Price Transmission Effect between GDRs and Their

Review of Quantitative Finance and Accounting, 19: 181–214, 2002©C 2002 Kluwer Academic Publishers. Manufactured in The Netherlands.

Price Transmission Effect between GDRs and TheirUnderlying Stocks—Evidence from Taiwan

SHEN-YUAN CHEN∗Department of Finance, Ming Chuan UniversityE-mail: [email protected]

LI-CHUAN CHOUDepartment of Finance, Ming Chuan University

CHAU-CHEN YANGDepartment of Finance, National Taiwan University

Abstract. In this paper we examine the price transmission effect between ADRs or GDRs and their respectiveunderlying stocks. This linkage is investigated for Granger causality using difference form and VECM. Resultsreveal unidirectional causality from Taiwan’s capital market to the foreign market. This asymmetry suggests thedomestic market plays a dominant role in price transmission relative to the foreign market. Besides, the prices ofboth markets will make adjustment to establish a long run cointegrated equilibrium. An additional finding is thatboth the premium and net buy have significant impacts on international price transmission for over twenty percentsamples. Empirical outcomes also provide the evidence that our model is quite robust.

Key words: price transmission, ADRs, GDRs, premium, net buy

JEL Classification: G15, F21, F23, C22

1. Introduction

Among the emerging equity markets, Taiwan’s capital market is an increasingly importantone for global institutional investors due to the government’s incessant revolution andliberalization policy in past decade. For example, in 1991, foreign institutional investorswere allowed to directly invest in Taiwan stock market and from September 1996, Taiwanmarket was included in its indices by the Morgan Stanley Capital International Inc. (MSCI).As Taiwan capital market continuously deregulated, foreign investors are getting more activeto this emerging market.

At the same time, as an important Original Equipment Manufacturer for worldwidefamous enterprises in recent years, Taiwan companies, especially for high-tech industries,are attracting more attention from the global investors. Rapid growth in competitive abilityhas engendered the result that a large number of Taiwan firms have their stocks cross-listed

∗Address correspondence to: 250, Chung Shan N. Rd. Sec. 5, Taipei, Taiwan. Tel.: (886) 2-28824564-2390, Fax:(886) 2-28809769.

182 CHEN, CHOU AND YANG

on international exchanges successfully. The stock price linkage between Taiwan market andforeign market has become an important issue for local and foreign institutional investorsbecause of the price interaction and arbitrage opportunities provided by dually listing.

The most commonly used vehicles of dual listing by Taiwan companies are AmericanDepositary Receipts (ADRs) and Global Depositary Receipts (GDRs). The possible advan-tages for such cross listing are promoting a firm’s reputation in large capital markets, theavailability of capital, lower capital costs and elimination of investment barriers such as do-mestic accounting and tax practices (see Karolyi (1998) survey on why and how companieslist abroad).

DRs can be created in one of the two ways: sponsored DR and unsponsored DR. In asponsored DR, the underlying corporation pays a fee to the depositary institution to coverthe cost of DR program. By regulation, the underlying corporation must provide periodicfinancial reports to the holders of DRs. A sponsored DR is often issued by a public companyto seek to have its stock traded in foreign country and to raise capital from a foreign market.In contrast to sponsored DR, an unsponsored DR is issued by one or more banks or securitybrokerage firms that assemble a large block of the shares of a foreign corporation withoutthe participation of the underlying corporation. Most DRs issued by Taiwanese listingcompanies are sponsored DRs.

The first issuance of DRs sponsored by a Taiwan company was the GDR of China SteelCorporation in May 1992. At the end of 1999, 36 Taiwanese listing companies have issuedDRs and the total amount of issuance had reached to 6.243 billion US dollars. Amongthese DRs, high technology companies are the major sponsors, which record 22 or 61.11%of issuances. The capital raised by these high technology companies was 4.475 billionUS dollars, or 71.68% of all issuances. Besides, the frequency of DRs issued by Taiwancompanies dramatically increased from 1994 to 1999. The status of Taiwan-listed companiesissuing DRs is summarized in Table 1.

In recent years, financial deregulation and international financial integration have resultedin a large amount of research on the dynamics of international transmission between GDRsor ADRs and their underlying securities. For example, Barclay et al. (1990) report thatdual listing of sixteen New York Stock Exchange (NYSE) listed companies on the TokyoStock Exchange (TSE) has no impact on the variances of NYSE close-to-close returns onthe stocks. Kato et al. (1991) and Wahab et al. (1992) try to find arbitrage opportunitiesbetween the prices of ADRs and underlying securities. They generally support the notationthat, after transactions costs, few profitable opportunities exist in these markets, implyingthat both markets are efficient. Jayaraman, Shastri and Tandon (1993) suggest that the listingof ADRs are associated with permanent increases in the return volatilities of the underlyingstocks. Kim, Szakmary and Mathur (2000) use both a vector autoregressive (VAR) modelwith a cointegration constraint and a seemingly unrelated regression (SUR) approach toexamine the relative importance of, and the speed of adjustment of ADR prices to, theseunderlying factors. Their results show that the ADRs appear to initially overreact to the USmarket index but underreact to changes in underlying share prices and exchange rate.

Multiple listing offers a unique opportunity to study the transmission of pricing infor-mation across markets. Neumark, Tinsley and Tonsini (1991) find that the foreign marketreacts to domestic price changes more quickly than the domestic market reacts to foreign

PRICE TRANSMISSION EFFECT BETWEEN GDRS 183

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price changes. This asymmetry, confirmed for price indices by Eun and Shim (1989) andHamao, Masulis and Ng (1990), is interpreted by Garbade and Silber (1979) as evidence thatthe foreign market acts as a satellite to the domestic market. Hauser, Tanchuma and Yaari(1998) investigate five companies based in Israel whose stocks are listed on both the TelAviv Stock Exchange and NASDAQ. Their empirical tests of causality in price changes usethe side-by-side Box-Jenkins ARIMA models and the Sims VAR model. Overall, the resultsshow that price causality in dually listed stocks is unidirection from the domestic marketto the foreign market. Jithendranathan, Nirmalanandan and Tandon (2000) evaluate marketsegmentation and its effect on the pricing of cross-listed securities using Indian Global De-positary Receipts (GDRs). They report that capital flow barriers existing in India lead to theGDRs being priced at a premium over the exchange rate adjusted prices of the underlyingIndian securities. And GDR index returns are affected by both domestic and internationalfactors, while the underlying Indian securities are affected only by domestic variables.

Earlier studies on international capital asset theory assume that international dually listedsecurities should sell at the same price in the absence of transaction costs and restrictionto capital flows. Garbade and Silber (1979) reported that prices may differ between marketcenters for short intervals of time in imperfectly integrated market. The adjustment be-tween prices in market A and market B can be characterized in one of two ways: (1) theadjustment may be symmetrical; (2) the adjustment may be one-sided. Hence, this paperuses Granger tests to examine causal relations between the returns on GDRs or ADRs andtheir respective underlying Taiwanese securities. We use error-correction model to analyzethe long run causal relations where the stock returns data is nonstationary. In addition, thispaper further discusses the impact of premium or discount in overseas-listed stocks on theprice transmission effect.1 The net buy by QFIIs2 in Taiwan is also one of important factorsto be measured in price transmission effect because QFIIs play an increasingly importantrole in Taiwan market since the MSCI indices including this emerging market. So we alsoexamine the effect of the net buy variable on causal relations.

Similar to the most existing research, our empirical results show the return causality ismostly unidirection from the domestic market to foreign market for dually listed Taiwanstocks. Besides, the prices of both markets will make adjustment to establish a long runcointegrated equilibrium. Unlike prior studies, this paper finds that both the premium ordiscount and QFII’s net buy have significant impacts on international price transmission forover twenty percent samples. Empirical tests show that our model is robust.

The remainder of this article is organized as follows: the next section presents the datadescription and the related empirical methodology. Our empirical results are described insection three. The final section concludes the paper.

