance is not unique to the US IPO market, it also ex-
ists in a number of other countries, like Canada, Japan
and so on.
Chinese stock markets expanded rapidly following the
opening of securities markets in Shanghai and Shenzhen
in the early 1990s. Although until now they are only 18
years old, they enjoy very high growth. The importance
and newness of the markets and unique institutional fea-
tures make China a special environment to conduct re-
search on IPOs and findings from studies in other markets
cannot be extrapolated to China. Some of the previous
studies have noted that Chinese IPOs enjoy the world’s
highest initial returns at around 200-300% [18] [4]. How-
ever, there is little research on the long-run performance
of Chinese IPOs due to the data shortage and the current
results on the long-run performance are mixed. Sun and
Tong [20] look briefly at the long-run share returns (raw
returns and Hong Kong Hang Seng Index adjusted returns)
of IPOs and find stock returns show some mild improve-
ments up to five years after share issue privatizations.
Chan et al. [4] study 570 A-share IPOs and 39 B-share
IPOs from 1993-98 and 1995-98 respectively and find
that in the long-run (within three-year after listing)
A-share IPOs slightly underperform the size- and/or
book/market-matched portfolios while B-shares outper-
form the benchmark portfolios.
The contribution of this paper is to use more updated
data and to present a deeper understanding of the special
features in the Chinese IPO market to study the perform-
ance, especially the long-run performance computing by
both the abnormal three-year cumulative returns and
buy-and-hold returns of IPOs and use a cross-sectional
analysis to explain th e long -run und erp erf ormance of Ch i-
nese IPOs.
The rest of the paper is organized as follows: Sectio n 2
introduces the features of China’s stock markets; Section
3 presents the data and methodology for calculating the
long-run returns; Section 4 provides the analysis of em-
pirical results on the long-run returns. Section 5 examines
several different hypotheses of the cross-sectional vari-
ance in abnormal returns. The summary and conclusion
appear in Section 6.
2. Features of China’s Stock Market
Following the economic reforms that began in 1978, the
Chinese stock market was finally established in the early
1990s. The Shanghai Securities Exchange was opened in
1990, followed by the establishment of the Shenzhen

136 Liang Peng
Table 1. International evidence on the aftermarket performance of IPOs
Stock Exchange in 1991.Chinese government tries to use
the market to develop the econ omy, while still keep some
socialist characteristics, which means the government
plays a crucial role in monitoring and regulating the stock
markets.
In Chinese stock market, there are several classes of
share, A-shares, B-shares, H-shares, N-shares and
non-tradable shares. A-shares were tradable only by do-
mestic investors (and quoted in Yuan) whilst B-shares
were tradable only by foreign investors (and quoted in US
Dollars), although recently domestic investors have also
been able to trade B-shares. Hand N-shares are listed on
the Hong Kong and New York Stock exchanges, respec-
tively. Non-tradable shares include those owned by the
state and other state owned enterprises (legal person
shares), although China started to merge this dual share-
holding system in May 2002.When going public, shares
not retained by the government, other enterprises or em-
ployees are sold to outsid e investors. There are five types
of shares in China: government shares, which are held by
the State Assets Management Bureau (SAMB); legal en-
tity shares (or C shares), which are held by other
state-owned enterprises; employee shares, which are held
by managers and employees; ordinary domestic individ-
ual shares (or A-shares), which can be purchased only by
Chinese citizens of the PRC on th e Shanghai Securities or
the Shenzhen Stock Exchange; and foreign shares, which
can be purchased only by foreign investors in Mainland
China (B-share), in Hong Kong (H-share), or on the
NYSE (N-share). Only the A-shares and B-shares are
listed on the Shanghai Securities and Shenzhen Stock
Exchanges. The first three types of shares are not tradable
in the official exchanges, although employee shares are
allowed to be listed three years after the IPO.
3. Data and Methodology
We study the long-run performan ce of 166 IPOs listed on
China’s Shanghai Stock exchanges from 2000 to 2002.
The data mainly from the China Centre for Economic
Research and www.sse.com.cn, while the financial data
and transactional data of shares (mainly daily closing
prices) come from the Wind Information database.
