DYNAMIC LINKAGES OF ASIAN STOCK MARKETS

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DYNAMIC LINKAGES OF ASIAN STOCK MARKETSAhmad Zubaidi Baharumshah a , Tamat Sarmidi b & Hui Boon Tan aa Universiti Putra Malaysiab Universiti Kebangsaan MalaysiaPublished online: 06 Oct 2010.

To cite this article: Ahmad Zubaidi Baharumshah , Tamat Sarmidi & Hui Boon Tan (2003) DYNAMIC LINKAGES OF ASIANSTOCK MARKETS, Journal of the Asia Pacific Economy, 8:2, 180-209, DOI: 10.1080/1354786032000074730

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Journal of the Asia Pacific Economy

8(2)

2003: 180–209©2003 Taylor & Francis Ltd

ISSN 1354–7860 print/ISSN 1469–9648 onlineDOI: 10.1080/1354786032000074730

D

YNAMIC LINKAGES OF ASIAN

STOCK MARKETS

An analysis of pre-liberalization and post-liberalization eras

Ahmad Zubaidi Baharumshah, Tamat Sarmidi and Hui Boon Tan

Abstract

This study examines the dynamic interrelationship among the majorstock markets and in the four Asian markets (Malaysia, Thailand, Taiwan and SouthKorea), both in the short run and in the long run. To investigate the impact offinancial reforms and the Asian financial crisis on these markets, we split the sampleinto three sub-periods: pre-liberalization (1988–91), post-liberalization (1992–96)and post-crisis (1997–99) periods. The empirical results suggest that all the Asianmarkets are closely linked with each other and with the world capital markets,namely those of the US and Japan, over the post-liberalization era. Overall, theevidence shows that the degree of integration between the Asian emerging marketsand the US increased following the deregulation period, and that the relationshiphas intensified since the onset of the Asian crisis. There is no evidence to show thatJapan has overtaken the US in dominating the Asian equity markets. In addition, ourresults show that the interrelationship among the Asian national markets has beenaffected by the crisis. Specifically, the crisis-affected countries of Malaysia andThailand are increasingly interrelated with South Korea and Taiwan in thepost-crash period.

Keywords

Cointegration, integration, financial crisis, stock markets.

JEL classification

C32, F36, G12.

1 . INTRODUCTION

In recent years, considerable attention has been focused on the interdependenceamong the major world equity markets.

1

In an integrated world equity market,national stock prices are expected to have long-run relationships. The 1987October stock market crash has had pronounced effects on world markets, indi-cating that the world equity markets are well integrated. The US exerts a stronginfluence on the smaller capital markets while the smaller markets have littleinfluence on the US market.

2

The recent financial crisis in East Asia is yet another

74Q 03zubaidi (ds) Page 180 Friday, May 2, 2003 11:07 PM

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DYNAMIC LINKAGES OF ASIAN STOCK MARKETS

181

episode to indicate that national equity markets are closely linked. The crisis thatstarted in Thailand in July 1997 spread contagiously throughout Southeast Asia,South Korea, Taiwan and Japan. The crisis has not only been disastrous foreconomies in this region, but it has also put the global financial system understress. Given the rapid pace of internationalization of the financial markets andthe development of telecommunication networks, these episodes should be of nosurprise.

The issue of whether there exists a global integrated market has implications forasset-allocation strategies. A portfolio that is internationally diversified carries lessrisk than one that is purely domestic. In general, the less the national markets areconnected with other exchanges, the greater is the benefit of international diversi-fication.

3

Moreover, a fully integrated domestic market cannot insulate foreignshocks since assets are priced according to international factors. Therefore, under-standing the mechanism through which stock price movements are transmittedacross national markets has important implications for pricing of securities andhedging, as well as trading strategies. The main objective of this paper is toexamine the dynamic relationship among the major stock markets and four Asianmarkets (Malaysia, Thailand, South Korea and Taiwan) both in the short run andin the long run. It is well known that linkages among stock markets may vary overtime. In this paper we also attempt to see whether financial reforms and the recentAsian financial crisis have any influence on the degree of linkages among theemerging markets and between emerging markets and the developed markets.

The main contributions of this paper are threefold. First, we utilized somerecent econometric technique based on vector time-series analysis to investigatethe dynamic causal linkage among the national stock returns. We utilized themultivariate cointegration technique based on the work of Johansen (1988) andJohansen and Juselius (1990) to determine the number of stochastic trends amongthe stock indices, and the vector error-correction model (VECM) to detect thecausal relationships among the stock markets. Besides providing the causal rela-tionships among the markets, the present study also shows to what extent and howrapid shocks induced by innovations in one market are borne by other markets.Second, we seek to examine if there are linkages among the emerging Asian stockmarkets and examine their nature of linkage with respect to the establishedmarkets ( Japan and the US). In this way, we hope to complement the existingliterature on global financial integration since empirical work on these emergingmarkets is still lacking. Third, this study brings out the effect of financial reformsin Asia on the financial integration of the equity markets in the region by usingmore recent data.

Authors such as Faruqee (1992), Reisen and Yeches (1993) and Phylaktis (1997),among others, found that there is a substantial financial integration betweendomestic and international markets in Japan, Hong Kong, Singapore andMalaysia. However, the views on linkages of financial markets are mixed forThailand and Korea while the case of Taiwan is found to be rather limited. For


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AHMAD ZUBAIDI BAHARUMSHAH

ET AL

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182

instance, Phylaktis using real interest differentials showed that the degree offinancial market integration during the 1980s compared to the 1970s hasincreased both versus the US and Japan. In addition, Baharumshah and Ariff(1997) based on the purchasing power parity (PPP) relationship found that in mostof the ASEAN countries the goods and financial markets are well integrated withthe global markets in the long run.

