Modern Economy, 2011, 2, 561-568
doi:10.4236/me.2011.24062 Published Online September 2011 (http://www.SciRP.org/journal/me)
A New Revisit Evidence of Stock Markets’
Interrelationships in the Greater China
Chu-Chia Lin, Chung-Rou Fang, Hui-Pei Cheng
Department of Economics, National Cheng-chi University, Taipei, Chinese Taipei
Received April 4, 2011; revised May 15, 2011; accepted May 30, 2011
Abstract
This paper investigates the recent stock markets’ interrelationships in Greater China (China, Hong Kong, and
Taiwan). The main goal is to use more detailed and new daily stock market data from 2005/7 to 2010/5 to
offer valuable and complementary insights on financial integration among these economies. From the em-
pirical analysis, we found that China’s stock market has a positive impact on the other Greater China econo-
mies, but the reverse is not true. In addition, Hong Kong’s stock market also has a significantly positive im-
pact on Taiwan, but not on China, and the impact of Hong Kong on Taiwan is larger than that of China on
Taiwan. This result is consistent with the previous empirical findings that the segmented and integrated
China stock market is mixed, and this result implies that the China stock market is still “partially integrated”
with the other Greater China stock markets after the 2008 global financial crisis.
Keywords: China Stock Market, Greater China, Financial Integration, Global Financial Crisis
1. Introduction
The economic reforms begun in 1978 have led to the
rebirth of the stock markets in China. Later, the acces-
sion of China to the WTO and stock market reforms in
2003 and 200 51 have been heralded as a watershed event,
making a distinct break in China’s economic relations
with the rest of the world. The Sh anghai Stock Exch ange
and the Shenzhen Stock Exchange are the two major
emerging Chinese capital markets, and are linked via the
national stock exchange automated quotation system.
The Shanghai Stock market was officially opened in
1990 and the Shenzhen Stock Market was inaugurated in
1991. Two types of stocks are traded in th e two markets:
“A” shares and “B” shares. “A” shares are restricted to
Chinese citizens and denominated in the Chinese cur-
rency, the Yuan or Renminbi (hereafter RMB), while
“B” shares can be bought and sold only by foreigners
and settled in foreign currencies (US dollars for Shang-
hai, Hong Kong dollars for Shenzhen). In this study, we
focus on the analysis of “A” shares markets since the
“B” shares market has been losing its appeal to foreign
investors and “A” shares dominate “B” shares in terms of
the number of listed companies, trading volume, and
market capitalization.2
As the PRC gradually opens her markets to interna-
tional trade, the concept of Greater China has begun to
take shape. Thus far, the neighborhood region or culture
cluster of Greater China consists of China, Hong Kong,
and Taiwan.3 Improved relationships between these re-
gions, coupled with th e return of Hong Kong to the PRC
on July 1, 1997, have strengthened ties within Greater
China. Since the three economies adopt export-led poli-
cies, there have been many studies investigating the
economic relationships within Greater China which want
to know whether the interactions are becoming stronger
due to the growing trade relations among them. There-
fore, this paper will analyze the relationship among the
stock markets of Greater China. We are interested in
these economies because Greater China has led the world
in economic growth for the last decade, and has become
one of the major factors in the world economy. It is vir-
tually certain to become even more important in the
1China’s stock market reforms, such as the qualified foreign institu-
tional investors (QFII) policy in 2003, increased the proportion o
f
shares that were freely tradable in the markets in 2005. The QFII pol-
icy allowed foreign institutional investors to invest a meagerUS$ 10
b
illion in domestic equities at a time when market capitalization in
2007 grew to exceed US$ 3 trillion (see [1]).
2There are a lot of studies devoted to detailed discussion of this topic,
such as [2-5], among others.
3[6] and [7] discussed the possibility of market integration or market
clustering around the world.