2. Data and methodology

2.1. Data description

Thirty-six listed companies issued GDRs or ADRs by the end of 1999 in Taiwan; ninety-fiveGDRs or ADRs were issued and listed on exchange or over-the-counter (see Table 2). This


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5346

TT

POSD

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432

17.8

439

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0,97

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Table 3. List of selected samples

Bloomberg Code

Corporation GDRs or Issuing SampleCode ADRs Code Date

Shares ofQFIIs’Holding (inthousand)

Ratio ofQFIIs’Holding (%)

Ratio of QFIIs’& Non-QFIIs’Holding (%) Days

2317 TT HHPD LI 10/07/99 326,998 29.73 34.53 1515346 TT POSD LI 10/21/99 303,432 17.84 39.16 1412330 TT TSM US 10/08/97 1,777,349 17.79 34.69 6232357 TT ASKD LI 05/30/97 200,007 17.45 17.73 6261402 TT FETD LI 10/25/99 460,977 16.76 23.76 1392311 TT ASED LI 07/13/95 256,888 12.97 39.28 6262345 TT ATOD LI 02/01/97 26,491 11.29 13.69 6262609 TT YMTD LI 11/14/96 175,538 10.45 11.52 6262306 TT ACID LI 11/01/95 320,816 10.32 25.69 6262347 TT SYXD LI 07/03/97 36,112 10.32 37.87 6262324 TT CPED LI 11/09/99 152,969 9.83 10.06 1282325 TT SILD LI 10/04/95 110,158 9.77 16.34 6262337 TT MXICY US 05/14/96 201,890 9.49 19.91 5392344 TT WBDD LI 02/05/99 272,733 7.73 12.20 3071227 TT SFTD LI 06/19/97 21,007 6.95 12.31 6262346 TT LTTD LI 09/25/96 32,403 6.57 7.04 6262603 TT EGMD LI 07/30/96 119,344 6.43 33.14 6262002 TT CSGDS LI 05/28/92 547,186 6.39 6.82 6261102 TT ACGDS LI 06/23/92 69,589 3.72 11.88 6262342 TT MSVD LI 09/16/99 57,125 2.25 14.26 1621605 TT WLWD LI 10/03/95 25,812 0.82 13.53 626

Average: 261,658 10.71 20.73 Sum: 10,328

paper chooses twenty-one GDRs or ADRs from the ninety-five, representing twenty-onelisted companies, for total data of 10,328 sample days (see Table 3). The principal of makingselections is as below:

1. Forty-two GDRs or ADRs which have no quotations and no trading are eliminated.Eighteen GDRs or ADRs which have quotations but traded light are also excluded.

2. We deleted some listed company samples because their shares held by QFII are lessthan or equal to 6.3%. Exceptions are Asia Cement, Mosel Vitelic, and Walsin Lihwa,because these stocks are included in MSCI Taiwan Index.

3. We chose GDRs or ADRs on exchange for some companies issuing more than one andbeing liquid, for example, Taiwan Semiconductor Manufacturing (TSM US). GDRs orADRs in dollar quotation are selected if they have dollar and eurdollar quotations, forexample, ACID LI, EGMD LI, and CSGDS LI.

4. Finally D-Link is also deleted because of late issuance and there only being forty-sevencollected days.

The data for this paper are taken from three sources: the daily close price for GDRs orADRs and NT exchange rate are collected from the Bloomberg information system; the


underlying stock close price and adjusted price for ex-dividend are provided by TaiwanEconomic Journal (TEJ); the volume of net buy by foreign institutions is offered by theEnTrust Securities Company.

The period of selected samples is from October 8, 1997 to May 31, 2000 on the basis ofthe three points below:

1. In September 1997, Taiwan stocks were first included in the MSCI indices as a result ofincreasing foreign institution investment in the Taiwan equity market. It happened thatthe Asian Financial crisis began at the same time, which sharply increased systematicrisk in Taiwan stock market. This event didn’t end until the fourth quarter of 1997.

2. Taiwan Semiconductor Manufacturing (TSM) ADR made an epochal entry for Taiwancompanies issuing GDRs or ADRs because TSM is at the head of Taiwan’s high-techindustry, the first Taiwan company listed in NYSE, and the issuing amount being thelargest among all GDRs or ADRs.

3. These two years and seven months of selected samples cover a bearish market in 1998and bullish market in 1999 and 2000. So this period represents a complete business cyclein the Taiwan stock market.

2.2. Methodology

The methodology employed in this study is based on Granger (1969). Other causalitytesting methods reported in the literature include the test proposed by Sims (1972) and theprocedure suggested by Pierce and Haugh (1977). However, Granger’s tests are employedbecause they are superior to Sims’ (see Geweke, Meese and Dext (1983), and accordingto Hardouvelis (1988)), they perform well for small samples. However, it is necessary totest if the variables are stationary or not before Granger tests. If they are nonstationary, it isappropriate to specify by means of the vector error-correction models (Engle and Granger,1987) to explore Granger causality relationship between GDRs or ADRs and the prices ofunderlying shares.

2.2.1 Unit root test. The assumptions of the classical regression model necessitate thatthe time series be stationary and the errors have a zero mean and finite variance. In thepresence of nonstationary variables, there might be what Granger and Newbold (1974) calla spurious regression.3 Thus, the first step in the analysis is to check if the structure of thereturns series is stationary by the augmented Dickey-Fuller test (ADF).

The augmented Dickey-Fuller test can be applied both in the case of a lower and a higherautoregressive (AR) process. The following equation presents a higher AR process version(with a constant and a time trend) of the Dickey Fuller test:

�yt = a0 + a1t + γ yt−1 +P∑

i=2

βi · �yt−i+1 + et , et ∼ iid(0, σ 2)


where yt represents a time series, � implies first difference, and t is the time trend. Accordingto Said and Dickey (1984) the ADF test procedure is valid for a general ARMA process inthe errors. The null hypothesis in the ADF test is unit root (γ = 0). For yt to be stationary,γ should be negative and significantly different from zero.

2.2.2 Cointegration tests. A system of nonstationary individual stock price in levels can,however, share common stochastic trends. Put simply, two nonstationary time series arecointegrated if a linear combination of two variables is stationary, that is, converges to anequilibrium over time. The main idea behind cointegration is a specification of models thatincludes beliefs about the movements of variables relative to each other in the long-run,such as the price of Taiwan’s stock and GDRs or ADRs. Thus a common stochastic trendin a system of stock prices can be interpreted to mean that the stochastic trend in Taiwan’sstock price is related to the GDRs or ADRs trend. There exists more than one method ofconducting cointegration tests. The long-run relationship tests in this paper are conducted bymeans of the method developed by Johansen (1988) and Johansen and Juselius (1990). TheJohansen maximum likelihood approach sets up the nonstationary time series as a vectorautoregressive (VAR). The model is also called vector error-correction model (VECM):

�Xt = c +N∑

i=1

i�Xt−i +∏

Xt−1 + ηt , ηt ∼ niid(0, δ)

where Xt is a vector of nonstationary (in levels) variables, � implies first difference andc is the constant term. The information on the coefficient matrix between the levels of theseries

∏is decomposed as

∏ = αβ ′ where the relevant elements of the α matrix are theadjustment coefficients and the β matrix contains the cointegrating vectors. α and β arep × r matrices of full rank. If r = 0, then

∏ = 0, and there exists no linear combination ofthe elements of Xt that is stationary. At the other extreme, if rank (

∏) = p, Xt is itself a

stationary process. In the intermediate case, when 0 < r < p, there exist r stationary linearcombinations of the elements of Xt . The constant term is included to capture the trendingcharacteristic of the time series involved. The Johansen method provides the trace test andto determine the number of cointegrating vector. It is defined as:

trace statistic = −Tp∑

i=r+1

ln(1 − λi )

for r = 0, 1, 2, . . . , p − 1 where λi is the i th largest eigenvalue. The critical values forthe trace statistic are reported by Osterwald-Lenum (1992), not those tabulated in Johansenand Juselius (1990). The trace statistic generally has greater power when the λi s are evenlydistributed.

2.2.3 Granger causality test. The objective of this section is to investigate causal relationsbetween the returns on GDRs or ADRs and their respective underlying Taiwan securities.The methodology employed in this study is based on Granger (1969). The Granger Causality


tests with difference form involve the estimation of the following equation:

R fi,t = λ

f0 + λ

f1 R f

i,t−1 + λf2 Rd

i,t + εf

i,t (1)

Rdi,t = λd

0 + λd1 Rd

i,t−1 + λd2 R f

i,t−1 + εdi,t (2)

where

Ri,t = log(p f (d)i,t ) − log(p f (d)

i,t )

p f (d)i,t : p f

i,t denotes the close price of GDRs or ADRs in day t;pd

i,t denotes the close price of the underlying security in day t.

Within the same calendar day, Taiwan market closes earlier than US and European markets,so foreign investors can observe the returns of both markets on the same day. On theother hand, the domestic investors observe the returns of the preceding day overseas. Theregression model is set up so that R f

t regresses on R ft−1 and Rd

t , but Rdt regresses on Rd

t−1 andR f

t−1. The Granger causality tests with the VECM involve the estimation of the followingequation while the data exist cointegration relationship:

R fi,t = k f

0 + k f1 R f

i,t−1 + k f2 Rd

i,t + k f3

(log p f

i,t−1 − c0 − c1 log pdi,t−1

) + εf

i,t (3)

Rdi,t = kd

0 + kd1 Rd

i,t−1 + kd2 R f

i,t−1 + kd3

(log pd

i,t−1 − d0 − d1 log p fi,t−1

) + εdi,t (4)

The lambdas and kappas are the parameters to be estimated. In the above estimation ofequation (1) to equation (4), if the estimated coefficients λ

f2 and k f

2 of equations (1) and (3)are statistically significant while the estimated coefficients λd

2 and kd2 of equations (2) and

(4) are not statistically significant, then the results suggest a uni-directional causality, in theGranger sense, from the Taiwan stock returns to change GDR stock returns. In terms coinedby Garbade and Silber (1979), the underlying security market is dominant and the overseassecurity market is a satellite. If, on the other hand, the estimated coefficients λd

2 and kd2 of

equations (2) and (4) are statistically significant while the estimated coefficients λf2 and

k f2 of equations (1) and (3) are not statistically significant, then uni-directional causality

exists from changes in GDRs or ADRs to Taiwan’s stock returns. If the four coefficientsare statistically significant in equations (1) and (4), then the data provide evidence of bi-directional causality. Absence of directional causality is indicated when the set of parametersλd

2 , kd2 , λ

f2 and k f

2 are statistically insignificant. Finally, both kd3 and k f

3 represent the speedof adjustment coefficient for reflecting the long-run disequilibrium in the prices betweenthe underlying stock and the GDRs or ADRs. c0, d0, c1, d1 are cointegrating coefficients.

