J. Service Science & Management, 2009, 2: 348-352
doi:10.4236/jssm.2009.24041 Published Online December 2009 (www.SciRP.org/journal/jssm)
The Transmission of Pricing Information of
Dually-Listed between Hong Kong and New
York Stock Exchange
Shuangfei LI, Shou CHEN
School of Business Adiministration, Hunan University, Changsha, China
Received July 31, 2009; revised September 5, 2009; accepted October 29, 2009.
ABSTRACT
The study investigates the transmission of pricing information between Hong Kong Stock Exchange and New York Stock
Exchange. Using the opening and closing stock prices of these two markets from Jan. 2003 to Apr. 2007 with the
method of Seemingly Unrelated Regression, we draw the conclusions that: 1) intraday returns of Chinese dually-listed
stocks is influenced more obviously by Hang Seng Index than Dow-Jones Average; 2) transmission of pricing informa-
tion is only from New York to Hong Kong; 3) intraday returns of stocks from New York Stock Exchange has a remark-
able influence on that of the next day in Hongkong market, but the stocks price of Hong Kong Stock Exchange has no
relation with which of New York Stock Exchange.
Keywords: Information Tra n smi ssi o n, D ually-List ed, St o ck Price
1. Introduction
In recent years, there have been quite a number of Chi-
nese companies listed in foreign capital markets. Ac-
cording to the China Securities Regulatory’s Statistics,
up to early 2006, there are a total of 120 Chinese compa-
nies listed in foreign capital markets. The market value
of China's A-Shares reaches 9 trillion RMB, while the
market value of overseas listed enterprises reaches 11
trillion RMB. At the mean time, Along with China's fi-
nancial industry is opened to external and to deepen fi-
nance reformation, more and more people begin to pay
attention to the relationships between Chinese market
and overseas securities market. The interdependence of
international equity markets has been examined exten-
sively.
The interdependence of international equity markets
has been examined extensively. Using stock market in-
dices, Koch and Koch examined relationships between
daily closing values of eight national stock indices for the
years 1972, 1980 and 1987.Their result suggested that
international stock market has grown an more interdep-
endent over time, and increased equity market interdep-
endence has been concentrated primarily between mark-
ets in neighboring countries and between markets whose
trading hours overlap [1].
Using multivariate GARCH models, Zhao L. and
Wang Y. point out there is anasymmetry in pred ictability
of the volatility of A share verses B share. Before the
openness to domestic inverstors of B share in Feb. 2001,
the volatility of B share and A share are relatively inde-
pendent. After that, there is a prominent volatility spill-
over effect from A share to B share [2].
However, using the dually-listed stock prices will de-
scribe transmission of pricing information better than
using the indices [3–4]. Using the daily opening and
closing stock prices of seven Japanese corporations that
are dually listed on the New York Stock Exchange
(NYSE) and the Tokyo Stock Exchange (TSE), Lau and
Diltz conclude that market imperfections th at may inhibit
information transfer between TSE and NYSE stock re-
turns are not readily apparent and that international list-
ings do not give rise to arbitrage opportun ities [5].
Bae investigates the transfer of pricing information
between the Hong Kong Stock Exchange (HKSE) and
the London Stock Exchang e (LSE). They find that HKSE
overnight returns respond significantly to changes in LSE
intraday returns, but the transmission pro cess is not com-
pleted at the opening of the SEHK; LSE overnight re-
turns respond significantly to changes in HKSE intraday
returns, but the transmission process is not completed at
the opening of the LSE, either; the impact is stronger