C. C. LIN ET AL 562
years to come. Rapid economic growth in these econo-
mies has been accompanied by an increase in the size of
their stock markets. Along with the increased importance
of these economies as leaders of the capital markets in
the Asian economy, foreign participation in stock mar-
kets and foreign interest in the behavior of the stock
markets has been increasing in recent years. In addition,
since these economies have implemented significant
capital liberalization and domestic financial deregulation
in recent years, we also want to use capital mobility and
financial integration to investigate stock market interre-
lationships in Greater China after the 2008 global finan-
cial crisis.
The remainder of this paper is arranged as follows.
Section 2 provides a brief review of existing work and
outlines our contribution to the literature. Section 3 de-
scribes the data and empirical methodology applied in
this study. Section 4 reports the estimation results. Fi-
nally, Section 5 concludes the main findings of our
analysis.
2. Literature Review
There have been several studies examining the dynamic
interrelationships among Greater China and developed
markets, including [3-5,7-14]. Among them, [9] investi-
gated the status of real and financial integration of
Greater China by using monthly data on 1-month inter-
bank rates, exchange rates, and prices. It was found that
China and Hong Kong appear to experience increasing
real and financial integration while Hong Kong and Tai-
wan show no substantial gain in the integration process.
However, the concept of integration is difficult to define
and measure precisely. In another approach to assessing
integration, [9] suggested that one could compare the
expected yield on similar assets (e.g. stock market) in
different economies in future studies. In addition to [8]
and [3], [9] examined the dynamic interrelationships
between the share markets of Greater China from 1992 to
2001 in detail, they examined the data before and after
the Asian crisis of 1997-1998 by using VAR models.
They found that Hong Kong and Taiwan have a strong
contemporaneous relationship, but that the mainland
markets are relatively isolated from the other two mar-
kets. [7], [13], and [14] had similar findings. However,
whether the recent modest growth in interrelationships
within Greater China is due to the occurren ce of the 2008
global financial crisis or the greater integration of the
Chinese economy into the world economy will require
more detailed studies. In response, the main goal of this
paper is that we try to use the more detailed and recent
stock market daily data from 2005/7 to 201 0/5 to fill this
gap, in order to offer valuable and complementary in-
sights on integration between the Greater China econo-
mies.
In addition, there is also a lot of literature on the stock
market interdependence and capital mobility between
China and the other Asian countries, such as [5,6,15-22]
and so on. Among them, [5] and [6] discussed the stock
market interdependence between China and Asian Newly
Industrialized Economies (NIEs), and found that after the
Asian crisis, the Chinese equity markets became more
interdependent among themselves, although Hong Kong
remained non-influential. However, the studies about
capital mobility in East Asia are quite different, and early
previous studies show the lower degree of capital mobil-
ity in developing coun tries. For ex ample, [17] studied th e
experiences of developing countries in Africa, Asia,
Eastern Europe, and Latin America. They found that
these countries often use reserve requirements to depress
capital flow and mitigate the impact on the domestic
money supply. Based on the International Monetary
Fund’s Annual Report on Exchange Arrangements and
Exchange Restrictions, [19] developed a capital control
index to measure the exten t of capital mobility. He found
that imperfect capital mobility is a common fact in most
developing countries. In addition, [18] suggested that
capital mobility facing developing countries is not as
high as some studies have concluded. In particular, tak-
ing sterilization into account sharply lowers estimates of
capital mobility. However, [20] applied the time-varying
parameter estimates of the degree of capital mobility in
NIEs. His estimates illustrated the different processes of
capital accounts and domestic financial liberalization in
the region, and the empirical results indicated that the
degree of capital mobility has been increasing substan-
tially in these countries. In addition, [21] explored the
Saving-Investment correlation of East Asian countries in
relation to international capital mobility. Their results
were consistent with the fact that capital mobility in East
Asia has increased but is still lower than that among the
OECD countries. [22] have a similar description. Overall,
since quite a few papers address the issues of capital
markets in emerging economies and their relation to the
performance in the stock markets, the other goal of this
paper is to combine these two topics, using capital mo-
bility to explain the stock market interrelationships in
Greater China after the 2008 global financial crisis.
3. The Data and Empirical Methodology
3.1. Data
Since the 1990s, the influence of the mainland’s eco-
nomic and financial development on the Hong Kong
stock exchange has increased. The first listing of a