2.2.4 The impact of premium and net buy on Granger causality

The premium effect. Several studies on the pricing behavior of dual listed internationalsecurities do not find any significant difference between the domestic price and exchangerate adjusted price of the same security listed in an overseas market.4 Park and Tavakkol


(1994) examine the exchange rate adjusted returns of Japanese ADRs and the underly-ing stocks and find no significant differences between the two. On the other hand, Millerand Morey (1996) find intra-day pricing differences between the British ADRs and theunderlying securities. This paper examines whether the price transmission effect is signifi-cantly amplified while the magnitude of the premium or discounts in overseas-listed stocksincreases. We set up the estimation of the following equations:

R fi,t = λ

f0 + λ

f1 R f

i,t−1 + (β

f0 + β

f1 ∗ prem f

t

)Rd

i,t + εf

i,t (5)

Rdi,t = λd

0 + λd1 Rd

i,t−1 + (βd

0 + βd1 ∗ premd

t−1

)R f

i,t−1 + εdi,t (6)

R fi,t = k f

0 + k f1 R f

i,t−1 + (φ

f0 + φ

f1 · prem f

t

)Rd

i,t

+ k f3

(log p f


) + εf

i,t (7)

Rdi,t = kd

0 + kd1 Rd

i,t−1 + (φd

0 + φd1 · premd

t

)R f

i,t−1

+ kd3

(log pd

i,t−1 − d0 − d1 log p fi,t−1

) + εdi,t (8)

where

prem ft = p f

i,t−1 · EXt − pdi,t

pdi,t

(9)

premdt = p f

i,t−1 · EXt−1 − pdi,t−1

pdi,t−1

(10)

EXt : exchange rate in day t

We further discuss the above equations in two cases: one, both the premium and Rdt

have the same sign. For example, if foreign investors observe that there exists positivepremium and the underlying stock price rises, then through the market mechanism ofarbitrary transactions, the prices of ADRs or GDRs will not change or even go down inorder to shrink the price gap between the underlying stock and ADRs or GDRs. Therefore,both β

f1 and φ

f1 will be expected to be equal to or less than zero. Second, the premium and

Rdt have the opposite sign. In this case, if foreign investors find that there exists positive

premium but the underlying stock price is down, then the prices of ADRs or GDRs willdecline. Thus, both β

f1 and φ

f1 will be expected to be greater than or equal to zero. According

to the above, if both the premium and R ft−1 are the same sign, for example, domestic investors

observe that there exists positive premium and ADRs or GDRs price is also up, then theunderlying stock price will go up and both βd

1 and φd1 will be expected to be greater than or

equal to zero. On the contrary, when both the premium and R ft−1 are the opposite sign, for

example, domestic investors observe that there exists positive premium but ADRs or GDRsprice is down, the underlying stock price will not change or even go up in order to shrinkthe price gap. Therefore, both βd

1 and φd1 will be expected to be equal to or less than zero.


Net buy effect. During these years QFIIs are more aggressive to increase their investmentpositions in Taiwan. In consequence of the substantial growth of QFIIs’ portfolio holdingin Taiwan’s equities, the net buy or net sell of QFIIs’ daily trading has become an importantinvestment signal for all investors participating in the Taiwan market. Stock with positivenet buy by QFIIs is often followed by an increase in share price on next trading day, inparticular, for those stocks underlying ADRs or GDRs. Thus, we also add the variable ofQFIIs’ daily net buy into our empirical models to further examine the impact of net buy onGranger causality relationship between the underlying stock and the ADRs or GDRs. Themodels are as follows:

R fi,t = λ

f0 + λ

f1 R f

i,t−1 + (δ

f0 + δ

f1 · BS f

t

)Rd

i,t + εf

i,t (11)

Rdi,t = λd

0 + λd1 Rd

i,t−1 + (δd

0 + δd1 · BSd

t−1

)R f

i,t−1 + εdi,t (12)

R fi,t = k f

0 + k f1 R f

i,t−1 + (ω

f0 + ω

f1 · BS f

t

)Rd

i,t

+ k f3

(log p f


) + εf

i,t (13)

Rdi,t = kd

0 + kd1 Rd

i,t−1 + (ωd

0 + ωd1 · BSd

t−1

)R f

i,t−1

+ kd3

(log pd

i,t−1 − d0 − d1 log p fi,t−1

) + εdi,t (14)

where

BS ft : the volume of net buy for underlying stock by QFIIs in Taiwan observed

by foreigners in day t; i.e., the net shares of total bought minus total sold forunderlying stock by all QFIIs in day t

BSdt−1: the volume of net buy for underlying stock by QFII in Taiwan observed by

the domestic investors in day t

In the above estimation of equations (11) and (13), if QFIIs buy net shares for theunderlying stock in Taiwan’s market and at the same time the return of the underlyingstocks rises, the prices of GDRs or ADRs will rise, fall or hold steady, so the signs of δ

f1

and w f1 can’t be determined. There are two reasons to explain the above phenomenon. One

is that the prices of the underlying stocks are relatively undervalued as a consequence ofQFIIs’ net buy in order to get arbitrage profit. Of course the gap between both prices can beshrunk by arbitrage trading. The other reason is that the prospect of the underlying companydemonstrates such potential that QFIIs purchase these underlying stocks, and as a result theprices of the underlying stocks and ADRs or GDRs simultaneously rise. On the other side, inequations (12) and (14), if the return of GDRs or ADRs is negative and QFIIs buy net sharesof the underlying stock, the return of the underlying stock will be positive, negative or zero,so the signs of δd

1 and wd1 are also uncertain. The reason for the uncertainty is that the

prices of the underlying stocks are undervalued and QFIIs buying net shares will lead to theprice of the underlying stocks rising. However, the underlying stock prices may also dropto reflect the falling price of GDRs or ADRs.


Robust test. Finally, our model simultaneously includes the premium and net buy factors toexamine if the model is robust. This is reflected in the estimation of equations (15) to (18):

R fi,t = λ

f0 + λ

f1 R f

i,t−1 + (θ

f0 + θ

f1 · prem f

t + θf

2 · BS ft

)Rd

i,t + εf

i,t (15)

Rdi,t = λd

0 + λd1 Rd

i,t−1 + (θd

0 + θd1 · premd

t + θd2 · BSd

t−1

)R f

i,t−1 + εdi,t (16)

R fi,t = k f

0 + k f1 R f

i,t−1 + (γ

f0 + γ

f1 · prem f

t + γf

2 · BS ft

)Rd

i,t

+ k f3

(log p f


) + εf

i,t (17)

Rdi,t = kd

0 + kd1 Rd

i,t−1 + (γ d

0 + γ d1 · premd

t + γ d2 · BSd

t−1

)R f

i,t−1

+ kd3

(log pd

i,t−1 − d0 − d1 log p fi,t−1

) + εdi,t (18)

3. Empirical results

3.1. Unit root and cointegration tests results

As stated earlier, all series are applied in logarithmic form. As required of all cointegrationtests, the series of stock price must first be inspected for the presence of unit roots. Table 4

Table 4. Augmented Dickey-Fuller tests for a unit roota

Corporation Code Taiwan GDRs or ADRs

1102 −2.721650 −2.8850681227 −2.532691 −2.3829611402 −1.494700 −1.2529381605 −1.586543 −1.8456392002 −2.816041 −2.4042932306 −1.864972 −2.0642312311 −1.910316 −2.0500462317 −1.981890 −1.3528532324 −1.791862 −1.9354912325 −3.505806** −3.729858**2330 −1.978247 −2.5876202337 −1.401737 −1.5307772342 −2.154823 −2.2527262344 −3.093396 −3.0082042345 −2.522986 −2.4944032346 −1.172046 −1.1136042347 −3.763689** −3.686703**2357 −2.081670 −2.1916812603 −2.337686 −1.7147612609 −3.341800** −3.717536**5346 −2.465527 −2.501067

aThe entry in each cell is the ADF statistic.**Implies rejection of the null at 5% level.