Prior research that sought to test the linkages among the national equitymarkets in East Asia has mainly focused on the dynamic economies of HongKong, Singapore, Taiwan and Korea. The evidences reported in these studies aremixed, depending on the time period and the methodology used in the analysis.For example, Cheung and Lee (1993) and Chan

et al

. (1992) showed that theequity markets are segmented, while Cheung and Mak (1992) and Masih andMasih (1997a, 1997b, 1999) found evidence that they are strongly integrated.Specifically, they found that the US is a global factor affecting both the developedand developing markets. This mixed nature of empirical findings has inspiredfurther studies in search of an answer to the puzzle.

To preview our results, we find that the long-run relationship among the stockmarkets is affected to a greater extent by the financial reforms. The Asianmarkets are fully integrated with the global markets, namely the US and Japanin the post-liberalization era. Our results do not contradict with the widelymade observations: deregulation of financial markets and international capitalmobility appear to be an important factor in determining the interrelationshipof national stock markets with the global financial centres. Second, the US is theprice leader in the Asian countries in all the three periods, reflecting thepersisting dominant role of the US stock market. Although the influence ofJapan in the region can be traced back to the late 1980s, there is no evidence toshow that Japan has overtaken the US in dominating the Asian equity markets.Third, Thailand appears as the most interactive market in the region in thepre-liberalization era while Malaysia emerged as the most active market in thepost-liberalization and post-crash period. Fourth, the regional markets have astrong influence on Taiwan’s (South Korea’s) markets when the US ( Japan)impact is isolated in the post-crisis period. These findings indicate that therelative predictive power among the stock markets is affected by financial crisisand/or changing economic situation in the region. Specifically, the degree ofintegration between Asian emerging markets and the US increased following thederegulation period, and the relationship has intensified since the onset of theAsian financial crisis.

The rest of the paper is organized as follows. In the next section, we begin witha brief overview of the macroeconomic environments and Asian stock markets.Section 3 describes the data and methodology utilized in the analysis. Theempirical results concerning the interrelationship among the stock markets arepresented in section 4. Finally, section 5 concludes the paper.


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2 . MACROECONOMIC ENVIRONMENTS AND ASIAN STOCK MARKETS

In this study, the sample countries consist of two NIEs (newly industrializedeconomies, namely Korea and Taiwan), two ASEAN members (Malaysia andThailand) and two established markets (the US and Japan). The reasons forchoosing the four Asian stock markets are as follows. First, these markets offer awindow of opportunities to foreign investors due to their potential and favourablegrowth track records.

4

Not only have they achieved average annual rates wellabove the world average growth, they have also managed to sustain such rates fora long period. Rapid economic growth was accompanied by an increase in size oftheir stock markets, and, according to some observers, the most active stocks inseveral of these markets appear to be as liquid as those in the equity markets of theindustrialized countries.

5

Second, the 1997 Asian financial crisis started inThailand and spread contagiously to the other East Asian countries. Malaysia andSouth Korea are among the countries most affected by the slowdown in theregion. These stock markets are currently suffering from the recent financial crisis.Finally, we have included Taiwan because it is one of the fastest-growing emergingequity markets, but it is also known as one of the most restrictive emerging marketsin the global financial market.

There are several explanations as to why national stock markets may share acommon stochastic trend. The presence of strong economic ties and policycoordination among the relevant countries can link their stock prices over time(Choudhry 1996). This point has also been emphasized recently in Masih andMasih (1999). Specifically, they pointed out that the intra-regional stock marketdependency is partly due to the growing share of intra-regional trade and invest-ment in the Asian region. In addition, all the countries sampled for this studyfollowed a conservative monetary policy and most of their currencies are peggedto the US dollar. As shown in Table 1, the East Asian currencies remained fairlystable before the financial crisis erupted in July 1997.

In the past two decades, all these countries have implemented a series of policyreforms to deregulate the pricing of their financial markets, lift restrictions oncapital inflows and relax foreign exchange controls. The timing as well as theextent of the liberalization programmes vary across countries. For instance,Malaysia ( Japan) took steps toward liberalization of the financial markets in themid-1980s. Later, Thailand took a significant step towards liberalization in the late1980s, while Korea and Taiwan took a little longer, and started reforms only in theearly 1990s. The recent reforms include the removal of various restrictions oninternational investors in the equity markets.

6

Consequently by 1992, most ofthese economies had opened up to foreign portfolio investors although someregulations remain and continue to limit the scope of international participationin some of these equity markets. Major progress in computer technology, improve-ments in communication technology, innovation in financial products in recent


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Table 1

Statistics of East Asian countries, 1988–1997

Macro variables 1988 1991 1994 1997

Malaysia

RGDP (%) 9.94 9.54 9.21 7.32Trade/Balance (RM Mn) 11,967 –6,334 –2,000 –45Inflation (%) 1.97 4.34 3.73 2.71Interest Rate 3M(T.B) (%) 4.124 7.62 4.51 6.76Saving Deposit (%) 6.75 6.55 6.55 10.25Current Account 1,659 –4,271 –4,786 –4,736Exchange Rate (RM/US) 2.71 2.72 2.56 3.89

South Korea

RGDP (%) 10.46 9.23 5.49 5.01Trade/Balance (US Mn) 8,886 –9,655 –6,335 –8,452Inflation (%) 7.14 9.34 6.28 4.44Lending Rate 12.00 11.25 10.50 15.32Saving Deposit 5.00 3.00 3.00 5.13Current Account –14,505 –8,317 –3,867 –8,167Exchange Rate (Won/US) 684.10 760.80 788.70 1,695.00