The following criteria are used in selecting the final
sample: (1) issuing firms are listed in Shanghai Stock
Exchange (2) stock price data for issuers, market capi-
talization are available on the Wind Information database
(3) common-share IPOs are selected, and exclude units,
close-end funds, and real estate investment trust offerings.
To analyze the after performance of Chinese IPOs, we
apply the standard event study methodology. Thus ab-
normal returns of our sample are computed using the
Cumulative Abnormal Returns (CAR) and Buy-and-Hold
Abnormal Returns (BHAR). There continues to be dis-
agreement regarding the measurement of long-run ab-
normal return performance. Barber and Lyon [2], Lyon et
al. [17], Kothari and Warner [10] and Fama [5] analyze
the difference of these two methods, and find that there is
no cons ensus on the preferred on e. Lyon et al. [17] docu-
ment that BHARs should be used if the research question
is whether or not investors earn abnormal stock returns by
holding stocks over a particular time horizon. While the
CAR approach should be employed to answer the fol-
lowing question: do sample firms persistently earn ab-
normal monthly returns? Though CARs implicitly assume
frequent portfolio rebalancing, Fama [5] justifies its use
since it would produce fewer spurious rejections of mar-
ket efficiency than would the use of BHARs. There also
exists a greater knowledge of the distribution properties
and the statistical tests for CARs. Since in China, th e ma-
Countr
y
Author(s) Number of IPOsIssuing YearsAftermarket performance
Australia Lee,Taylor& Walter(1996) 266 1976-89 –46.5%
Brazil Aggarwal, Leal&Hernandez(1993) 62 1980-90 –47%
Canada Kooli and Suret(2003) 445 1991-98 –16.86%
Chile Aggarwal, Leal&Hernandez(1993 28 1982-90 –23.7%
Finland Keloharju(1993) 79 1984-89 –21.1%
Germany Ljungqvist(1997) 145 1970-90 –12.1%
Hong Kong M cguiness (1993) 72 1980-90 –18.3%
Japan Cai&Wei(1997) 172 1971-90 –27%
Korea Kim, Krinsky&Lee(1995) 99 1985-88 2.00%
New Zealand Firth(1997) 143 1979-87 –10%
Sweden Loughran,Ritter&Rydqvist(1994) 162 1980-90 1.20%
United Kindom Levis(1993) 712 1980-88 –8.1%
United States Loughran&Ritter(1995) 4753 1970-90 –20%
United States Simon (1989) 35 1926-33 –39%
United States Ritter (1991) 1526 1975-84 –29.1%

Empirical Study on the Performance of Initial Public Offerings in China 137
jority of investors are individual investors, and they trade
much more frequently than those in other markets, to
guarantee the robustness of our results, we estimate the
three-year abnormal return after IPO using both measures.
Research in the US has frequently used a matching
firm approach to measure long-run abnormal returns.
However, the small number of companies available
means there would be a bias caused by the repeated use of
matching companies. We therefore both measure
three-year post-IPO abnormal returns relative to the
Shanghai Stock Exchange A-share index, a capitalization
weighted index of 166 compan ies and matching firms. So
we build our conclusions on different methodologies,
limited by the paper, we use the event time approach and
use two methodologies within each approach: we first
examine the cumulative abnormal returns (CARs) and
Buy-and-hold returns (BHARs) with the shanghai stock
exchange Index as the benchmark and then examine the
cumulative abnormal returns (CARs) and Buy-and-hold
returns (BHARs) with matching firms.1
We measure the monthly return to both the company
it
r and the market over the three year period after the
IPO. The market benchmark return mt ris the return to the
Shanghai Stock Exchange A-share index or the return of
the matching firms. We follow Ritter (1991) [19] and
exclude the initial return at the time of th e IPO. The CAR
is obtained from the individual firm abnormal returns.