Table 5. Cointegration test results (Lags in the VAR = 1)

r a = 0 r =< 1

Corporation Code Eigenvalue Trace Statistic Eigenvalue Trace Statistic

1102 0.028652 26.32853*** 0.013037 8.188700***1227 0.018837 12.46983 0.000966 0.6033291402 0.071200 12.34016 0.016081 2.2210291605 0.034779 23.29036*** 0.001924 1.2020122002 0.031511 24.74242*** 0.007604 4.763040**2306 0.199605 14.02069*** 0.002038 1.2730442311 0.033467 24.49023*** 0.005194 3.2493192317 0.090624 16.04527** 0.020229 2.8407112324 0.083378 14.61861 0.028546 3.6490782330 0.044065 28.63125*** 0.001040 0.6459712337 0.215139 13.00895*** 0.000003 0.0018612342 0.114581 20.31530*** 0.005262 0.8442012344 0.065481 20.70226*** 0.000153 0.0465712345 0.011082 8.226734 0.002038 1.2729492346 0.013422 11.19552 0.004419 2.7636382357 0.047425 32.22369*** 0.003050 1.9060042603 0.022752 18.79700** 0.007083 4.435474**5346 0.060651 10.65297 0.013973 1.955989

ar is hypothesized number of cointegrating relationships.*** and **imply rejection of the null at 1% and 5% level, respectively.

presents the results from ADF tests. We employed Akaike’s information criterion to selectthe appropriate lag lengths. For most of the series, we are unable to reject the unit roothypothesis, but there are some exceptions. In other words, most of time series data are I (1),but some series data are I (0). When the series are stable, they don’t need the cointegrationtest.

Table 5 presents the results from the cointegration tests. In this paper, we used trace testto determine the number of cointegrating vectors. Results show a cointegration relationshipexisting between most Taiwan stock prices and their GDR’s or ADR’s prices. In otherwords, we are able to find a stationary long run relationship between both. So, we shouldemploy VECM to test Granger causality relationship for existing cointegration time series.It is appropriate to simultaneously consider long- and short-term effects. For time serieswithout cointegration, they directly take the first difference form to test Granger causalityrelationship. As reported in Table 5, trace tests indicate that at least one cointegrationrelationship exists for twelve of the firms. Each firm’s cointegrating vector is calculated andincorporated in the VAR model estimation to capture the long run equilibrium relationship.

3.2. Granger causality tests results

Table 6 shows the results from Granger Causality with difference form. Only sevensamples have bi-directional causality but fourteen samples among twenty-one total show


Table 6. Granger causality tests results—difference form

R fi,t = λ

f0 + λ

f1 R f

i,t−1 + λf2 Rd

i,t + εf

i,t

Rdi,t = λd

0 + λd1 Rd

i,t−1 + λd2 R f

i,t−1 + εdi,t

λf0 λ

f1 λ

f2

Corporation Code D. V.a λd0 λd

2 λd1

1102 R ft −0.0002 −0.0381 0.8993

(0.7954) (0.1667) (0.0000)***Rd

t −0.0005 0.1077 −0.0446(0.6563) (0.0241)** (0.4457)

1227 R ft −0.0002 0.0844 0.7185

(0.8390) (0.0073)*** (0.0000)***Rd

t −0.0006 0.1447 0.0154(0.5680) (0.0010)*** (0.7632)

1402 R ft 0.0001 0.0508 0.7535

(0.9609) (0.4282) (0.0000)***Rd

t 0.0008 0.1383 −0.0683(0.8085) (0.1808) (0.5582)

1605 R ft 0.0001 −0.0282 0.9315

(0.9272) (0.1644) (0.0000)***Rd

t 0.0005 0.0931 −0.1169(0.6575) (0.2052) (0.1407)

2002 R ft −0.0000 0.0164 1.0482

(0.9792) (0.5628) (0.0000)***Rd

t 0.0002 0.1391 0.1770(0.8430) (0.0003)*** (0.0018)***

2306 R ft 0.0000 −0.1074 0.9934

(0.9536) (0.0000)*** (0.0000)***Rd

t 0.0009 0.1744 −0.1645(0.5259) (0.0146) (0.0422)**

2311 R ft 0.0001 0.0156 0.9501

(0.9152) (0.5719) (0.0000)***Rd

t 0.0004 0.1021 −0.1039(0.7498) (0.0216) (0.0742)∗

2317 R ft −0.0003 0.1373 0.8626

(0.8942) (0.0305)** (0.0000)***Rd

t 0.0021 0.1098 0.0003(0.4069) (0.1669) (0.9975)

2324 R ft 0.0002 0.0530 1.0029

(0.9188) (0.2725) (0.0000)***Rd

t −0.0006 0.0938 −0.1403(0.8474) (0.5136) (0.4079)

2325 R ft 0.0000 −0.0440 0.9086

(0.9892) (0.1629) (0.0000)***Rd

t 0.0003 0.0594 −0.0370(0.8375) (0.0896)* (0.4684)

2330 R ft 0.0009 −0.1244 0.7192

(0.5526) (0.0008)*** (0.0000)***Rd

t 0.0011 0.2096 −0.0637(0.3371) (0.0000)*** (0.1398)


Table 6. (Continued)

λf0 λ

f1 λ

f2

Corporation Code D. V.a λd0 λd

2 λd1

2337 R ft 0.0005 −0.1373 0.7759

(0.7222) (0.0000)*** (0.000)***Rd

t 0.0011 0.1300 −0.0548(0.5018) (0.0080)** (0.3338)

2342 R ft 0.0007 −0.0334 0.9720

(0.6420) (0.3512) (0.0000)***Rd

t 0.0056 0.0230 0.0473(0.0815)* (0.8873) (0.7873)

2344 R ft 0.0004 −0.0840 1.0020

(0.7229) (0.0074) (0.0000)***Rd

t 0.0033 0.1238 −0.1679(0.0767) (0.1577) (0.1094)

2345 R ft −0.0006 −0.0753 1.0214

(0.4457) (0.0001)*** (0.0000)***Rd

t 0.0004 0.0116 0.0874(0.7739) (0.8720) (0.2932)

2346 R ft −0.0004 −0.0876 0.9839

(0.6363) (0.0000)*** (0.0000)***Rd

t −0.0000 0.0091 0.1163(0.9796) (0.9094) (0.1848)

2347 R ft 0.0000 −0.1148 0.9800

(0.9753) (0.0000)*** (0.0000)***Rd

t 0.0004 0.0769 0.0748(0.7415) (0.2383) (0.3125)

2357 R ft 0.0003 −0.0628 1.0568

(0.7993) (0.0355)** (0.0000)***Rd

t 0.0010 0.1374 −0.0739(0.3419) (0.0001)*** (0.1711)

2603 R ft −0.0000 0.0439 0.8715

(0.9898) (0.1034) (0.0000)***Rd

t −0.0002 0.0722 0.0435(0.8058) (0.1542) (0.4660)

2609 R ft 0.0006 −0.0094 0.8723

(0.4126) (0.7111) (0.0000)***Rd

t −0.0001 0.0642 −0.0199(0.9626) (0.2578) (0.7549)

5346 R ft 0.0021 −0.0297 0.9594

(0.2426) (0.4854) (0.0000)***Rd

t 0.0033 0.0259 0.0199(0.3150) (0.8617) (0.9020)

aD. V. represents dependent variable.*Significant at the 10% level.**Significant at the 5% level.***Significant at the 1% level.(.) represents p-value.


uni-directional causality. This demonstrates that most of the time the Taiwan stock re-turns change GDRs or ADRs returns. In addition, the estimated coefficient λd

2 approaches100 percent, despite the estimated coefficient λ

f2 being near to zero. So our empirical re-

sults mostly support Garbade and Silber’s (1979) idea that the underlying security marketis dominant and the overseas security market is a satellite.

To continue, the cointegration relationship data employ the Granger causality test withVECM which simultaneously considers long run and short run effects between the returnsof Taiwan stock and GDRs or ADRs. Table 7 presents the empirical results with VECM. Inthe short run, it shows similar results that Taiwan stock returns significantly influence GDRsor ADRs returns but not the reverse. In the long run, all the coefficients for the speed of

Table 7. Granger causality tests results—VECM

R fi,t = k f

0 + k f1 R f

i,t−1 + k f2 Rd

i,t + k f3 (log p f

i,t−1 − c0 − c1 log pdi,t−1) + ε

fi,t

Rdi,t = kd

0 + kd1 Rd

i,t−1 + kd2 R f

i,t−1 + kd3 (log pd

i,t−1 − d0 − d1 log p fi,t−1) + εd

i,t

κf

0 κf

1 κf

2 κf

3

Corporation Code D.Va κd0 κd

2 κd1 κd

3

1102 R ft −0.0002 −0.0240 0.9088 −0.0545

(0.8056) (0.3817) (0.0000)*** (0.0000)***Rd

t 0.0927 −0.0324 −0.0302(0.0558)* (0.5812) (0.0857)*

1605 R ft 0.0038 −0.0274 0.9311 −0.0007

(0.6412) (0.1784) (0.0000)*** (0.6455)Rd

t 0.0187 0.0925 −0.1125 −0.0064(0.2620) (0.2078) (0.1565) (0.2749)