Taiwan

RGDP (%) 7.84 7.55 7.11 6.68Trade/Balance (NT Mn) 308,703 350,000 194,400 205,591Inflation (%) 1.29 3.59 4.11 0.90Prime Lending Rate 7.00 8.00 8.00 7.65Saving Deposit 3.50 3.50 3.50 3.50Current Account 10,200 12,468 6,498 7,851Exchange Rate (T/US) 28.17 25.75 26.24 32.64

Thailand

RGDP (%) 13.29 8.56 8.95 –1.68Trade/Balance (Baht Mn) –109,544 –233,201 –231,437 –117,582Inflation (%) 3.74 5.73 5.04 5.53Prime Lending Rate 12.00 14.00 11.75 15.25Saving Deposit 7.25 8.50 5.00 5.00Current Account –1,756 –7,682 –8,929 –3,587Exchange Rate (Baht/US) 25.240 25.280 25.090 47.25

Japan

RGDP (%) 8.21 6.33 0.87 1.47Trade/Balance (Yen Bill.) 9,896 10,474 12,419 9,827Inflation (%) 0.77 3.23 0.73 1.70Lending Rate 4.94 7.22 4.06 2.38Deposit Rate 1.76 3.25 1.71 0.29Current Account (Mill. US) 79,610 72,910 130,260 94,350

Exchange Rate (Yen/US) 125.85 125.20 99.74 129.95

Source

: All data are from Asian Development Bank except for Japan’s lending rate and deposit rate. Thelending rate and deposit rate are taken from

International Financial Statistics

, International MonetaryFund.


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years may have also induced the integration of national stock markets (Blackman

et

al

. 1994; Jeon and Chiang 1991). The ASEAN member countries are much moreopen to foreign direct investment than the Northeast Asian countries (Taiwan,Korea and Japan). In addition, Northeast Asian firms relied more heavily on debtfinancing in the early stage of their development than ASEAN firms, which wereready to raise funds through equity issues. As a result the ASEAN financial marketsdeveloped more quickly than in Northeast Asian markets.

Until 1996, economic fundamentals looked good in East Asia. These econo-mies recorded stable exchange rates and low inflation and interest rates (see Table1). According to Chuppe

et al

. (1989) a favourable economic environment canfacilitate the expansion of both domestic and international financial markets. In1995, market capitalization ranged from $222.7 billion in Malaysia to $141.5billion in Thailand ( Japan recorded $3.6 trillion in the same year). The number oflisted companies ranged from 721 in South Korea to 347 in Taiwan. The highestmarket capitalization took place in Thailand (295 per cent) and the lowest tookplace in Taiwan (50 per cent) over the 1991–95 period.

7

Foreign capital flowed ataccelerating rates in South Korea, Thailand and Malaysia throughout the 1990s.On a cumulative basis, from 1987–96, Korea received $80 billion, Thailandreceived $75 billion, and Indonesia and Malaysia received $68 billion each. Theseinflows averaged nearly 12 per cent of GDP per year in Malaysia, followed by 7.4per cent in Thailand and 5.1 per cent in Korea.

The combination of high saving rates and large capital inflow produced aninvestment boom across much of the region.

8

The phenomenal economic growthin the 1988–95 period (see Table 1) is partly due to heavy capital inflows in theform of FDI (and also portfolio equity investments).

9

The pouring-in of interna-tional funds in the 1990s led to rapid domestic credit expansion. Foreign capitalwas channelled into sectors that were relatively open, such as properties andequities, leading to skyrocketing stock and real estate prices in basically all coun-tries in East Asia.

10

The pre-crisis fundamentals for 1996 (Table 1) reveal that the Asian financialcrisis cannot be attributed to bad macroeconomic fundamentals. However, anumber of stylized facts did give clear warning of a looming crisis. The appreci-ation of the real exchange rate due to the strengthening of the US anchorcurrency against the yen undermined the competitiveness of exports of thesecountries. At the same time the world was experiencing overproduction oflabor-intensive exports: textiles, clothing and footwear; motor car and compo-nents; and semiconductors. The massive influx of foreign capital in the 1990scontributed to high current account to GDP ratio, which averaged 5.5 per cent(Table 1). National banks borrowed excessively abroad and lent excessively athome. Much of the capital inflow was inefficiently allocated as reflected by thehigh ratio of non-performing loans in Thailand (19 per cent), Malaysia (18 percent), Indonesia (17 per cent), Korea (16 per cent) and the Philippines (14 percent). Investors’ confidence deteriorated before the crisis hit the region. Indeed,


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stock markets in Korea and Thailand had been under pressure since the begin-ning of 1996. In Malaysia, the pressure began in early 1997. When Thailandwas forced to devalue the baht on 2 July 1995, the pressure spread quickly acrossthe region and triggered a massive reversal of capital flows in East Asia. Thecapital outflows led to a sharp fall in the exchange rates. The pegging exchangerate regime and the banking sector collapsed at the same time. The panic soonspread to the stock markets. While the East Asian countries were the worstaffected, the crisis spilled over to many other countries as far as Australia, LatinAmerica and Russia.

11

3 . DATA AND METHODOLOG Y

The study uses the natural logs of weekly local currency-denominated stockindices from January 1988 to December 1999. The stock market indices do notdouble-count those stocks with multiple listing on foreign exchanges. Conse-quently, any observed interdependence among stock markets cannot be attributedto multiple listings. We tested for long-run relationship(s) among national stockmarkets by using two separate models: [US, Korea, Taiwan, Malaysia, Thailand]and [ Japan, Korea, Taiwan, Malaysia, Thailand].