C. C. LIN ET AL563
t
mainland China company took place in 1993 through the
system of the so-called H-shares (shares in mainland
China companies listed in Hong Kong). Today, a large
number of mainland companies are listed in Hong Kong.
The main exchange company merged with the Hong
Kong futures exchange and their clearinghouses in 1999.
In addition, in the case of Taiwan’s stock market, its
stock exchange was formed in 1961 and trading began in
1962. Both equities and fixed income are traded on the
Taiwan stock exchange. However, compared to other
developed countries, there are a number of restrictions in
place. For example, the short-selling of stocks is prohib-
ited and there are ceiling and floor limits on daily price
changes of plus and minus 7%.4 Overall, as one of the
indicators of the Greater China stock market, [7] show
that the number of listed companies grew extremely
quickly in mainland China, with the number of compa-
nies in 2005 more than four times, that in 1995. Similarly,
the number of listed companies in Hong Kong and Tai-
wan more than doubled dur ing the same period.
Since the accession of China to the WTO, stock mar-
ket reform,5 and relaxing the control of RMB in 2005/7,6
this study applied a daily data from 2005/7 to 2010/5 and
it is available from the Taiwan Economic Journal data-
base (TEJ).7 The dataset includes the China Shanghai A
share stock index, Taiwan weighted stock index and
Hong Kong Hang Seng stock index. Following [3] and
[9], we adapt Shanghai’s A share stock index to repre-
sent China’s stock market.8 The reason we apply the A
share index is that its trading value is much larger than
the B share’s, and the number of listed companies in the
A share index is much more than that in the B share in-
dex. Moreover, as in [3], the B share index is not nor-
mally considered by Asian fund managers as a serious
component of Asian portfolios. Therefore, we believe
that the Shanghai A share stock index should provide
more information about China’s stock market and it
could also capture the main trend of China’s stock ex-
change. In order to know the interrelationships among
the stock markets in Greater China, we use the stock
markets’ returns to investigate the relationship in this
study.
3.2. Methodology
Since most time series variables have a unit root, one
cannot use those data without considering their unit root
property. Otherwise, a spurious regression problem may
occur and the results may not be reliable. To avoid this
problem, we have to check whether the variables applied
in this study have a unit root or not. Therefore, we use
the ADF test first to check the unit root property as fol-
lows.
The ADF test is called the augmented Dicker-Fuller
test, and the original test was developed by [23]. By con-
sidering the variables with autoregressive process with
order p (AR(p)), the ADF test can be applied to check
whether the high order autoregressive variables have unit
root property. Let us illustrate the ADF test as follows:
112 21tt tptpt
yy yyty


 


 

2
~0,
tN
,


 (1)
where t is the stock returns, 1tp
are the
first difference of the stock returns, t is the trend of the
stock returns, 1t
y,,
t
yy


y

is the lagged term of the stock re-
turns, and t

is an identical independent distribution
(i.i.d.) white noise process. From Equation (1), 1


represents that the data in equation have unit root prop-
erty, and we say that the data is nonstationary. On the
other hand, 1 

represents that the data have no unit
root, thus they are a stationary process.9
In addition, if the data have a nonstationary property,
we have to check if they have a cointegration relation-
ship, and it implies that all variables have a long run
equilibrium relationship.10 Therefore, we must examine
whether the nonstationary variables have a cointegration
relationship or not. If the cointegration relationship does
not exist, then we take the first difference to deal with
the nonstationary property. Thereafter, we can use the
vector autoregressive method (VAR) to analyze the rela-
tionship among the variables.
4There are a lot of studies devoted to detailed discussion of the Greater
China stock markets, such as [2-5], and [7], among others.
5The reform of China’s stock market, such as the QFII policy in 2003,
has increased the proportion of shares that are freely tradable in the
market in 2005. It is expected that total shares need by QFII will reach
10% of foreign shares in A shares market a ft e r 2005 (see [5]).
6In the end of 2009, the foreign exchange reserve of China is abou
t
US$2,399,152 million, and it is the number 1 in the world. Relaxation
of RMB controls is expected to have great influence on the world
economy.
7For the details of data obtained, please see the TEJ website:
http://www.tej.com.tw.
8There is a little difference from [3], who use value-weighted stock
returns in Shanghai and Shenzhen A shares; here we only use the re-
turns of Shanghai A shares as an indicator of China’s stock market.
The reason is that the trading value of Shanghai shares is larger than
that of Shenzhen A shares; for example, the trading value of Shanghai
A shares is about twice that of Shenzhen A s h ares in 2009.
Consider a VAR(p) process as follows:
011ttptp
YAAYAY t