2202 R ft −0.0000 0.0277 1.0570 −0.0551

(0.9763) (0.3236) (0.0000)*** (0.0000)***Rd

t 0.0002 0.1333 −0.1699 −0.0146(0.8434) (0.0007)*** (0.0031)*** (0.3940)

2306 R ft −0.0001 −0.0062 1.0453 −0.5855

(0.8883) (0.7336) (0.0000)*** (0.0000)***Rd

t 0.0009 −0.0207 0.0012 −0.3905(0.5105) (0.8064) (0.9889) (0.0000)***

2311 R ft −0.0001 0.0318 0.9659 −0.0425

(0.9250) (0.2527) (0.0000)*** (0.0004)***Rd

t 0.0004 0.0803 −0.0930 −0.0437(0.7441) (0.0724)* (0.1084) (0.0008)***

2317 R ft −0.0005 0.1613 0.8939 −0.0467

(0.8620) (0.0134)** (0.0000)*** (0.1231)Rd

t 0.0021 0.0461 0.0350 −0.1167(0.3888) (0.5669) (0.7434) (0.0047)***

2330 R ft 0.0009 −0.1134 0.7351 −0.0191

(0.5712) (0.0028)*** (0.0000)*** (0.1663)Rd

t 0.0012 0.1740 −0.0648 −0.0607(0.2966) (0.0000)*** (0.1255) (0.0000)***


Table 7. (Continued)

κf

0 κf

1 κf

2 κf

3

Corporation Code D.Va κd0 κd

2 κd1 κd

3

2337 R ft 0.0003 −0.0133 0.8312 −0.5796

(0.8124) (0.6487) (0.0000)*** (0.0000)***Rd

t −0.0048 0.0454 0.0288 −0.1681(0.0790)* (0.4330) (0.6542) (0.0073)***

2342 R ft 0.0004 −0.0023 0.9973 −0.2655

(0.7952) (0.9475) (0.0000)*** (0.0000)***Rd

t 0.0057 −0.1091 0.1679 −0.2772(0.0712)* (0.5285) (0.3598) (0.0418)**

2344 R ft 0.0003 −0.0490 1.0169 −0.1630

(0.8205) (0.1131) (0.0000)*** (0.0000)***Rd

t 0.0006 0.0931 −0.1434 −0.0629(0.8471) (0.3081) (0.1794) (0.2395)

2357 R ft 0.0003 −0.0396 1.0849 −0.0663

(0.8356) (0.1880) (0.0000)*** (0.0001)***Rd

t 0.0010 0.1030 −0.0470 −0.0799(0.3304) (0.0045)*** (0.3828) (0.0001)***

2603 R ft −0.0000 0.0362 0.8796 −0.0200

(0.9899) (0.1782) (0.0000)*** (0.0018)***Rd

t −0.0003 0.0691 0.0580 −0.0329(0.8078) (0.1720) (0.3332) (0.0338)

aD. V. represents dependent variable.*Significant at the 10% level.**Significant at the 5% level.***Significant at the 1% level.(.) represents p-value.

adjustment, kd3 ’s and k f

3 ’s, are negative and most of them are significant. This result indicatesthat once the return relationship of the underlying stock and the GDRs or ADRs deviatesfrom the long run cointegrated equilibrium, both markets will make opposite adjustment toreestablish the equilibrium in next period. In a word, Table 7 shows that price causality indually listed stocks is mostly unidirectional from the domestic market to the foreign marketand the prices of both markets will adjust to a long run cointegrated equilibrium.

3.3. Results of the premium and net buy effect

Table 8 reveals the results from Granger Causality involving the premium in overseas-listed stocks. The estimated coefficient β

f0 or φ

f0 is significant and approaches to 1, but

the estimated coefficient βd0 or φd

0 is mostly not significant and near to zero. So the pricetransmission effect is still unidirectional from the domestic market to the foreign market.The transmission effect of seven samples is influenced by the premium in overseas-listed


ble

8.C

hang

ein

Gra

nger

caus

ality

resu

lts—

Prem

ium

Rf i,t=

λf 0+

λf 1

Rf i,t−

1+

( βf 0+

βf 1∗p

rem

f t

) Rd i,

t+

εf i,t

(5)

Rd i,

t=

λd 0

+λ

d 1R

d i,t−

1+

( βd 0

+β

d 1∗p

rem

d t−1

) Rf i,t−

1+

εd i,

t(6

)

Rf i,t=

kf 0+

kf 1

Rf i,t−

1+

( φf 0+

φf 1·p

rem

f t

) Rd i,

t+

kf 3

( log

pf i,t−

1−

c 0−

c 1lo

gpd i,

t−1

) +ε

f i,t

(7)

Rd i,

t=

kd 0+

kd 1R

d i,t−

1+

( φd 0

+φ

d 1·p

rem

d t

) Rf i,t−

1+

kd 3

( log

pd i,t−

1−

d 0−

d 1lo

gp

f i,t−

1

) +ε

d i,t

(8)

Cor

pora

tion

λf 0(κ

f 0)

λf 1(κ

f 1)

βf 0(φ

f 0)

βf 1(φ

f 1)

κf 3

Cod

eD

.V.a

λd 0(κ

d 0)

βd 0(φ

d 0)

λd 1(κ

d 1)

βd 1(φ

d 1)

κd 3

1102

Rf t

−0.0

009

−0.0

133

0.95

80−1

.207

1−0

.057

2(0

.297

0)(0

.627

9)(0

.000

0)**

*(0

.000

3)**

*(0

.000

0)**

*R

d t−0

.000

70.

0347

−0.0

107

0.63

73−0

.029

2(0

.514

9)(0

.540

8)(0

.858

1)(0

.052

5)*

(0.0

961)

*

1227

Rf t

−0.0

007

0.08

110.

8006

−0.5

703

(0.5

076)

(0.0

098)

***

(0.0

000)

***

(0.0

187)

**R

d t−0

.000

60.

1650

0.01

57−0

.164

7(0

.588

4)(0

.001

7)**

*(0

.758

4)(0

.474

5)

1402

Rf t

−0.0

000

0.05

220.

7713

−0.1

063

(0.9

902)

(0.4

231)

(0.0

000)

***

(0.8

913)

Rd t

0.00

03−0

.241

6−0

.009

41.

5740

(0.9

375)

(0.1

719)

(0.9

352)

(0.0

095)

***

1605

Rf t

0.00

38−0

.027

40.

9315

−0.0

000

−0.0

007

(0.6

419)

(0.1

798)

(0.0

000)

***

(0.9

608)

(0.6

462)

Rd t

0.01

880.

1359

−0.1

383

−0.7

969

−0.0

064

(0.2

596)

(0.1

022)

(0.0

946)

*(0

.265

3)(0

.275

0)

2002

Rf t

−0.0

000

0.02

941.

0946

−0.0

000

−0.0

551

(0.9

902)

(0.2

967)

(0.0

000)

***

(0.4

570)

(0.0

000)

***

Rd t

0.00

010.

0863

−0.1

410

0.37

27−0

.010

5(0

.945

8)(0

.077

0)*

(0.0

189)

**(0

.109

8)(0

.545

8)


06R

f t−0

.000

1−0

.006

41.

0349

0.00

00−0

.584

5(0

.865

6)(0

.722

3)(0

.000

0)**

*(0

.506

4)(0

.000

0)**

*R

d t0.

0001

−0.0

315

1.02

412.

9732

−0.3

836

(0.9

620)

(0.7

080)

(0.7

873)

(0.0

118)

**(0

.000

0)**

*

2311

Rf t

0.00

04−0

.092

70.

0783

0.01

01−0

.043

7(0

.752

0)(0

.110

6)(0

.197

3)(0

.960

1)(0

.002

9)**

*R

d t0.

0004

0.07

83−0

.092

70.

0101

−0.0

437

(0.7

520)

(0.1

973)

*(0

.110

6)(0

.960

1)(0

.002

8)**

*

2317

Rf t

−0.0

005

0.15

830.

8665

0.00

01−0

.046

0(0

.846

7)(0

.016

2)**

(0.0

000)

***

(0.6

891)

(0.1

305)

Rd t

0.00

230.

0889

0.03

65−0

.118

2−0

.114

8(0

.369

6)(0

.609

1)(0

.734

0)(0

.780

8)(0

.006

2)**

*

2324

Rf t

0.00

020.

0665

0.95

320.

0004

(0.9

002)

(0.1

722)

(0.0

000)

***

(0.0

948)

*R

d t−0

.000

50.

1294

−0.1

587

−0.7

208

(0.8

618)

(0.4

380)

(0.3

661)

(0.6

715)

2325

Rf t

0.00

00−0

.037

50.

9880

−0.0

004

(0.9

947)

(0.2

338)

(0.0

000)

***

(0.0

080)

***

Rd t

0.00

040.

0814

−0.0

418

−0.0

969

(0.7

754)

(0.1

392)

(0.4

199)

(0.6

033)

2330

Rf t

0.00

07−0

.121

00.