12

The modelling strategyallows for evaluating the relative importance of the world’s two largest markets onthe smaller markets, and innovations from the US and Japanese markets may beviewed as shocks from the world and regional markets, respectively.

Weekly rather than daily data are chosen to avoid the potential biases associatedwith micro-structure issues, non-trading, the bid–ask spread effect in daily dataand problems of thin trading which are often associated with most emergingmarkets. The data employed in the analysis are obtained from the Bloombergfinancial services. The indices used are the Korean Composite Index, the KualaLumpur Stock Exchange Composite Index, the Taiwan Stock ExchangeWeighted Price Index, the Stock Exchange of Thailand Index, the Standard &Poor’s 500 Index and the Tokyo Stock Price Index. As in most past analyses, thestock indices are in local currency-denominated stock price indices.

13

To investi-gate the possible differences of the long-run relationship among the stated indicesas a result of the major economic events in the region, the data are divided intothree sub-periods: (i) the pre-liberalization period 1988:01–1991:52; (ii) thepost-liberalization period 1992:01–1996:52; and (iii) the post-crisis period1997:01–1999:50.

To get a visual impression of the interrelationship among the stock indices, weplotted the six indices in Figure 1. There are three noteworthy points. First,Thailand, Korea and Malaysia showed a strong rise in stock prices in the periodpreceding the 1997 crisis and the biggest drop occurred in 1997–98. Second, theTaiwanese market appeared to be the least affected by the recent crisis among thefour Asian markets. Third, the US market trended upwards while the Japanesemarket fluctuated around a narrow band during the sample period. However,


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studying the plots alone will not allow us to arrive at a conclusion with regard tomarket integration, especially during the post-crisis period.

The prerequisite condition for the series to be cointegrated is that the seriesmust have the same order of integration. Schwert (1987) and DeJong

et al

. (1992)have noted that the augmented Dickey–Fuller (ADF) statistics may reject the nullhypothesis of unit root too often in the presence of the first-order moving averageprocess. However, Campbell and Perron (1991) have shown that the ADF statisticshave better small-sample properties. Both the ADF (Dickey and Fuller 1981) andPhillips–Perron (PP) (Phillips and Perron 1988) are utilized in the analysis in orderto avoid the criticism of any individual testing technique.

Once we had determined the order of integration of each series, the next stepwas to test for cointegration relationships among the series. We employed themaximum-likelihood cointegration test attributed to Johansen (1988) andJohansen and Juselius (1990). The Johansen–Juselius test is utilized to prove thenumber of linearly independent cointegrating vectors in the system. Theprocedure provides more robust results than other methods when there are morethan two variables (Gonzalo 1994). If a non-zero vector is indicated by these tests,a stationary long-run relationship is implied. The Johansen approach sets up thenon-stationary time series (

Y

) as a vector autoregression (VAR):

(1) ∆Yt µ Γ i∆Yt i– ΠYt k– et+ +

i 1=

k 1–

∑+=

Figure 1

Asian and US stock markets


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where

Γ

i

= –(

I

–

Π

1

– . . . –

Π

i

) and

Π

i

= –(

I

–

Π

1

– . . . –

Π

k

) for

i

= 1, . . .,

k

– 1

Y

t

is a vector of

p

variables,

µ

are the intercepts and

e

t

is a vector of Gaussianrandom variables.

The matrix

Π

is called the long-run impact matrix and it contains informationabout the long-run relationship between variables. The number of cointegratingvectors is determined by the rank (

r

) of the matrix

Π

, which indicates the numberof cointegrating vectors. If

Π

is of full rank, or

r

=

p

, no cointegration is present asall series are themselves stationary. On the other hand, if

Π

is a null matrix, or

r

=0 then no long-run relationship is present as equation (1) is the usual VAR modelin first differences. In the case when 0 <

r

<

p

, then there exist one or morecointegrating relationships among the variables. The Johansen procedure uses twolikelihood ratio statistics to test for cointegration vectors – the trace statistic andmaximum eigenvalue (

λ

max

) statistics. These test statistics may be compared withthe appropriate critical values provided by Osterwald-Lenum (1992).

If cointegration is found, then the Granger causality, variance decomposition andimpulse response analyses must be carried out based on the vector error-correction(VEC) model (Engle and Granger 1987). Otherwise, the analyses may be conductedusing a standard vector-autoregressive (VAR) model. The forecast variance decom-position analysis shows the proportion of the changes in the price in a particularmarket arising out of random shocks from other markets. The novelty of ImpulseResponse Functions (IRF) is that it also quantifies the magnitude of responses tounanticipated shocks. This further helps analysts to predict the direction as well asthe momentum of market responses to a shock in other markets.

4 . EMPIRICAL RESULTS

(a) Unit root and cointegration tests

We employed the classical unit root tests discussed earlier to the stock price seriesfor the whole sample as well as the three sub-periods. Akaike InformationCriterion (AIC) is used to ensure a sufficient number of lags are employed in theunit root tests. In addition, lags that were insignificant were dropped from theformulation, unless their elimination produced serial correlation. The computedADF and PP test statistics for the three time periods are all insignificant at the 5per cent significance level based on critical values given in MacKinnon (1991).The results failed to reject the null hypothesis of unit roots in their level form in theautoregressive representation of each stock price, thus implying that there is nopossibility of the series being stationary around a constant mean or around adeterministic linear trend. Unit root tests on the first difference for all series yieldstatistics that are significant at conventional significance levels. The results hold for


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all three sample periods, thus confirming that stock indices from all countries areintegrated of order one. To conserve space the results of the unit root tests are notreported here.