The CAR over the 36 months from listing is the sum of
the average monthly market-adjusted returns. The BHAR
is the difference between the holding-period return of
stock ‘i’ and the market return:
The first measure we use is the three-year buy-and- hold
market-adjusted returns (BHAR), defined as:
()
T
iT t1
BHR1 it r+
∏
＝
＝ (1)
()( )
TT
iT t1 t1
BHAR 11
it mt
rr+− +
∏∏
＝＝
＝ (2)
The mean BHAR over a period T is:
TiT
1
BHAR BHAR
n
i=
∑
1
＝n (3)
A simple t-test is employed to test the null hypothesis
of zero mean market-adjusted buy-and-hold return:
,
()
t
iT
BHAR
tBHAR n
σ
= (4)
Where , ()
iT
BHAR
σ
is the standard deviation of the
buy-and-hold market-adjusted returns, and n is the sample
1 In China, the total number of market days of each year, less the long
holidays, is about 240. However, in consistent with the study with Ritter
(1991) and Loughran and Ritter (1995), we assumed that the number of
market days per year is 252 and each month has 21 market days. On and
from the first day of listi ng to the 21st market day is the first event month
and then the second, the third and so on. So, the word “month” herein
refers to a market month, the word “year” to the market year and the
express “three years” to 756 market days.
size.
The second measure we use is the three-year cumula-
tive market-adjusted long-run performance (CAR), de-
fined as:
()
1
T
iTit mt
t
CARr r
=
=−
∑ (5)
n
TiT
i=1
1
CAR CAR
n∑
＝ (6)
The statistical significance of cumulative abnormal re-
turns is tested by:
()
it
it t
CAR
tCAR n
σ
= (7)
Where ()
it
CAR σ is the standard deviation of cumula-
tive abnormal returns for the sample of n firms and t n is
the number of IPOs on the tth month.
What’s more, as an additional robustness check, we
calculate wealth relatives. Wealth relatives (WR) are the
ratio of the end-of-period wealth from holding a portfolio
of issuers to the end-of period wealth from holding the
market benchmark. A wealth relative less than 1 indicates
underperformance relative to the benchmark portfolio.
4. Results on the long-run performance
4.1. Results on the Long-run Performance by
Using Shanghai Stock Exchange Index as the
Benchmark
Tables 2 and 3 present the abnormal returns calculated
using Shanghai Stock Exchange Index as the bench-
mark.This two tables present the mean percentage CAR
and BHAR within 36 months after listing for 166 IPOs
listed on the Shanghai A-share market between 2000 and
2002. The initial return at listing is excluded from the
estimation of the CAR and BHAR.
From the result, IPO performance has been poor
whichever method is used. For example, From Table 1
and Table 2, either method shows the IPO performance-
begins to underperformed than that of the market index
after 6 months of listing and the mean BHAR and CAR
estimated over one year period after issue is
-3.2%(t-statistic=-2.314) -2.05%(t-statistic=-1.259), over
a two year period after issue is-11.37%(t-statistic=-5.285)
and -14.07%(t-statistic=-5.427), and a three-year period
after issue is -20.88%(t-statistic=-9.806) and
-32.02%(t-statistic=-9.37). One year after listing, WR less
than 1 and we obtain a three-year wealth relative of
0.6826.
Figure1 shows the plot of CAR, BHAR and the
monthly AR for the first 36 months after the listing. It
shows the IPO performance within the first months after
listing slightly outperforms the market index. The con-
tinuation of this trend varies with the measurement. By
CAR, the IPO performance outperforms the market index
for the first nine months after listing; while with BHAR,

138 Liang Peng
Table 2. Mean of CAR and BHAR of A shares on Shanghai Stock Exchange (RA:A-Share Index of Shanghai Stock
Exchange; BHRA: A- Share Index of Shanghai Stock Exchange)
Months/Return RIPO RA(2) CAR (3)=(1) – (2)BHRIPO (4)BHRA (5)BHAR (6)=(4) – (5) WR