The Transmission of Pricing Information of Dually-Listed between Hong Kong and New York Stock Exchange349
t
moving from the LSE to the SEHK [6].
Kalok et al. using high frequency data to study how
overnight price movements in local markets affect the
trading activity of foreign stocks on the NYSE. They
found that local price movements affect not only the
opening returns of foreign stocks , but also their returns in
the first 30-min interval. The magnitude of local price
movements is positively related to price volatility of for-
eign stocks, and this relation is stronger at the NYSE
open but weaker afterward. However, local price move-
ments cannot account for intraday variations in trading
volume. They interpret the result as evidence that the
trading activity of foreign stocks on the NYSE is related
more to liquidity trading of US investors and less to local
market information [7].
Chinese enterprises have a shorter history in listing in
foreign capital markets, Research on the relationships
between Chinese Capital Market are in progress. This
study is important due to the growing number of firms
that choose for their common stock to be traded on for-
eign stock exchanges. By examining the transmission of
pricing information, optimal investment decision for in-
vestors from home and abroad can be made.
The remainder of this study is organized as follows.
Section 2 describes the data and method used in the study,
while Section 3 summarizes the empirical results. Finally,
Section 4 presents the conclus i ons.
2. Data and Method
2.1 Data
Using opening and closing stock prices of Chinese firms
which are dually-listed on the Hong Kong and New York
stock exchanges over the period of 2003 to April 2007.
The firms’ New York listings are in the form of Ameri-
can Depository Receipts (ADRs). We eliminate two
firms due to unavailability of prices for the entire period.
Therefore, the final sample consists of seven firms, the
length of time series is 1043. Hong Kong Stock
Exchange and New York Stock Exchange opening and
closing prices are obtained from www.yahoo.com.cn.
(Table 1)
2.2 Method
The specification and methodology used in this study are
a refined version of those employed by Lau, S T (1994)
and Becker K H. (1990). Intraday and overnight returns
are calculated in the following manner. and
are the daily opening and closing stock prices,
and are the intraday return and overnight re-
turns:
t
open
t
close
t
oc t co
100*log(/ )
tt
occlose open

;
1
100*log( /)
tt
coopenclose t

;
All return series are adjusted for dividend payment and
stock split. More specifically, we define the overnight
return and the intraday return for the HKSE and NYSE
as follows:
oc
t
H
K: The SEHK intraday return on day t,
co
t
H
K: The SEHK return for the overnight period
ending on day t,
oc
t
NY : The NYSE intraday return on day t,
co
t
NY : The NYSE return for the overnight period end-
ing on day t.
The Hong Kong Stock Exchange opens at 10:00 hours
and closes at 16:00 hours, and New York Exchange pre-
cedes Hong Kong by half an hour. Thus, on a given
trading day, the trading times are overlap, and the
Table 1. The description of sample firms
Firms Name Exchange Code Transform ProportionIndustry Listing Date
SINOPEC SHANGHAI ADS SHI (0338) 1:100 Energy 07/26/1993
CHINA TELECOM CP LTD CHA (0728) 1:100 Communication 07/22/2002
BRILLIANCE CHI CBA (1114) 1:100 Autocar manufacture 10/22/1999
GUANGSHEN RAIL CO LT GSH (0525) 1:50 Transportation 05/14/1996
ALUMINUM CP CHIN ADS ACH (2600) 1:100 Metallurgy 12/12/2001
HUANENG POWER INTL HNP (0902) 1:40 Electric power 01/22/1998
CHINA EASTERN AIRLNE CEA (0670) 1:100 Aviation 02/05/1997
Note: The ADR in Exchange code is the code on NYSE and corresponding code on HKSE each. Transform proportion is the number which one
ADR respond to H share.

The Transmission of Pricing Information of Dually-Listed between Hong Kong and New York Stock Exchange 350
open
Hong Kong
oc
t
H
K
1
oc
t
H
K
co
t
H
K
1
oc
t
NY

co
t
NY
close
1
co
t
NY
American
close
open closeopen
close open
Figure 1. The chronological sequence of events in the New York Stock Exchange (NYSE) and the Hong Kong Stock Exchange
(HKSE)
chronological sequence is as shown in Figure 1.
First of all, we give our attention to the transmission of
pricing information between NYSE and HKSE. We
specify four equations that relate to the transmission of
pricing information between market participants in HK-
SE and NYSE. The first two equations model the trans-
mission of pricing information from the NYSE to the
HKSE.
Specifically, we first examine the effect of changes in
the intraday NYSE returns,, on the following
day’s HKSE overnight return, by estimating the
following regression specification:
1
oc
NYt
co
t
HK
1) Regression Equation (1) illustrates the effect of
changes in the intraday NYSE return on day t-1, on the
following day's HKSE overnight return,
11 11
co oc
tt
HKNY t



  
t
(1)
2) Equation (2) illustrates the effect of changes in
the intraday NYSE return on day t-1, on the following
day’s HKSE intraday return,
2212
oc oc
tt
HK NY



   (2)
3) Equation (3) illustrates the effect of changes in
the intraday HKSE return on day t-1,on the same day’s
NYSE overnig ht ret ur n,
133 13
co oc
tt
NYHK t



  