14

We employed the Johansen methodology to the two five-dimensional vectorautoregression models of stock indices for the whole sample period: [US, SK, TW,KL, TH] and [ JP, SK, TW, KL, TH]. The required number of lags in the VARsis selected by means of the AIC. Results of the cointegration tests for the wholesample period are shown in Panel A of Table 2. Briefly, the empirical results maybe summarized as follows. First, cointegration relationship is found in the twosystems. Specifically, one significant cointegrating vector is found in both the USand Japanese models based on the

λ

max

test. Second, the sampling period ismarked by instability in the Asian equity markets. In all cases, a single break seemsto occur in late 1991 based on the cumulative sum square (CUSUM) test. Resultsof the Johansen iterative

λ

max

tests for

p

= 0 were also found to be unstable,rejecting the null hypothesis of

p

= 0 for some period while failing to reject it inother periods.

15

To examine the effect of financial reforms and the recent financial crisis onthese emerging markets, we divided the sample period into three sub-periods:the pre-liberalization era (1988:01–1991:52), the post-liberalization era(1992:01–1996:52) that ended prior to the crisis, and the post-crisis era(1997:01–1999:50).

16

The reason for the sub-sample analysis is because ourpreliminary results indicate that the sampling period is characterized by struc-tural breaks, which coincide with the major economic events in the region.Table 2 summarizes the main results from the cointegration tests for the threesampling periods.

(i) US model

When the US is included in the five-dimensional VAR model (Table 2, Panel B),the results are not supportive of an internationally integrated equity market inthe first sub-period. Chowdhury (1994) also reported the absence of a cointe-grating relationship among the major Asian stock markets ( Japan, Korea,Taiwan, Singapore, Hong Kong) and the US using daily indices from 2 January1986, and ending on 30 December 1990. However, Panel C shows that bothtrace and

λ

max

statistics are significant at the 10 per cent level or better for thenull hypothesis of no cointegrating vector hypothesis (

r

= 0) over the post-liber-alization era. We may conclude that there exists (

p

–

r

) = 4 common stochastictrends among each of the stock markets in the US model after the deregulationperiod. The empirical results suggest that structural changes due to theopening-up of these markets affect the co-movements of national stock prices.The results may also indicate the increasing dominance of the US marketinfluence in the region. Specifically, the sub-period analyses suggest that finan-cial reforms affect the stability of the system by altering the number of common


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stochastic trends.

17

Interestingly, we found that the unique cointegrating vectorfound in the post-liberalization period (1992–97) seems to be unaffected by thefinancial crisis.

(ii) Japan model

We performed the cointegration tests for the three sub-periods using Japan as theestablished market. Panel B (Table 2) shows that both

λ

max

and trace statisticsidentify two cointegrating vectors in the system in the pre-liberalization era. Weview this strong intra-regional stock market relationship as partly due to thegrowing intra-regional trade and investments in the Asian region (see Masih andMasih 1999). For the post-liberalization period (Panel C), the null hypothesis of

Table 2

Johansen and Juselius’s test for multiple cointegrating vectors

Null hypothesis

US model Japan model

λ

max

Trace

λ

max

Trace

Panel A: Full sample (1988:01–1999:50)

r

= 0 34.79** 65.67 41.67** 69.08

r

≤

1 18.03 30.88 17.19 27.41

r ≤ 2 8.04 12.85 6.49 10.22r ≤ 3 3.77 4.81 3.11 3.72r ≤ 4 1.03 1.03 0.61 0.61

Panel B: Pre-liberalization (1988:01–1991:52)r = 0 28.47 63.90 57.96** 109.70**r ≤ 1 17.01 35.43 28.02* 51.73*r ≤ 2 10.18 18.41 14.25 23.14r ≤ 3 7.03 8.23 5.84 9.24r ≤ 4 1.20 1.20 3.62 3.62

Panel C: Post-liberalization (1992:01–1997:02)r = 0 34.76** 72.62* 39.58** 81.83**r ≤ 1 21.14 34.86 23.91 42.26r ≤ 2 7.43 13.72 12.14 18.34r ≤ 3 5.94 6.28 5.83 6.20r ≤ 4 0.33 0.33 0.36 0.36

Panel D: Post-crisis (1992:01–1999:50)r = 0 45.79** 86.20** 43.50** 98.22**r ≤ 1 19.58 40.40 37.95 54.72**r ≤ 2 9.75 20.81 8.91 16.76r ≤ 3 6.99 11.06 6.48 7.84r ≤ 4 4.06 4.06 1.36 1.36

Note: The optimal lag structure for each of the VAR models is selected by using the Akaike’s FPEcriteria. Critical values are sourced from Osterwald-Lenum (1992).** and * indicate rejection at the 5 and 10 per cent critical values, respectively.


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zero cointegrating vectors (H0: r = 0) is easily rejected. The single vector, whichrepresents a distinct long-run relationship, tied the markets in a manner differentfrom the earlier period.18 This finding is partly due to the fact that for most of the1990s, the Japanese economy was in recession while the other Asian countrieswere growing rapidly over the same period.