 ,

~0,
tN



(2)
where contains
t
Y1n

variables and ti Y,
1, 2i,, p

 are lagged dependent variables. From
above, we consider the appropriate order selection in the
ADF test and VAR(p) process. Here we use the Akaike’s
information criterion (hereafter AIC, see [24]) for the
model fitting. AIC is defined as:
9If neither mean nor autocovariance depend on the date t, the process
t
10 For details, see [25].
y is called a (weakly) stationary process.

C. C. LIN ET AL 564
 

2lnmax2
A
IC MlikelihoodM , (3)
where M is the number of estimated parameters in the
model. The optimal order of the model is chosen by the
value of M, which is a function of p, such that AIC(M) is
minimal.
After choosing the optimal order for the VAR(p) proc-
ess, we can transfer the VAR(p) process to a moving
average infinite (MA()) as follows:

112 2, tttt
Y

 

  (4)
Then, we can calculate the impulse response function.
The element of
s

in row i and column j can be ex-
pressed as follows:
,
,its ij
j
t
y




, (5)
where
j
t

is the jth variable’s innovation at data t, and
,its is the i-th variable at date t+s. The impulse re-
sponse function means how much the ith variable at date
t+s will change ,ij
y

units, as when the jth variable’s
innovation increases by one unit at data t. By using the
impulse response function, we can implement impulse
response analysis (hereafter IRA) and also plot the im-
pact of one unit increase in the j-th variable’s innovation
at t on i-th variable at date t+s. At the same time, we can
find the response of the key variables when shock occurs
in the other variables. In our paper, we employ IRA to
analyze the relationship among the stock markets.
4. Empirical Findings
4.1. Basic Statistics Description
From Table 1, we can see that mean and standard de-
viation of China are higher than those of Hong Kong and
Taiwan, which means that Chinese stock market is more
profitable but riskier. Consequently, the higher returns
attract more international capital flow into this stock
market and then reflect the higher economic growth rate
in China.11 Finally, the skewness and kurtosis among all
economies reflect that the financial time series data have
fat tail properties.
Table 1. Basic statistic description of stock returns, 2005/7
to 2010/5 unit: %
Economies Mean S. D. Skewness Kurtosis
China 0.0489 2.0944 –0.5590 5.6337
Hong Kong 0.0236 1.9820 0.1684 10.6260
Taiwan 0.0070 1.5088 –0.3590 5.4472
Source: Taiwan Economic Journal. Note: China = Shanghai A share stock
returns; Taiwan = Taiwan stock returns; Hong Kong = Hang Seng stock
returns.
Table 2 is the annual growth rate of the number of
listed companies from 2006 to 2010. Compared to [7]
which show the number of China’s listed companies
more than quadrupled from 1995 to 2005, but those in
Hong Kong and Taiwan grew by only half as much dur-
ing the same period, we found that the annual growth
rate of Hong Kong is the largest among all three from
2005 to 2010. Since Hong Kong is more international-
ized, international investors interested in profiting from
China’s rapid economic growth have tended to go
through Hong Kong recently.
From Table 3, the results of the ADF test show that
stock returns in the three economies have no unit root
property. This means that all variables have no persistent
impact, and the current effect of one market shock on the
others will disappear in the future. Hence, we can im-
plement the VAR estimation and IRA to proceed with
our analysis in the following section.
4.2. Estimation Results
4.2.1. VAR Es ti mation
Since the lag length is chosen as the minimum AIC value,
it requires only one lagged period for estimation in this
model. In addition, in order to deal with the 2008 global
financial crisis, we construct a dummy variable into our
estimation as well. Therefore, we set the dummy variable
representing the period after September in 2008.12
In Table 4, one may see that the explanatory power
(adj. ) of each equation is very low, and it implies
that the daily returns contain too little information to do
any meaningful prediction. Among them, China’s stock
market is not significantly influenced by all returns of
Hong Kong and Taiwan, but Hong Kong’s stock market
is significantly influenced by the first lagged returns of
China (CN(–1)) and Taiwan (TW(–1)). In addition, Tai-
wan’s stock market is significantly influenced by the first
lagged returns of China (CN(–1)), the first lagged returns
of Hong Kong (HK(–1)), and the first lagged returns of
Taiwan (TW(–1)). Furthermore, the dummy variable
shows that the 2008 financial crisis had no significant
impacts on all markets. The insignificant coefficient im-
plies that the effect of the financial crisis may have
gradually decayed after 2008.
2
R
Overall, from Table 4, we can see that the interactions
among all markets are complicated, and some findings
such as China having an insignificant effect on all vari-
ables are also difficult to explain. Since the VAR model
is a reduced form, we cannot obtain any exact result.
Therefore, we find that the explanatory power is poor in
12After September in 2008, the US Government took control of Fannie
Mae and Freddie Mac, which are the major Federal Home Loan
Mortgage Corporations in the US, and Lehman Brothers Holdings Inc.
filed for bankruptcy.
11China’s economic growth rate was 11.6% in 2006, 13% in 2007,
9.0% in 2008, and 8.7% in 2009; the average economic growth rate in
the past four years is the largest in Greater China.