0 –1 – 0.9996 –0.9962 – 0.0034 1.0002 1.0042 – 0.004 0.9963
0 –3 – 0.9817 –0.9841 0.01245 1.0174 1.0042 0.0132 1.0118
0 –6 – 1.0033 –1.0168 0.0135 0.9874 0.9798 0.0076 1.0048
0 –12 – 1.1367 –1.1162 – 0.0205 0.8471 0.8791 – 0.032 0.9581
0 –18 – 1.2489 –1.181 – 0.0679 0.736 0.8069 – 0.0709 0.896
0 –24 – 1.3223 –1.1816 – 0.1407 0.6837 0.8022 – 0.1137 0.8323
0 –36 – 1.5468 –1.2242 – 0.3202 0.5407 0.7495 – 0.2088 0.6826
Table 3. Mean and t-Statistic test of CAR and BHAR. ** significant at the 0.05, *** significant at the 0.01 (significance
is given by a skewness-adjusted t-statistic)
Return Months Mean Media Std. DevSkewnessKurtosisMin. Max. t-Statistic Sig
0 –1 – 0.004 – 0.0143 0.0778 0.5281 – 0.1944– 0.159 0.21380.661 0.51
0 – 3 0.0132 0.0058 0.1278 1.2024 2.7328 – 0.21880.50641.335 0.184
0 – 6 0.0076 0.0014 0.1397 0.6874 1.0327 – 0.25410.56320.699 0.485
0 – 12 – 0.032 – 0.0318 0.1783 – 0. 0367 0.8188 – 0.61130.4725– 2.314** 0.022
0 – 18 – 0.0709 – 0.0751 0.2018 0.1141 1.8557 – 0.75640.7431– 4.524*** 0
0 – 24 – 0.1137 – 0.1404 0.2772 1.5804 5.5915 – 0.76 1.2381– 5.285*** 0
BHAR
0 – 36 – 0.2088 – 0.2835 0.2743 1.7754 4.7055 – 0.61671.1777– 9.806*** 0
0 – 1 –0.0034 – 0.0126 0.0773 0.3886 – 0.4122– 0.16740.1962– 0.569 0.57
0 –3 0.0125 0.0098 0.1212 0.6578 1.0641 – 0.25830.41681.324 0.187
0 – 6 0.0135 0.0187 0.1407 0.1368 – 0.1955–0.28290.43851.237 0.218
0 – 12 – 0.0205 – 0.0043 0.2103 – 0.5158 0.9987 – 0.73960.4309– 1.259 0.21
0 – 18 –0.0679 – 0.058 0.2637 – 0.6502 1.822 –1.13050.6636– 3.319*** 0.001
0 – 24 – 0.1407 – 0.1436 0.334 0.15 1.2852 – 2.25230.9658– 5.427*** 0
CAR
0– 36 –0.32.2 – 0.3499 0.4403 0. 3586 0.1121 – 1.59341.0116– 9.37*** 0
IPO performance outperforms the market index for the
first 6months after listing. Although there is a little dif-
ference between the long-run abnormal returns by these
two measurements, the overall trends are consistent: the
IPO performance outperforms the market index within a
short period after listing, but it is poor than the market
index in the long run. In addition, from the AR of each
individual month, the IPO performance is almost equal to
the market index within the first nine months after listing,
but it drops significantly in the 10th month and then con-
tinues to keep equal to the market index. However, its
performance for every month after the 16th month is sig-
nificantly poor than the market index.
4.2. Results on the Long-run Performance by
Using Matching Firms
Research in the US has frequently used a matching firm
approach to measure long-run abnormal returns. So we
also compute the long-term abnormal return with the
matching firms. Our reference portfolios are formed con-
tinually on the basis of firm size. To construct the size
control portfolio, all Chinese stocks are ranked each
month according to their market capitalization, and four
quartile portfolios are formed.
From Table 4, within one-year, results of abnormal re-
turn of an IPO computing by CAR and BHAR begin to
show big deviations. The one-year period CAR is
-10.89%, but the one-year period BHAR is only -6.14%.
In addition, the differences between the 0-18 month,
two-year and three-year period CAR and BHAR are even
bigger, especially the two-year and the three-year abnor-
mal returns. The deviations in these two methods results
in the matching firm will be adjusted at the end of each
year. For the same sample firm, the matching firm is dif-
ferent and there are big differences between the market
prices of different matching firms. When different
matching firms are linked at the end of each year, big
differences may appear between the closing price of the
last market day of the previous year and the closing price
of the first market day of another matching firm for the
current year, thus making the return of the first market
day of the current year to be very small or very big.