6540

0.00

02−0

.019

2(0

.666

3)(0

.001

6)**

*(0

.000

0)**

*(0

.183

2)(0

.163

3)R

d t0.

0012

0.18

50−0

.065

3−0

.028

8−0

.060

7(0

.282

2)(0

.000

2)**

*(0

.123

0)(0

.782

1)(0

.000

0)**

*

2337

Rf t

0.00

01−0

.015

90.

7948

0.00

02−0

.574

8(0

.938

9)(0

.587

0)(0

.000

0)**

*(0

.069

7)*

(0.0

000)

***

Rd t

−0.0

055

0.04

280.

0331

1.35

87−0

.172

3(0

.045

0)**

(0.4

587)

(0.6

071)

(0.0

902)

*(0

.005

9)**

*

(con

tinu

ed)


Tabl

e8.

(Con

tinu

ed)

Cor

pora

tion

λf 0(κ

f 0)

λf 1(κ

f 1)

βf 0(φ

f 0)

βf 1(φ

f 1)

κf 3

Cod

eD

.V.a

λd 0(κ

d 0)

βd 0(φ

d 0)

λd 1(κ

d 1)

βd 1(φ

d 1)

κd 3

2342

Rf t

0.00

040.

0011

1.01

85−0

.000

2−0

.264

5(0

.784

5)(0

.973

9)(0

.000

0)**

*(0

.240

7)(0

.000

0)**

*R

d t0.

0054

−0.0

751

0.16

611.

5598

−0.2

759

(0.0

936)

*(0

.673

2)(0

.365

7)(0

.408

7)(0

.043

1)**

2344

Rf t

0.00

03−0

.049

11.

0055

0.00

00−0

.163

1(0

.812

1)(0

.112

6)(0

.000

0)**

*(0

.732

5)(0

.000

0)**

*R

d t0.

0006

0.12

34−0

.159

3−0

.956

2−0

.069

4(0

.844

7)(0

.207

3)(0

.141

8)(0

.385

2)(0

.199

1)

2345

Rf t

−0.0

006

−0.0

753

1.01

780.

0165

(0.4

784)

(0.0

001)

***

(0.0

000)

***

(0.8

725)

Rd t

0.00

050.

0364

0.08

35−0

.099

2(0

.758

7)(0

.663

0)(0

.316

6)(0

.558

3)

2346

Rf t

−0.0

004

−0.0

875

0.99

15−0

.000

2(0

.586

2)(0

.000

0)**

*(0

.000

0)**

*(0

.194

0)R

d t−0

.000

00.

0073

0.11

720.

0202

(0.9

794)

(0.9

331)

(0.1

893)

(0.9

564)

2347

Rf t

0.00

00−0

.114

10.

9831

−0.0

001

(0.9

570)

(0.0

000)

***

(0.0

000)

***

(0.5

909)

Rd t

0.00

030.

0632

0.08

260.

3805

(0.8

264)

(0.3

601)

(0.2

725)

(0.5

483)


2357

Rf t

0.00

02−0

.041

31.

0726

0.00

02−0

.066

3(0

.868

5)(0

.171

5)(0

.000

0)**

*(0

.450

7)(0

.000

1)**

*R

d t0.

0011

0.12

19−0

.055

5−0

.101

9−0

.080

8(0

.295

6)(0

.006

5)**

*(0

.314

5)(0

.472

3)(0

.000

1)**

*

2603

Rf t

−0.0

000

0.04

010.

9174

−0.0

002

−0.0

210

(0.9

859)

(0.1

361)

(0.0

000)

***

(0.0

522)

*(0

.001

0)**

*R

d t−0

.000

30.

0267

0.07

980.

2721

−0.0

330

(0.7

938)

(0.6

683)

(0.2

038)

(0.2

457)

(0.0

329)

**

2609

Rf t

0.00

04−0

.013

30.

8217

0.00

03(0

.588

4)(0

.598

0)(0

.000

0)**

*(0

.002

6)**

*R

d t−0

.000

1−0

.006

7−0

.001

10.

3824

(0.9

444)

(0.9

237)

(0.9

863)

(0.0

823)

*

5346

Rf t

0.00

20−0

.026

90.

9496

0.00

01(0

.260

8)(0

.535

8)(0

.000

0)**

*(0

.702

4)R

d t0.

0036

0.05

070.

0435

1.15

38(0

.280

6)(0

.736

1)(0

.789

7)(0

.290

2)

a D.V

.rep

rese

nts

depe

nden

tvar

iabl

e.*S

igni

fican

tatt

he10

%le

vel.

**Si

gnifi

cant

atth

e5%

leve

l.**

*Sig

nific

anta

tthe

1%le

vel.

(.)

repr

esen

tsp-

valu

e.


Tabl

e9.

Cha

nge

inG

rang

erca

usal

ityre

sults

—ne

tbuy

Rf i,t=

λf 0+

λf 1

Rf i,t−

1+

( δf 0+

δf 1·B

Sf t

) Rd i,

t+

εf i,t

(11)

Rd i,

t=

λd 0

+λ

d 1R

d i,t−

1+

( δd 0

+δ

d 1·B

Sd t−1

) Rf i,t−

1+

εd i,

t(1

2)

Rf i,t=

kf 0+

kf 1

Rf i,t−

1+

( ωf 0+

ωf 1·B

Sf t

) Rd i,

t+

kf 3

( log

pf i,t−

1−

c 0−

c 1lo

gpd i,

t−1

) +ε

f i,t

(13)

Rd i,

t=

kd 0+

kd 1R

d i,t−

1+

( ωd 0

+ω

d 1·B

Sd t−1

) Rf i,t−

1+

kd 3

( log

pd i,t−

1−

d 0−

d 1lo

gp

f i,t−

1

) +ε

d i,t

(14)

Cor

pora

tion

λf 0(κ

f 0)

λf 1(κ

f 1)

δf 0(ω

f 0)

δf 1(ω

f 1)

κf 3

Cod

eD

.V.a

λd 0(κ

d 0)

δd 0(ω

d 0)

λd 1(κ

d 1)

δd 1(ω

d 1)

κd 3

1102

Rf t

−0.0

003

−0.0

232

0.91

140.

0000

−0.0

544

(0.7

715)

(0.3

999)

(0.0

000)

***

(0.6

190)

(0.0

000)

***

Rd t

−0.0

007

0.09

93−0

.027

60.

0000

−0.0

321

(0.5

349)

(0.0

403)

**(0

.637

6)(0

.028

1)**

(0.0

671)

*

1227

Rf t

−0.0

002

0.08

440.

7185

−0.0

000

(0.8

445)

(0.0

075)

***

(0.0

000)

***

(0.9

931)

Rd t

−0.0

005

0.13

950.

0188

−0.0

000

(0.6

787)

(0.0

017)

***

(0.7

130)

(0.3

648)

1402

Rf t

0.00

100.

0603

0.74

71−0

.000

0(0

.725

4)(0

.354

1)(0

.000

0)**

*(0

.376

8)R

d t0.

0019

0.11

36−0

.058

1−0

.000

0(0

.579

2)(0

.283

0)(0

.619

2)(0

.288

4)

1605

Rf t

0.00

40−0

.028

50.

9311

−0.0

001

−0.0

007

(0.6

288)

(0.1

618)

(0.0

000)

***

(0.1

673)

(0.6

381)

Rd t

0.01

870.

0934

−0.1

131

0.00

00−0

.006

4(0

.262

2)(0

.205

1)(0

.155

1)(0

.867

1)(0

.275

0)


2002

Rf t

−0.0

000

0.02

871.

0557

0.00

02−0

.054

5(0

.937

5)(0

.305

8)(0

.000

0)**

*(0

.285

9)(0

.000

0)**

*R

d t0.

0001

0.12

60−0

.160

0−0

.000

1−0

.012

6(0

.875

1)(0

.001

4)**

*(0

.005

6)**

*(0

.150

6)(0

.464

3)

2306

Rf t

−0.0

002

−0.0

062

1.04

700.

0001

−0.5

870

(0.8

095)

(0.7

317)

(0.0

000)

***

(0.1

820)

(0.0

000)

***

Rd t

1.00

10−0

.025

52.

0044

−0.0

001

−0.3

961

(0.4

729)

(0.7

628)

(0.9

609)

(0.4

134)

(0.0

000)

***

2311

Rf t

0.00

030.

0315

0.97

17−0

.000

1−0

.042

9(0

.813

8)(0

.257

5)(0

.000

0)**

*(0

.329

5)(0

.000

4)**

*R

d t0.

0001

0.95

020.

0307

0.00

01−0

.042

5(0

.952

4)(0

.000

0)**

*(0

.270

9)(0

.524

9)(0

.000

4)**

*

2317

Rf t

0.00

050.

1742

0.94

76−0

.000

5−0

.050

6(0

.855

8)(0

.006

8)**

*(0

.000

0)**

*(0

.010

4)**

(0.0

894)

*R

d t0.

0016

0.02

970.