C. C. LIN ET AL565
Table 2. Annual growth rate of the number of listed com-
panies, 2006 to 2010 unit: %.
Economies Average
China 5.5222
Hong Kong 24.0642
Taiwan 7.0912
Source: This st udy. Note: China = Shanghai A share stoc k market; Taiwan =
Taiwan stock market; Hong Kong = Hang Seng st ock market
Table 3. Stationary tests (the ADF test).
Economies Statistic (No trend) Statistic (with Trend)
China –13.5183** –7.5173**
Taiwan –6.8128** –6.8097**
Hong Kong –9.1249** –9.1565**
Source: This study. Note: 1. ** represents 5% significance level. 2. The
stationary test applied in this paper is the ADF test. The 5% critical value
without trend is -2.8639, and the 5% critical value with trend is -3.4138. 3.
China = Shanghai A share stock returns; Taiwan = Taiwan stock returns;
Hong Kong = Hang Seng stock returns.
Table 4. VAR for Greater China.
Regressor CN HK TW
Intercept 0.0665 0.0587 –0.0100
(0.0794) (0.0746) (0.0565)
CN(-1) –0.0097 –0.1114** –0.0461*
(0.0335) (0.0315) (0.0239)
HK(-1) 0.0619 0.0495 0.1657**
(0.0430) (0.0404) (0.0306)
TW(-1) –0.0834 –0.0885* –0.0760**
(0.0532) (0.0500) (0.0378)
Dummy –0.0464 –0.0799 0.0446
(0.1303) (0.1224) (0.0927)
Adj. R-squared –0.0008 0.0132 0.0240
Note: 1. The figures in the parenthesis are the standard deviations. 2. CN =
Shanghai A share stock returns; HK = Hang Seng stock returns; TW =
Taiwan stock returns. 3. * represents 10% significance level and *
*represents 5% significance level. 4. For the days between 2005/7/1 and
2010/5/31, Dummy equals to zero; else for the days between 2008/9/1 and
2010/5/31, Dummy equals to one.
Table 4 and this means that the predictive power of all
markets’ lagged returns is very low. Generally speaking,
since it is difficult to obtain the dynamic interaction rela-
tionships among the markets, we will consider IRA in
the next section to obtain the exact dynamic interaction
among all markets.
4.2.2. Impulse Response Analysis
The relationship among all economies in this study could
be understood by implementing IRA. Moreover, IRA
could also show that the dynamic interaction among all
economies and the reflection of the impact of a shock
from different economies. All empirical results are
shown in Figure 1 as follows.
Firstly, when an external shock occurs in China, we
find that the other Greater China stock markets have a
significantly positive response and the impact will con-
tinue for only about one period (one day). It appears that
China’s shock benefits other stock markets but the dura-
tion of this good impact is very short. However among
them, the positive response of the Hong Kong market
will turn to a significantly negative effect, which means
that the external capital which flows in Hong Kong will
gradually move toward China after the shock. However,
although the other Greater China stock markets have a
significantly positive response, the reverse is not true.
This implies that China restrains its capital mobility
more than the others. This empirical finding is consistent
with [3], who pointed out that “China’s stock market is
relatively isolated from the other two - it has little effect
on either Hong Kong or Taiwan and is, in turn, little af-
fected by them. However, after Asian crisis, this isolation
of China was less marked, it was only influenced by
Hong Kong but not Taiwan.”13 In addition, since China’s
economic growth in recent years is higher than that of
the data which is adopted by [3],14 China’s impact be-
comes more significant than before.
Secondly, we could find that the shock occurring in
Hong Kong’s stock market has a positive affect on Tai-
wan’s economy, but not on China’s. Since the amount of
Taiwan’s response is larger than that of China’s response,
this implies that the relationship between Taiwan and
Hong Kong is closer than that between Taiwan and
China. The reason is obvious in that since Taiwan gov-
ernment constrains direct investment into China, many
Taiwanese companies have to transfer their capital
through Hong Kong to China. Consequently, the amount
of Taiwan’s response to Hong Kong’s shock is larger
than that of China’s response. This finding is also con-
sistent with [2] and [3], who found Hong Kong to be the
most influential in Greater China.
Finally, the shock of Taiwan’s stock market has insig-
nificantly negative impact on the Hong Kong and China
stock markets, which implies that the recent investment
and political environment of Taiwan is worse than those
in Hong Kong and China. Since both the degree of capi-
tal mobility and th e economic growth rate of Ho ng Kong
are higher than those of Taiwan,15 more foreign capital
will flow into Hong Kong stock market. This finding is
also supported by [20] and [21], who indicated that the
degree of financial liberalization and capital mobility in
Hong Kong is the highest among the Asian NIEs.
Overall, from the above empirical results, we found
that it is a common fact that only the shock occurring in
China will have a significant impact on the other econo-
13In [3], they find that China’sstock market could be affected by Hong
Kong’s stock market after the Asian financial crisis. Our finding here
is that China’sstock market may not be obviously affected by Hong
Kong’s stock market, because the Chinese government has morepower
to control its market than the other governments do.
14The economic growth rate of China from 2005 to 2008 was 10.4%,
11.6%, 11.9%, and 9% respectively, but the economic growth rate in
2001 was 7.5%.
15The economic growth rate of Hong Kong in 2006 is 7.0% and 6.4%
in 2007, respectively, and it is higher than the economic growth rate o
f
Taiwan.