BHAR is obtained using the continuous multiplication, so
this makes the results unreliable. On basis of this, when
using the return of the matching firm to calculate the

Empirical Study on the Performance of Initial Public Offerings in China 139
-0.35
-0.3
-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
1357911 1315 1719 212325 2729 3133 35
CAR/BHAR/A
R
BHAR CARAR
Month
Figure 1. Three Year AR, CAR and BHAR for IPOs
listed in 2000-2002
-0.35
-0.3
-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
1471013 16 19 2225 28 31 34
CAR/AR/BHAR
AR CAR BHAR
Mont
Figure 2 Three Year AR , CAR and BHAR for IPOs
listed in 2000-2002
Table 4. Mean of CAR and BHAR of A shares on Shanghai Stock Exchange (BHRm: m-matching firm)
Months/Return IPO Matching firm CAR BHRIPO BHRm BHAR WR
0–1 –0.9996 –0.9976 –0.002 1.0002 1.0027 –0.0025 0.9975
0–3 –0.9817 –1.0048 0.02307 1.0175 0.9905 0.0269 1.0273
0–6 –1.0033 –0.9608 –0.0426 0.9868 1.0175 –0.0307 0.9698
0–12 –1.1367 –1.0278 –0.1089 0.8421 0.9035 –0.0614 0.932
0–18 –1.2489 –1.0938 –0.1552 0.7226 0.7783 –0.0558 0.9284
0–24 –1.3223 –1.13 0.1923 0.669 0.6849 –0.016 0.9768
0–36 –1.5444 –1.2558 –0.2886 0.5147 0.5305 –0.0158 0.9702
Table 5. Mean and t- Statistics of CAR and BHAR. *, ** and *** mean that it is significant at 0.1, 0.05 and 0.01
Return Months Mean Median Std.Dev.SkewnessKurtosisMin. Max. t-statistic Sig.
0–1 –0.0025 –0.0055 0.2131–1.515 10.5136–1.31760.6509 –0.151 0.88
0–3 0.0269 0.0405 0.2782–0.6819 3.5738–1.27640.8272 1.247 0.214
0–6 –0.0307 0.0111 0.4516–2.8202 15.2875–3.1570.8763 –0.875 0.383
BHAR 0–12 –0.0614 0.0549 0.47 –1.885 5.3669–2.4760.5415 –1.683* 0.094
0–18 –0.0558 0.0251 0.4454–1.8782 6.323 –2.12790.7636 –1.613 0.109
0–24 –0.016 0.0043 0.3925–1.3557 8.2853–2.31231.2539 0.542 0.601
0–36 –0.0158 –0.142 0.3567–0.0927 3.6216–1.42091.3853 0.57 0.57
0–1 –0.002 –0.0043 0.2228–1.5615 12.0763–1.40260.7531 –0.114 0.909
0–3 0.0231 0.043 0.2711–0.8661 4.4508–1.35440.8025 1.096 0.274
0–6 –0.0426 0.0107 0.4551–2.7806 13.7181–3.04210.7497 1.205 0.23
CAR 0–12 –0.1089 0.0076 0.5624–1.523 3.9671–2.89210.8262 –2.495** 0.014
0–18 –0.1552 –0.0521 0.5794–1.3606 3.3573–2.82010.8532 –3.451*** 0.001
0–24 –0.1923 –0.0891 0.6053–1.1468 2.986 –2.8181.1703 –4.094*** 0
0–36 –0.2886 –0.245 0.7067–0.4151 0.802 –2.44431.7588 –5.261*** 0
long-term performance of IPO, it is better for us to use the
CAR to explain the degree of long-term underperfor-
mance of IPO.
From Table 4 and 5, the CAR over one year after list-
ing is found to be –10.89%, with a t-statistic of –2.495%,
two years after listing is found to be –19.23% with a
t-statistic of –4.094%, three years after listing is found to
be –28.86% with a t-statistic of –5.261%. The BHAR is
significant at the 0.1 level only for the first year and the
long-run return is –6.14%. It shows that IPO performance
has been poor whichever method is used.Fig.2 shows the
plot of AR, CAR and BHAR for each month within three
years. From Fig.2, for the first six months after the listing,
IPO performance is slightly outperform a matching firm,

140 Liang Peng
but it is underperformed after six months. Although it
rebounds after that period, but the degree is small. In the
long run, the IPO perf ormance has been poor.