(3)
4) Equation (4) illustrates the effect of changes in
the intraday HKSE return on day t-1,on the same day’s
NYSE intraday return,
144 14
oc oc
tt
NYHK t



  

(4)
where it

（i＝1,2,3,4）is a stochastic disturbance term.
If the one stock exchange responds to changes in re-
turns on the other, then estimation of equation should
produce a significan t positive slope coefficient.
The empirical specifications (1) and (3) each contain
variables that, while not strictly simultaneously deter-
mined, nevertheless share a considerable amount of
common trading time. Upon consideration of our em-
pirical specification and the types of hypotheses we are
testing, we employ a four-step instrumental variables
procedure that differs slightly from that of Koch [1] and
Lau S.T. [5].
First, we estimate market model regressions for
and
oc
t
NY
oc
t
H
K using ordinary least squares:
5 5
oc oc
t
NYDJA 5tt



 (5)
66 6
oc oc
tt
HKHSI t



 (6)
Where is intraday return on the Dow Jones In-
dustrials Index, and
oc
t
DJA
oc
t
H
SI is intraday return on the Hong
Kong Hang Seng Index.
Secondly, the resulting parameter estimates are used to
create instruments (i.e. predictions), and
for variables and Equa-
tions (1) and (3), respectively.
oc
t
YN
ˆ
oc
t
HK
oc
t
KHˆoc
t
NY
oc
t
oc
tDJAYN 55 ˆ
ˆ
ˆ
  (5’)
oc
t
oc
tHSIKH 66ˆ
ˆ
ˆ
  (6’)
Third, the instrumental variables are substituted into
Equations (1) and (3), yielding:
t
oc
t
co
tYNHK 7177 ˆ
   (1’)
t
oc
t
oc
tKHNY 81881 ˆ
  (3’)
Finally, the parameters of the system of Equations (1’),
(2), (3’) and (4) are estimated jointly using the Seem-
ingly Unrelated Regression (SUR) method. By using the
estimates of the covariance of residuals across equations,
the SUR method improves the efficiency of the parame-
ter estimates.
3. Empirical Results
We believe that the instrumental variables produced in
the manner described above are appropriate instruments,
as they satisfy the two criteria for valid instruments. Ta-
ble 2 reports the parameter estimates for the market
models specified in Equations (5) and (6), all regression
slopes are statistically significant at the one per cent level,
indicating that all sample firms from NYSE and HKSE
return respond to changes of Share Market Indexes.
For each firm, the results give us an attention that
6

(0.56～0.87) is more than 5

(0.97～1.52), which
indicates the fluctuation range of Chinese stocks returns
of NYSE are narrower than Dow Jones Industrials Index,
and which from HKSE are wider than Hong Kong Hang

The Transmission of Pricing Information of Dually-Listed between Hong Kong and New York Stock Exchange351
Table 2. Results of the market model for the NYSE and the HKSE
New York Stock Market Hong Kong Stock Market
Stock 5

5

2
R
Stock 6

6

2
R
SHI 0.026
(0.73) 0.618*** (13.76) 0.154 0338.HK 0.004 (0.06) 1.475*** (15.72) 0.192
CHA -0.003
(-0.10) 0.781*** (20.83) 0.294 0728.HK 0.069 (1.41) 1.094*** (16.41) 0.206
CBA -0.090*
(-1.78) 0.759*** (11.99) 0.121 1114.HK -0.084 (-1.36) 0.998*** (11.88) 0.119
GSH 0.017
(0.40) 0.603*** (11.38) 0.111 0425.HK
-0.137**
(-1.98) 1.222*** (13.00) 0.140
ACH 0.011
(0.25) 0.870*** (15.51) 0.188 2600.HK -0.080 (-1.58) 0.968*** (14.08) 0.160
HNP 0.040
(1.20) 0.590*** (14.18) 0.162 0902.HK -0.139* (-1.76) 1.214*** (11.26) 0.109
CEA -0.055
(-1.24) 0.560*** (9.97) 0.087 0670.HK -0.024 (-0.34) 1.519*** (16.13) 0.200
Note: t-values appear in parentheses.
***Significant at the 1 per cent level. **Significant at th e 5 pe r cent level. *Significant at the 10 per cent level.
Table 3. SUR estimates of Equations (1’), (2), (3’) and (4)
Transfer direction From New York to Hong Kong From Hong Kong to New York
Stock 7