The results of cointegration tests in this model suggest that the Johansenprocedure is sensitive to the sampling period. Indeed the trace test in Panel D findstwo cointegrating vectors for the post-crisis period. The greater the vectors, themore stable the relationship; hence the relationship appears to be most stable inrecent years. As shown by Choudhry (1996) the presence of strong economic tiesand policy coordination among countries can link their equity markets. To thedegree that one country’s economy can influence the economies of other coun-tries, expectations about economies across countries may be somewhat similar.Following this line of argument, we may conclude that the five Asian stock marketsmay be responding to some of the same expectations.

(b) Temporal causality and vector error-correction model (VECM)

The results of the Johansen–Juselius procedure suggest that except for the USmodel in the pre-liberalization period, the Granger-causality tests must beconducted based on the VECM. Since each variable has a unit root but nocointegration vector is found in the pre-liberalization US model, the standardVAR model in first-difference is employed in the analyses that follow.

(i) US model

Panel A of Table 3 reports the results of the Granger-causality test for thepre-liberalization period. None of the short-run causality channels appeared inthe ∆US, ∆SK and ∆TW equations, suggesting that the US, Taiwan and Koreaare exogenous to the system in this period. Apart from the US thatGranger-causes Malaysia and Thailand stock markets, the Malaysian market alsosignificantly influences the Thai market at the 5 per cent level. The activeshort-run causality channels in these two markets indicate their degree of endo-geneity in the system, and suggest that not only their own past prices but pastprices in foreign markets are also important in gauging the future path of theirstock prices.

In the post-liberalization era (Panel B), the results show that only the US andTaiwan remained statistically exogenous. Neither the error-correction term(ECT) nor the short-term channels of the Granger-causality test of this countryis temporally active. This indicates that price movements in the US market isindependent of the Asian markets and is consistent with the fact that the USstock exchange is the largest in size and the most efficient among the fiveexchanges. The US market showed its significant influences on the Thai market.


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Notice that ECTs for Korea and Thailand are statistically significant, suggestingthat these two markets shared the brunt of the short-run adjustments to long-runequilibrium in the post-liberalization era. Although the ECT is insignificant inthe ∆KL equation, the market is influenced by the short-run causal channelsfrom Taiwan and Thailand. In the post-crisis period (Panel C), we found that allof the short-run channels are inactive except for one (the causality running fromThailand to Korea). The ECTs for South Korea and Malaysia are statistically

Table 3 Temporal causality result based on VECM

A: Pre-liberalization

∆US ∆SK ∆TW ∆TH ∆KL

Dep. variables F-value

∆US – 0.94 0.71 0.34 0.56∆SK 0.50 – 0.43 0.09 0.24∆TW 0.11 0.19 – 0.13 0.43∆TH 0.00a 0.37 0.90 – 0.02b

∆KL 0.00a 0.29 0.99 0.15 –

B: Post-liberalization

∆US ∆SK ∆TW ∆TH ∆KL ECT

Dep. variables F-value t (χ2)-value

∆US – –1.40 0.50 –1.76 –0.22 0.09∆SK –0.05 – 0.61 –0.25 0.39 –2.21b

∆TW –0.34 1.23 – 0.70 –0.16 –3.92∆TH 2.37a 0.84 2.66a – –0.98 2.61b

∆KL 1.88 –1.23 1.96b 2.71a – 0.62

C: Post-crisis

∆US ∆SK ∆TW ∆TH ∆KL ECT


∆US – 0.27 3.80 0.69 0.05 0.38∆SK 0.00 – 2.54 5.07b 0.11 2.51b

∆TW 0.05 2.23 – 0.13 0.36 0.62∆TH 0.05 0.95 0.85 – 0.23 –0.63∆KL 1.80 0.40 0.54 0.30 – –4.23a

Note: All variables are in first differences (denoted by ∆). VECM was estimated including an optimallydetermined criteria (Akaike’s FPE). US is United States, KL is Malaysia, TH is Thailand, SK is SouthKorea and TW is Taiwan.a and b indicate significance at the 1 per cent and 5 per cent level, respectively.


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significant, implying that these two markets shared the burden of the short-runadjustment in the post-crisis era. The exogeneity of the US market in thepost-crash period may reflect the fact that the four Asian countries did not playan important role in spreading the crisis to the US.

(ii) Japan model

Results in Table 4 reveal the endogeneity of all five markets in the system for bothperiods of pre-liberalization (Panel A) and post-liberalization (Panel B). In allcases, either the ECT or at least a short-run causality channel is statisticallysignificant at conventional significant levels. In the pre-liberalization period, thecausality running from Malaysia to Thailand, as detected in the US model, ispreserved in this model. Japan, even though the most dominant market in thesystem, only shows its significant short-run influence on one of the markets – theKorean market. The ECTs are, however, all statistically significant for all exceptTaiwan, implying that the Japanese, Korean, Thai and Malaysian markets sharethe burden of short-run adjustment to long-run equilibrium.

Results for the post-liberalization period as depicted in Panel B may besummarized as follows. First, inspection of the individual ECT term reveals thatJapan, Korea and Taiwan bear the short-run adjustments while Malaysia andThailand appear to be no longer important in the system. Second, the short-runchannel of causality from Japan to Korea is no longer active in the system. Theshort-run channel of causality run from Taiwan to Thailand and Malaysia areactive. The causal relationships in the post-crisis period are given in Panel C forthe Japanese model. The results reveal that the only short-run causal channel isactive between Japan and Taiwan. Note that for Japan and Malaysia, the ECTterm is significant at the 5 per cent significance level. Hence, an importantconclusion that can be drawn for the post-crisis period is that these Asian marketsspread the crisis to the Japanese equity market.