5. Explaining for the Long-run Underper-
formance
5.1. Some Determinants with Long-run Per-
formance
Previous research has identified several factors important
in explaining post-IPO performance. These incorporate
the consistent evidence of investor over optimism at issue,
together with the perceived riskiness of the firm and the
degree to which there is information asymmetry between
issuer and investor. Different from the previous studies, in
this section, we conduct multivariate regression analyses
to examine cross-sectional determinants of the aftermar-
ket performance of China's IPOs from the aspect of the
characteristic of a firm. For this purpose, we posit the
following regression model:
0123 4
3 LnTA+
M
ARRSC INDAGE
ββββ β
=++ + (8)
MAR3: the aftermarket performance of IPOs measured
by the market adjusted buy-and-hold return for the three
year aftermarket period excluding the initial-return period;
LnTA: the natural log of total assets before going public;
RSC: the percentage of trade shares; IND: industry
dummy to show the industry is high-tech or traditional;
1-traditional, 0-high-tech; AGE: th e natural log o f a firm's
incorporation age in years at the time of the IPO.
The first fact is the size of the company. Large compa-
nies have less ex ante risk than small companies, respec-
tively, because there is more information about them and
because they are likely to be more closely monitored by
government and regulatory agencies. We therefore hy-
pothesize negative signs on the LnTA. The second fact is
the percentage of tradable shares. The majority of Chi-
nese domestic shares are nontraded shares owned by the
government or by other companies, so fewer than half of
all shares are tradable. We assume that smaller govern-
ment holdings result in better restructuring, so the better
long-run performance a listed company would expect to
have. We hypothesize the positive signs on the tradable
shares (RSC). The third factor is the industry effect. Like
Ritter [19], we examine the industry effect on the IPO
long-run returns. The variable we use is IND: a dummy
variable with the value o assigned to high-tech , and tradi-
tional is 1. If a company belongs to the high-tech industry,
it is expected to enjoy high growth in the near future.
However at the same time, companies with high-tech
features will face more risk, which could be rewarded by
better long-run performance. Therefore, we expect a posi-
tive coefficient for the high-tech dummy. The fourth fac-
tor is the company's incorpo ration age in years at the time
of the IPO. The old companies tend to be more mature
and have stable performances than the younger compa-
nies [19]. They expect to have better long-run perform-
ance. So we hypothesizes it should be positively related to
long-run pe rf or mance.
5.2. Cross-sectional Analysis
In the regression analysis, the results of overall parameter
of the model are presented in Table 6. The variance re-
sults of regression are presented in Table 7. the results of
multivariate regressions are presented in Table8.
From Table 6, the adjusted 2
Ris to increase with the
improvement of model. In model 3, it is 12.6%. From the
regression result of Table 7, sum of squares are from
1.173 in model l to 1.763 in model 3. the significant of F
is lower than 1, it shows that the effect of regression is
significant at 0.01 level.
From Table 8, three variables are in the model, and
they are all at the significant of 0.05 level. As for the rela-
tionship between the company size and IPO long-run re-
turns, the estimation results shows that it have no rela-
tionship with the long-run returns. The variable that
measures the percentage of tradable shares is negative. In
China, after listing, the government is still the biggest
shareholder of listed companies. Unlike the developed
markets, particularly the US, they suggest that the propor-
tion retained by current shareholders reflects the demand
for an IPO [6]. In China, the listing mechanism does not
allow demand to feed back to either the size of issue or
the issue price. Our result is consisten ce with Tian [21] he
concludes that firm performance is positively related to
government ownership when the level of owner ship is
greater than approximately30%. In China, government
ownership is beneficial to firms.
Turing to the relationship between the industry effects,
the coefficient is 0.154, the traditional industry have a
better long-run performance. Incorporation age and
long-run performance are negatively related to each other
at the 0.05 significance level. This is similar to the find-
ings in previous research (Chen&Meng2000). Incorpora-
tion age we calculated is after the shareholding reform.