7

2

2

8

8

4

4

SHI
(0338.HK) 0.039 (0.85) 0.972*** (10.77) 0.040 (0.52) -0.106* (-1.74) 0.066 (0.95) 0.000 (0.05) 0.066 (0.96) 0.002 (0.55)
CHA
(0728.HK) -0.029 (-0.86) 0.928*** (17.99) 0.090* (1.65) -0.015 (-0.30) 0.055 (1.08) 0.002 (0.35) 0.055 (1.08) 0.002 (0.82)
CBA
(1114.HK) 0.240*** (5.83) 0.671*** (9.95) -0.072 (-1.10) -0.098*** (-2.61) 0.063 (0.85) 0.002 (0.51) 0.063 (0.85) 0.001 (0.51)
GSH
(0425.HK) 0.151*** (3.33) 1.002*** (10.69) -0.114 (-1.53) 0.016 (0.30) 0.088 (1.59) 0.000 (-0.06) 0.088 (1.60) 0.000 (0.07)
ACH
(2600.HK) 0.049 (0.63) 0.617*** (5.45) -0.063 (-1.14) -0.015 (-0.43) 0.006 (0.04) 0.000 (-0.01) 0.006 (0.04) 0.000 (0.02)
HNP
(0902.HK) 0.051 (1.09) 1.138*** (11.51) -0.104 (-1.24) -0.146** (-2.05) -0.050 (-0.62) 0.000 (-0.11) -0.050 (-0.61) 0.000 (0.15)
CEA
(0670.HK) 0.241*** (4.77) 1.667*** (14.70) 0.006 (0.08) 0.090* (1.76) 0.106 (1.92) 0.000 (0.03) 0.106 (1.92) 0.000 (0.11)
Note: t-values appear in parentheses.
***Significant at the 1 per cent level. **Significant at th e 5 pe r cent level. *Significant at the 10 per cent level.
Seng Index. Ther efore, contrast to Dow Jones Industr ials
Index, the stocks of mainland firms listed in Hong Kong
are sensitivity to Hang Seng Index, which would be an
overreact.
The first two columns in Table 3 reports the results of
SUR estimates of the effect of changes in the sample
firm NYSE intraday return on the following day’s sam-
ple firm HKSE overnight return. All seven regression
slopes are statistically positive significant at the one
percen t level, indi cating that sa mple firm HKSE retu rns
respond to changes in corresponding firms returns on
the NYSE. If the regression slopes of firms, 7

, higher
than one, indicating that stock returns in Hong Kong
effected by New York higher than that in New York and
vice versa.
The following two columns in Table 3 reports the re-
sults of SUR estimates of the effect of changes in the
sample firm NYSE intraday return on the following
day’s sample firm HKSE intraday return. This regression
allows us to determine whether the transmission of pric-
ing information has been completed at the opening trade.
The insignificance of three of the seven regression slopes
suggests that most of the transmission of pricing infor-
mation is completed at the first trade of the day. The
negative significance of three of that suggests that based
on the opening price closing price have a reversion. Only
one firm have a negative significance slopes at the ten
per cent level indicating that pricing information trans-
mission is continue at the all trade of the day.
Associate Equation (1’) w ith Equation (2), as shown in

The Transmission of Pricing Information of Dually-Listed between Hong Kong and New York Stock Exchange 352
Table 3 is the transmission of pricing information from
New York to Hong Kong. 7

are higher than 2

and
so are the corresponding t-statistics, which suggests that
the transmission from New York to Hong Kong is com-
pleted at the first trade of the day.
The regression slopes in Equations (3’) and (4) are
insignificant, which suggests that the transmission of
pricing information from Hong Kong to New York is
unconspicuous. This result disagrees with Lau [5] and
Bae [6].
4. Conclusions
This study examines th e transmission of pricing info rma-
tion between market participants in the HKSE and the
NYSE. Using the opening and closing stock prices of
seven Chinese firms that are inter-listed on the Hong
Kong and the New York stock exchanges over the period
of 2003 to April 2007, four regression specifications re-
lating to the transmission of pricing information are ex-
amined. The findings of this study suggest that: 1) Con-
trast to Dow Jones Industrials Index, the stocks of
mainland firms listed in Hong Kong are sensitivity to
Hang Seng Index. 2) Sample firm HK SE opening returns
respond to changes in sample firm NYSE intraday stock
performance; the transmission process is apparently
completed at the open ing of the HKSE; 3) The transmis-
sion of pricing information from Hong Kong to New
York are unconspicuous.
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