C. C. LIN ET AL 566
-0.5
0.0
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1.0
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Res pons e of C N t o H K
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1.0
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Res pons e of CN t o TW
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Res pons e of HK t o CN
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0.8
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Res pons e of TW t o TW
Response to Cholesky One S.D. Innovations ± 2 S.E.
Figure 1. Share market interrelationships in Greater China from 2005/7 to 2010/5 (daily data). Note: 1. The optimal lag pe-
riods selected is 1 (days); 2. The definition of economies is the same as Table 1; 3. The real line is the impulse response to
Cholesky one S.D. for the market in question, while the dotted line is a confidence interval corresponding to two S.D. The
impact effect is significant if the confidence interval does not include the zero line.
speaking, the China A- share market has long been con-
sidered to be segmented from the other global financial
markets. As a result, even though China has become a
member of the WTO and its government has committed
to the gradual opening of the A-share market over the
next several years, we found that China’s stock market
has a positive impact on the other Greater China econo-
mies but not vice versa. In addition, Hong Kong’s stock
market has also a positive impact on Taiwan’s economy,
but not on China’s, and the impact of Hong Kong to
Taiwan is larger than that of China to Taiwan. This result
is consistent with the previous empirical findings that the
segmented and integrated China stock market is mixed
(see [5]). In addition, [11] found that the volatilities of
most of Greater China market and other stock market
indices have significant asymmetric coefficients, where
mainland China’s stock market is not affected by both
contemporaneous and delayed “bad news”. The overall
findings provide evidence to support the view that the
China stock markets are “partially integrated” with the
international stock markets after the 2008 global finan-
cial crisis.
mies, but the reverse is not true. This means that China
and other Greater China stock markets are complemen-
tarily related, and they will benefit from the growth of
China’s stock market. Additionally, international capital
mobility is a well-documented phenomenon after the
financial deregulation and capital liberalization pursued
in the Asian developing countries during the last two
decades. Increasing integration of capital markets has
promoted a surge of private capital of developed coun-
tries flowing into developing countries. Therefore, the
financial deregulation process has led many to argue that
stock markets across the world are becoming increas-
ingly integrated (see [5]). A large number of empirical
studies have paid attention to measure the degree of
capital mobility in these Asian developing countries,
though the findings are quite different.16 Generally
16Consequently, one market that has recently stimulated high interest
with regard to the question of integration is the China stock market.
For example, some studies including [3] and [6] found modest growth
in the interrelationship among the mainland China stock market, Hong
Kong stock market, and Taiwan stock market after the Asian financial
crisis. However, [2] and [26] found little evidence that other Asian
markets have great influences on the China A-share market.