0466

0.00

02−0

.117

6(0

.510

8)(0

.711

2)(0

.661

3)(0

.074

6)*

(0.0

041)

***

2324

Rf t

0.00

000.

0649

1.01

290.

0004

(0.9

906)

(0.1

700)

(0.0

000)

***

(0.0

059)

***

Rd t

−0.0

006

0.15

39−0

.192

4−0

.000

2(0

.844

9)(0

.316

0)(0

.273

9)(0

.265

9)

2325

Rf t

0.00

04−0

.046

20.

9171

−0.0

003

(0.8

030)

(0.1

420)

(0.0

000)

***

(0.0

377)

**R

d t0.

0002

0.05

90−0

.036

50.

0000

(0.8

526)

(0.0

923)

*(0

.474

6)(0

.805

7)

(con

tinu

ed)


Tabl

e9.

(Con

tinu

ed)

Cor

pora

tion

λf 0(κ

f 0)

λf 1(κ

f 1)

δf 0(ω

f 0)

δf 1(ω

f 1)

κf 3

Cod

eD

.V.a

λd 0(κ

d 0)

δd 0(ω

d 0)

λd 1(κ

d 1)

δd 1(ω

d 1)

κd 3

2330

Rf t

0.00

10−0

.115

80.

7581

−0.0

005

−0.0

198

(0.5

326)

(0.0

023)

***

(0.0

000)

***

(0.0

426)

**(0

.149

9)R

d t0.

0013

0.20

31−0

.081

2−0

.000

4−0

.059

5(0

.234

8)(0

.000

0)**

*(0

.052

1)*

(0.0

000)

***

(0.0

000)

***

2337

Rf t

0.00

02−0

.012

70.

8331

−0.0

001

−0.5

776

(0.8

766)

(0.6

630)

(0.0

000)

***

(0.4

058)

(0.0

000)

***

Rd t

−0.0

048

0.04

570.

0286

0.00

00−0

.167

9(0

.081

8)*

(0.4

318)

(0.6

582)

(0.9

477)

(0.0

075)

***

2342

Rf t

0.00

04−0

.001

20.

9929

0.00

01−0

.265

3(0

.790

8)(0

.971

2)(0

.000

0)**

*(0

.493

0)(0

.000

0)**

*R

d t0.

0056

−0.1

101

0.16

270.

0001

−0.2

724

(0.0

758)

*(0

.525

7)(0

.376

8)(0

.592

7)(0

.046

4)**

2344

Rf t

0.00

03−0

.047

31.

0162

0.00

01−0

.164

1(0

.830

8)(0

.127

5)(0

.000

0)**

*(0

.436

9)(0

.000

0)**

*R

d t0.

0008

0.07

04−0

.123

70.

0002

−0.0

598

(0.7

932)

(0.4

528)

(0.2

538)

(0.2

943)

(0.2

638)

2345

Rf t

−0.0

008

−0.0

756

1.01

910.

0000

(0.3

488)

(0.0

001)

***

(0.0

000)

***

(0.2

919)

Rd t

−0.0

001

−0.0

117

0.10

130.

0001

(0.9

473)

(0.8

719)

(0.2

227)

(0.0

196)

**


2346

Rf t

−0.0

003

−0.0

892

0.98

280.

0001

(0.6

558)

(0.0

000)

***

(0.0

000)

***

(0.4

070)

Rd t

−0.0

000

0.01

130.

1124

0.00

01(0

.995

0)(0

.888

5)(0

.201

3)(0

.569

3)

2347

Rf t

0.00

00−0

.114

70.

9797

0.00

00(0

.997

6)(0

.000

0)**

*(0

.000

0)**

*(0

.863

7)R

d t0.

0004

0.07

620.

0751

0.00

00(0

.761

1)(0

.243

9)(0

.311

3)(0

.831

7)

2357

Rf t

0.00

06−0

.038

91.

0834

−0.0

002

−0.0

643

(0.6

252)

(0.1

950)

(0.0

000)

***

(0.0

858)

*(0

.000

2)**

*R

d t0.

0009

0.10

38−0

.044

10.

0001

−0.0

770

(0.4

311)

(0.0

042)

***

(0.4

128)

(0.1

710)

(0.0

003)

***

2603

Rf t

−0.0

000

0.03

540.

8802

0.00

01−0

.019

9(0

.957

6)(0

.188

2)(0

.000

0)**

*(0

.577

9)(0

.001

9)**

*R

d t−0

.000

20.

0673

0.05

94−0

.000

0−0

.032

5(0

.820

4)(0

.186

6)(0

.323

3)(0

.762

0)(0

.036

3)**

2609

Rf t

0.00

07−0

.013

00.

8748

−0.0

002

(0.3

496)

(0.6

081)

(0.0

000)

***

(0.1

131)

Rd t

−0.0

001

0.06

70−0

.022

60.

0001

(0.9

247)

(0.2

381)

(0.7

226)

(0.2

796)

5346

Rf t

0.00

22−0

.029

80.

9597

0.00

00(0

.235

0)(0

.486

0)(0

.000

0)**

*(0

.814

0)R

d t0.

0028

0.02

050.

0237

−0.0

002

(0.4

082)

(0.8

904)

(0.8

837)

(0.3

851)

a D.V

.rep

rese

nts

depe

nden

tvar

iabl

e.*S

igni

fican

tatt

he10

%le

vel.

**Si

gnifi

cant

atth

e5%

leve

l.**

*Sig

nific

anta

tthe

1%le

vel.

(.)

repr

esen

tsp-

valu

e.


Tabl

e10

.C

hang

ein

Gra

nger

caus

ality

resu

lts—

prem

ium

and

netb

uy

Rf i,t=

λf 0+

λf 1

Rf i,t−

1+

( θf 0+

θf 1·p

rem

f t+

θf 2·B

Sf t

) Rd i,

t+

εf i,t

(15)

Rd i,

t=

λd 0

+λ

d 1R

d i,t−

1+

( θd 0

+θ

d 1·p

rem

d t+

θd 2

·BSd t−

1

) Rf i,t−

1+

εd i,

t(1

6)

Rf i,t=

kf 0+

kf 1

Rf i,t−

1+

( γf 0+

γf 1·p

rem

f t+

γf 2·B

Sf t

) Rd i,

t+

kf 3

( log

pf i,t−

1−

c 0−

c 1lo

gpd i,

t−1

) +ε

f i,t

(17)

Rd i,

t=

kd 0+

kd 1R

d i,t−

1+

( γd 0

+γ

d 1·p

rem

d t+

γd 2

·BSd t−

1

) Rf i,t−

1+

kd 3

( log

pd i,t−

1−

d 0−

d 1lo

gp

f i,t−

1

) +ε

d i,t

(18)

Cor

.λ

f 0(κ

f 0)

λf 1(κ

f 1)

θf 0(γ

f 0)

θf 1(γ

f 1)

θf 2(γ

f 2)

κf 3

Cod

eD

.V.a

λd 0(κ

d 0)

θd 0(γ

d 0)

λd 1(κ

d 1)

θd 1(γ

d 1)

θd 2(γ

d 2)

κd 3

1102

Rf t

−0.0

010

−0.0

127

0.95

97−1

.202

60.

0000

−0.0

572

(0.2

850)

(0.6

440)

(0.0

000)

***

(0.0

003)

***

(0.7

092)

(0.0

000)

***

Rd t

−0.0

009

0.04

34−0

.006

90.

6120

0.00

00−0

.031

1(0

.418

6)(0

.444

4)(0

.907

9)(0

.062

0)*

(0.0

331)

**(0

.075

9)*

1227

Rf t

−0.0

007

0.08

120.

8007

−0.5

711

0.00

00(0

.506

7)(0

.009

8)**

*(0

.000

0)**

*(0

.018

7)**

(0.9

338)

Rd t

−0.0

005

0.15

380.

0185

−0.1

088

−0.0

000

(0.6

745)

(0.0

050)

***

(0.7

185)

(0.6

547)

(0.4

754)

1402

Rf t

0.00

070.

0646

0.79

02−0

.260

4−0

.000

0(0

.828

2)(0

.332

2)(0

.000

0)**

*(0

.743

6)(0

.352

7)R

d t0.

0015

−0.2

796

0.00

361.

6147

−0.0

000

(0.6

548)

(0.1

191)

(0.9

751)

(0.0

078)

***

(0.2

178)

1605

Rf t

0.00

40−0

.028

40.

9316

−0.0

000

−0.0

001

−0.0

007

(0.6

294)

(0.1

631)

(0.0

000)

***

(0.9

572)

(0.1

677)

(0.6

388)

Rd t

0.01

880.

1373

−0.1

393

−0.8

032

0.00

00−0

.006

4(0

.259

8)(0

.100

0)(0

.093

0)*

(0.2

623)

(0.8

310)

(0.2

751)


2002

Rf t

−0.0

000

0.03

031.

0918

−0.0

001

0.00

02−0

.054

6(0

.951

5)(0

.281

4)(0

.000

0)**

*(0

.475

9)(0

.295

8)(0

.000

0)**

*R

d t0.