6. Conclusions
This paper attempts to satisfy the great interest in Chinese
evidence on the long-run performance of 166 A-share
IPOs on Shanghai Stock Exchange between January 2001
and 2002. The main results are the following:
①. When we use shanghai stock exchange Index as the
benchmark to calculate the CAR and BHAR of our sam-
ple within 3 years after listing, either method shows the
IPO performance begins to underperformed than that of
the market index after 6 months of listing and the mean
BHAR and CAR estimated over one year period after
issue is –3.2%(t-statistic=–2.314) –2.05% ( t-statistic=
–1.259), over a two year period after issue is
–11.37%(t-statistic=–5.285) and –14.07% (t-statistic=
–5.427), and a three-year period after issue is –20.88%
(t-statistic=–9.806) and –32.02% (t-statistic=–9.37).

Empirical Study on the Performance of Initial Public Offerings in China 141
Table 6. Results of parameter of the model
Modle R R Square Adj.R Square Std.Error Durbin-Watson
of the Estimate
1 0.307(a) 0.094 0.089 0.2618
2 0.344(b) 0.118 0.108 0.2591
3 0.377(c) 0.142 0.126 0.2564 1.838
a Predictors:(constant), SC
b Predictors:(constant), RSC, AGE
c Predictors:(constant), RSC,AGE, IND
Table 7. Variance results of regression
Model Sum of Squaresdf Mean Square F Sig.
1 Regression 1.173 1 1.173 17.108 0.000(a)
Residual 11.214 164 0.069
Total 12.414 165
2 Regression 1.47 2 0.735 10.951 0.000(b)
Residual 10.944 163 0.067
Total 12.414 165
3 Regression 1.763 3 0.588 8.937 0.000(c)
Residual 10.651 162 0.066
Total 12.414 165
a Predictors:(constant), RSC
b Predictors:(constant), RSC, AGE
c Predictors:(constant), RSC,AGE, IND
d Dependent Variable: BHAR3
Table 8. Results of multivariate regressions: determinants of long-run performance of China's IPOs
Model Unstandardized Standardized t Sig.
Coefficients Coefficients
B Std.Error. Beta
1 contant 0.057 0.067 0.84 0.402
RSC –0.009 0.002 –0.307 –4.136 0
2 contant 0.197 0.094 2.091 0.038
RSC –0.009 0.002 –0.310 –4.22 0
AGE –0.018 0.008 –0.155 –.106 0.037
3 contant 0.163 0.095 1.721 0.087
RSC –0.009 0.002 –0.315 –4.325 0
AGE –0.018 0.008 –0.157 –2.150 0.033
IND 0.084 0.04 0.154 2.109 0.037
One year after listing, WR less than 1 and we obtain a
three-year wealth relative of 0.6826.
②. In order to reduce the influences of incorrect model
setup errors on the research results, we also use matching
firm approach to measure long-run abnormal returns, we
also found the CAR over one year after listing is found to
be –10.89%, with a t-statistic of –2.495%, two years af-
terlisting is found to be –19.23% with a t-statistic of
–4.094%, three years after listing is found to be –28.86%
with a t-statistic of –5.261%. The BHAR is significant at
the 0.1 level only fo r the first year and the long-run return
is –6.14%.
③. By looking at the market adjusted buy-and-hold return
for the three year aftermarket period, and using a
cross-sectional analysis, we have a better understanding
of the long-run performance of Chinese IPOs. From the

142 Liang Peng
characteristic of a firm, the ones with more government
ownership, traditional industry features and the share-
holding reform made later are better performs.
The results show that China’s IPO performed better
than market index returns and the returns of matching
firms within a short period after listing (6 months) but
exhibited significant underperformance in the long run.
The results obtained from this study provide important
information for prospective investors in new issuers to
understand better the Chinese IPO markets. As we men-
tioned before, the aftermarket underperformance is ap-
peared not unique to the developed market, like US. It
also exists in a number of countries, like Canada, Japan
and so on. Chinese IPO market is still a emerging market
and is small relative to the overall economy and many
structural and institutional problems remain, but it ap-
pears that the development of the market is approaching
maturity, holding out promising long-term prospects.
7. Acknowledgement
I would like to thank Professor Hamada Yasuyuki for a
number of helpful comments on my paper. I also thank
my research lab colleagues for their friendship. All erro rs
are the author’s responsibility.
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