(c) Dynamic analysis

We placed the US ( Japan) process at the top of the VAR system and ordered theremaining price series according to the opening and closing of each national stockprice. That is, we form a VAR by having the developed market first and theemerging markets are ordered as follows: SK, TW, KL and TH. This ordering isalso consistent with that suggested in Doan (1995) where the ordering is deter-mined based on the semi-structural interpretation of the model: if movement in Aprecedes movement in B within a single period, A precedes B in the ordering (seealso Cha and Oh 2000). A 24-week horizon is employed in the analysis to allow forthe dynamic adjustments in the system to work out.19


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(i) US model

The results for the pre-liberalization period show that over 89 per cent of its ownvariances are explained by its own innovations for the US (98 per cent), Taiwan(94 per cent) and Korea (89 per cent). The results from variance decompositionshow weak causality patterns and support the conclusion drawn from theGranger-causality tests (see Table 5). Both Korea and Taiwan are not responsive

Table 4 Temporal causality result based on VECM

A: Pre-liberalization

∆JP ∆SK ∆TW ∆TH ∆KL ECT


∆JP – –1.06 0.78 0.09 –0.81 –2.68a

∆SK –3.04a – –0.28 0.45 –0.46 5.57a

∆TW –0.79 0.55 – 2.11b 0.39 1.79∆TH 0.35 –0.05 –0.69 – –2.48b 3.98a

∆KL –0.22 0.34 –0.38 0.82 – 2.31b

B: Post liberalization



∆JP – 0.77 –0.57 –0.11 –0.82 –2.20b

∆SK 0.13 – –0.02 –0.71 0.04 –4.62a

∆TW –0.55 1.21 – –0.46 2.23b –2.50a

∆TH 0.48 1.18 2.98a – 0.83 0.83∆KL 0.53 –1.64 1.96b 1.72 – –0.20

C: Post-crisis



∆JP – 0.06 0.99 0.02 1.73 25.18a

∆SK 0.69 – 2.72 3.67 0.19 0.02∆TW 6.26b 3.53 – 0.41 0.47 3.77∆TH 0.01 0.95 0.97 – 0.21 1.11∆KL 1.95 0.00 0.51 0.04 – 6.68b

Note: All variables are in first differences (denoted by ∆). VECM was estimated including an optimallydetermined criteria (Akaike’s FPE). US is United States, KL is Malaysia, TH is Thailand, SK is SouthKorea and TW is Taiwan.a and b indicate significance at the 1 per cent and 5 per cent level, respectively.


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to innovation in foreign shocks because of the severe restrictions on cross-countryinvesting in this sample period. The most active market is Thailand (41 per cent)and followed by Malaysia (16 per cent). Among the four Asian countries, the USstock market has its most influence on the Thai market.

The degree of endogeneity (exogeneity) in the second period, which ended in1996:52, is summarized in Table 6. The exogeneity of the US and Taiwan ispreserved in the second period. As expected from estimates of the VECM, almostall variation (87 per cent) in US prices is explained by its own innovations. Thedegree of exogeneity in Taiwan increased over the deregulation period and this

Table 5 Decomposition of variance for US model (pre-liberalization)

Percentage of innovation Due to innovation in

∆US ∆SK ∆TW ∆KL ∆TH ∆FR

A: Weeks relative variance in: ∆US1 100.00 0.00 0.00 0.00 0.00 0.004 97.66 0.54 0.50 0.44 0.85 2.338 97.60 0.56 0.54 0.44 0.86 2.40

24 97.60 0.56 0.54 0.44 0.86 2.40

B: Weeks relative variance in: ∆SK1 0.58 99.42 0.00 0.00 0.00 0.584 2.21 93.94 0.36 1.22 2.27 6.068 2.26 93.83 0.41 1.23 2.27 6.17

24 2.26 93.83 0.41 1.23 2.27 6.17

C: Weeks relative variance in: ∆TW1 1.94 0.70 97.36 0.00 0.00 2.644 4.46 2.25 88.94 2.23 2.13 11.078 4.47 2.26 88.88 2.25 2.14 11.12

24 4.47 2.26 88.88 2.25 2.14 11.12

D: Weeks relative variance in: ∆KL 1 9.64 0.25 0.05 90.06 0.00 9.944 13.56 0.30 0.17 84.50 1.47 15.508 13.56 0.31 0.19 84.46 1.47 15.53

24 13.56 0.31 0.19 84.46 1.47 15.53

E: Weeks relative variance in: ∆TH1 5.99 2.01 0.01 24.61 67.37 32.624 11.86 2.31 0.40 26.01 59.42 40.588 11.87 2.31 0.41 25.98 59.43 40.57

24 11.87 2.31 0.41 25.98 59.43 40.57

Note: Ordering: US SK TW KL TH. Figure in first column refers to horizons. US denotes UnitedStates, JP denotes Japan, SK denotes South Korea, TW denotes Taiwan, KL denotes Malaysia andTH denotes Thailand. The last column (FR) provides the percentage of forecast error variances of eachcountry explained by the foreign countries.

in horizon


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result is partly due to the restrictive nature of the equity market. Besides Thailandand Malaysia, Korea is also found to be endogenous. Korea seems to be the mostinteractive market, with about 51 per cent of the market variance being explainedby innovation in other markets.

(ii) Japan model

Table 7 shows the results of the analysis for the Japanese model in the first period.All markets were found to be endogenous and Thailand and Taiwan seem to bethe most endogenous in the system. About 62 per cent of the variance of theThailand and Taiwanese markets is explained by innovations in other markets.