C. C. LIN ET AL567
5. Concluding Remarks
This paper investigates the interrelationships among the
indices of the mainland China stock market and those in
the neighboring markets of Greater China. Since the con-
cept of financial integration is difficult to define and
measure precisely, one important approach is to compare
the expected yield on similar assets (stock markets) in
different economies (see [10]). In the literature about the
Greater China stock market, the mainland market is rela-
tively isolated from the other two markets considered.
However, whether the growth of interrelationships in
Greater China is due to the occurrence of the Asian crisis
or due to the closer integration of the China economy into
the world economy requires more decent studies (see [3]).
Therefore, the main goal of this paper is to use newer, and
more detailed daily stock market data from 2005/7 to
2010/5 to fill this gap, in order to offer valuable and com-
plementary insights on financial integration within
Greater China after the 2008 global financial crisis.
Additionally, international capital mobility is a well-
documented phenomenon after the financial deregulation
and capital liberalization pursued in the Asian develop-
ing countries during the last two decades. Increasing in-
tegration of capital markets has promoted a surge of pri-
vate capital from developed countries flowing into de-
veloping countries. Therefore, the financial deregulation
process has led many to argue that stock markets across
the world are becoming increasingly integrated (see [5]).
A large number of empirical studies have paid attention
to measure the degree of capital mobility in these Asian
developing countries, but the findings are quite mixed.
Overall, since quite a few papers address both the issues
of capital markets in emerging economies and the rela-
tionship to the performance in the stock markets, the
another goal of this paper is to combine these two issu es
by using capital mobility to explain the stock market
interrelationships in Greater China.
From the empirical analysis in this paper, we found
that China’s stock market has a positive impact on the
other Greater China economies, while the reverse is not
true. In addition, Hong Kong’s stock market also has a
significantly positive impact on Taiwan’s economy, but
not on China’s, and the impact of Hong Kong on Taiwan
is larger than that of China on Taiwan. This result is con-
sistent with the previous empirical findings that the seg-
mented and integrated China stock market is mixed, and
the result implies that the China stock market is still
“partially integrated” with the international stock mar-
kets after the 2008 global financial crisis.
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