0000

0.08

95−0

.138

80.

3041

−0.0

000

−0.0

097

(0.9

511)

(0.0

673)

*(0

.020

9)**

(0.2

092)

(0.2

970)

(0.5

761)

2306

Rf t

−0.0

002

−0.0

065

1.03

760.

0000

0.00

01−0

.586

0(0

.791

1)(0

.721

4)(0

.000

0)**

*(0

.546

1)(0

.192

0)(0

.000

0)**

*R

d t0.

0001

−0.0

385

0.02

933.

1092

−0.0

001

−0.3

908

(0.9

193)

(0.6

481)

(0.7

429)

(0.0

088)

***

(0.2

745)

(0.0

000)

**

2311

Rf t

0.00

020.

0306

0.95

840.

0001

−0.0

001

−0.0

429

(0.8

434)

(0.2

725)

(0.0

000)

***

(0.6

022)

(0.3

659)

(0.0

004)

***

Rd t

0.00

040.

0818

−0.0

944

−0.0

053

0.00

00−0

.043

7(0

.768

1)(0

.188

8)(0

.106

8)(0

.980

0)(0

.794

8)(0

.002

9)**

2317

Rf t

0.00

050.

1759

0.96

18−0

.000

0−0

.000

5−0

.051

0(0

.844

2)(0

.006

9)**

*(0

.000

0)**

*(0

.848

1)(0

.011

5)**

(0.0

887)

*R

d t0.

0018

0.09

430.

0491

−0.1

790

0.00

02−0

.114

8(0

.468

7)(0

.584

5)(0

.645

8)(0

.671

9)(0

.071

1)*

(0.0

058)

***

2324

Rf t

0.00

010.

0778

0.96

450.

0004

0.00

04(0

.971

6)(0

.102

4)(0

.000

0)**

*(0

.095

5)*

(0.0

061)

***

Rd t

−0.0

005

0.24

81−0

.247

2−1

.560

2−0

.000

3(0

.874

5)(0

.188

8)(0

.187

1)(0

.388

1)(0

.180

4)

2325

Rf t

0.00

04−0

.039

61.

0009

−0.0

004

−0.0

003

(0.7

704)

(0.2

079)

(0.0

000)

***

(0.0

054)

***

(0.0

249)

**R

d t0.

0004

0.08

45−0

.041

9−0

.112

90.

0000

(0.7

871)

(0.1

294)

(0.4

192)

(0.5

554)

(0.7

097)

(con

tinu

ed)


Tabl

e10

.(C

onti

nued

)

Cor

.λ

f 0(κ

f 0)

λf 1(κ

f 1)

θf 0(γ

f 0)

θf 1(γ

f 1)

θf 2(γ

f 2)

κf 3

Cod

eD

.V.a

λd 0(κ

d 0)

θd 0(γ

d 0)

λd 1(κ

d 1)

θd 1(γ

d 1)

θd 2(γ

d 2)

κd 3

2330

Rf t

0.00

08−0

.120

90.

6981

0.00

02−0

.000

4−0

.019

8(0

.602

8)(0

.001

6)**

*(0

.000

0)**

*(0

.353

4)(0

.073

8)*

(0.1

496)

Rd t

0.00

150.

2390

−0.0

834

−0.0

916

−0.0

004

−0.0

595

(0.1

838)

(0.0

000)

***

(0.0

465)

**(0

.375

9)(0

.000

0)**

*(0

.000

0)**

*

2337

Rf t

0.00

00−0

.015

30.

7971

0.00

02−0

.000

1−0

.573

0(0

.996

3)(0

.600

6)(0

.000

0)**

*(0

.074

5)*

(0.4

442)

(0.0

000)

***

Rd t

−0.0

055

0.04

280.

0331

1.35

86−0

.000

0−0

.172

3(0

.046

3)**

(0.4

607)

(0.6

081)

(0.0

908)

*(0

.999

7)(0

.006

0)**

*

2342

Rf t

0.00

040.

0019

1.01

38−0

.000

20.

0001

−0.2

643

(0.7

814)

(0.9

568)

(0.0

000)

***

(0.2

635)

(0.5

541)

(0.0

000)

***

Rd t

0.00

53−0

.079

20.

1627

1.40

150.

0001

−0.2

728

(0.0

954)

*(0

.658

0)(0

.377

5)(0

.471

2)(0

.723

4)(0

.046

5)**

2344

Rf t

0.00

03−0

.047

41.

0042

0.00

000.

0001

−0.1

642

(0.8

220)

(0.1

271)

(0.0

000)

***

(0.7

198)

(0.4

330)

(0.0

000)

***

Rd t

0.00

080.

0957

−0.1

383

−0.6

757

0.00

02−0

.064

9(0

.801

0)(0

.354

4)(0

.214

2)(0

.557

5)(0

.406

6)(0

.231

8)

2345

Rf t

−0.0

008

−0.0

755

1.01

170.

0332

0.00

00(0

.391

1)(0

.000

1)**

*(0

.000

0)**

*(0

.749

0)(0

.276

2)R

d t−0

.000

10.

0023

0.09

89−0

.054

30.

0001

(0.9

606)

(0.9

783)

(0.2

355)

(0.7

492)

(0.0

226)

**


2346

Rf t

−0.0

004

−0.0

891

0.99

04−0

.000

20.

0001

(0.6

051)

(0.0

000)

***

(0.0

000)

***

(0.2

012)

(0.4

252)

Rd t

−0.0

000

0.00

840.

1138

0.03

150.

0001

(0.9

949)

(0.9

228)

(0.2

036)

(0.9

322)

(0.5

671)

2347

Rf t

0.00

00−0

.114

10.

9829

−0.0

001

0.00

00(0

.978

1)(0

.000

0)**

*(0

.000

0)**

*(0

.593

5)(0

.872

6)R

d t0.

0003

0.06

270.

0827

0.37

610.

0000

(0.8

428)

(0.3

647)

(0.2

720)

(0.5

535)

(0.8

488)

2357

Rf t

0.00

06−0

.040

61.

0715

0.00

02−0

.000

2−0

.064

3(0

.655

4)(0

.178

4)(0

.000

0)**

*(0

.462

9)(0

.087

6)*

(0.0

002)

***

Rd t

0.00

100.

1357

−0.0

576

−0.1

711

0.00

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stocks in equations (5) and (7). On the other side, four samples report that the transmissioneffects have been changed in equations (6) and (8) when the premium is considered. Thatis, the premium has significant impact on international price transmission for one fifth toone third of samples. However the impact may amplify or reduce the transmission effectsince the signs of β

f1 (φ

f1 ) are ambiguous.

The results from Granger Causality involving QFII’s net buy are shown in Table 9. Taiwanstock market is still dominant and the foreign market is a satellite. The result is similar to thestated outcomes above. In addition, QFII’s net buy significantly influences the price trans-mission effect of twenty percent samples and the direction of net buy effect is also obscured.

Finally, Table 10 illustrates the results from Granger Causality, including both the pre-mium and QFII’s net buy factors. The outcomes are quite consistent with the Table 8 andTable 9. The premium and QFII’s net buy still have significant impact on international pricetransmission for the same samples. These results prove the robustness of our models.

4. Conclusion

This paper studies the price transmission effect between ADRs or GDRs and their re-spective underlying stock. The selected samples cover twenty-one sponsored DRs issuedby Taiwan listing companies from October 8, 1997 to May 31, 2000. We use Granger teststo examine causal relations between the returns of both capital markets. Error-correctionmodel is employed to analyze the long run causal relations when the stock returns data isnonstationary.

Results reveal unidirectional causality from Taiwan’s capital market to foreign markets.This asymmetry suggests the domestic market plays a dominant role relative to the for-eign market. At the same time, the prices of both markets will make opposite adjustmentto establish the long run cointegrated equilibrium. An additional finding is that both thepremium and QFII’s net buy have significant impacts on international price movement forover twenty percent samples. Empirical outcomes provide the evidence that the modelspresented in this paper are quite robust.

Notes

1. One anonymous reviewer indicates that the premium or discount is an important variable for closed-endfunds. However, there are a few differences in premium concept between ADRs and closed-end funds. ADRsand underlying securities are two separately traded assets and their prices may exist lead-lag relation in bothdirections, thus causes the possible price premium or discount across different markets. The net asset value(NAV) of a closed-end fund is not marketable. NAV may affect the market price of a closed-end but not thereverse.

2. QFIIs (Qualified Foreign Institutional Investors) refer to foreign banks, insurance companies, securities firms,fund management institutions and other investment institutions who meet the qualifications set by the Secu-rities and Futures Commission, Taiwan, R.O.C.

3. A spurious regression has a high R2, t-statistics that appear to be significant, but the results are without anyeconomic meaning. The regression output “looks good” because the least-squares estimates are not consistentand the customary tests of statistical inference do not hold.

4. For a review of arbitrage and market efficiency of ADR markets, see Karolyi (1998).


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Price Transmission Effect between GDRs and Their