Table 6 Decomposition of variance for US model (post-liberalization)




24 87.42 10.50 0.57 0.79 0.71 12.57


24 1.46 49.45 1.26 22.84 24.99 50.55


24 6.89 0.59 90.25 1.39 0.88 9.75

D: Weeks relative variance in: ∆KL1 3.96 8.04 1.14 86.85 0.00 13.154 7.35 16.10 2.31 71.54 2.70 28.468 6.44 22.72 1.34 59.28 10.23 40.72

24 3.99 29.08 0.75 51.93 14.25 48.07


24 0.61 15.83 0.37 10.99 72.19 27.80

Note: Refer to Table 5.

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Japan is the most exogenous among the five Asian countries with about 91 percent of forecast variance explained by its own shocks. The Japanese stock markethas the most influence on the Malaysian stock market. The results of the VDCanalysis seem to indicate that the Asian markets are closely related since morethan 22 per cent of the variance of most of the Asian markets are explained bytheir regional markets. Overall, these findings are consistent with the resultsobtained from the VECM.

The results for the post-liberalization period are displayed in Table 8. Noticethat the importance of innovations of foreign countries in explaining the variance

Table 7 Decomposition of variance for JP model (pre-liberalization)


∆JP ∆SK ∆TW ∆KL ∆TH ∆FR

A: Weeks relative variance in: ∆JP1 100.00 0.00 0.00 0.00 0.00 0.004 92.67 0.24 1.13 4.03 1.92 7.338 91.71 0.24 1.24 4.46 2.35 8.29

24 90.73 0.25 1.35 4.99 2.68 9.27


24 0.48 77.41 8.09 0.19 13.83 22.59


24 2.28 31.67 37.32 26.96 1.77 63.68


24 15.61 0.93 11.02 63.66 8.77 36.34


24 0.42 4.90 9.00 48.04 37.63 62.37

Note: Ordering JP, SK, TW, KL and TH. Figure in first column refers to horizons (number of weeks).US denotes United States, JP denotes Japan, SK denotes South Korea, TW denotes Taiwan, KLdenotes Malaysia and TH denotes Thailand. The last column (FR) provides the percentage of forecasterror variances of each country explained by the foreign countries.

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of one market has decreased significantly. The reduction is 48 per cent for Taiwan,8 per cent for Malaysia, 16 per cent for Korea and 35 per cent for Thailand. Thissuggests that these countries responded passively in the post-liberalization periodwhen the US impact on the region is isolated. The relatively weaker causallinkages among the regional markets over the post-liberalization period suggestthe declining dominance of Japan in the region. This is not surprising as theJapanese market tumbled during this period and exhibited negative returns,reflecting the decade-long economic stagnation. It is also worth noting that theimportance of Korea in the Malaysian and Thai stock markets. Thailand andMalaysia emerged as the most interactive markets in the region with 27 per centof the forecast error being explained by foreign innovations.

Table 8 Decomposition of variance for JP model (post-liberalization)




24 86.46 9.89 0.21 1.08 2.36 13.53


24 1.65 92.60 2.45 1.59 1.69 7.37


24 8.70 4.99 84.03 1.79 0.48 15.97


24 0.63 17.54 4.43 72.09 5.31 27.91


24 3.58 15.21 1.28 7.06 72.87 27.13


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(d) The post-crisis era

Table 9 presents the forecast error variance decompositions in the post-crisisperiod for the US model. The results show that (i) South Korea is the mostimportant in the post-crisis era in predicting VDCs in Malaysia, Thailand andTaiwan, but not in the US; (ii) the US is more important in predicting the VDCsfor all the Asian countries, except for Thailand; (iii) Malaysia emerged as the mostactive market in this period and adjustment to foreign shocks are fairly rapid; (iv)the degree of exogeneity in all markets has decreased in the post-crash period,implying that no country is exogenous to the financial crisis.

Results in Table 10 indicate that South Korea is far more important than

Table 9 Decomposition of variance

A: Post-crisis (US model)




24 87.20 4.56 5.96 1.05 1.23 12.81


24 10.10 75.01 3.10 8.89 2.90 24.99


24 8.78 9.77 79.90 1.42 0.13 20.10


24 14.88 62.89 5.93 9.92 6.38 90.08


24 5.84 33.60 2.87 0.10 57.59 42.41


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Japan in explaining the movements of the Asian markets. Taiwan emerged asthe most important in predicting the VDCs in Japan. The table shows thatMalaysia is the most active market and Korea is the least active market in thepost-crisis era when the impact of the US is isolated. Importantly, thecrisis-affected countries, namely Malaysia and Thailand, are found to beincreasingly interrelated with South Korea. South Korea has lifted most restric-tions to foreign direct investment and foreign ownership since the financialcrisis. The degree of exogeneity in all markets except South Korea has decreasedin the post-crisis period. Since fluctuations in the Asian markets are explained by

Table 10 Decomposition of variance

B: Post-crisis ( Japan model)




24 58.81 7.14 25.78 0.46 7.80 41.19


24 0.22 92.63 1.55 3.52 2.08 7.37


24 16.89 25.26 55.14 2.67 0.04 44.86


24 0.60 80.86 3.28 4.95 10.30 95.05


24 0.43 42.13 1.40 0.03 56.02 43.98


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their regional markets, this is consistent with the contagion hypothesis (Masihand Masih 1999).

To investigate the dynamic impact of foreign shocks on the other countries’prices, impulse response analyses were conducted. As most of the simulatedresponses tended to indicate their full trajectory in short order, the impulseresponses were simulated for the next 25 periods (25 weeks). In addition, becausethese results can be sensitive to the order of orthogonalization, we examined thedecomposition ordering according to the opening time of these markets. The IRFsof the Korean and Taiwanese markets are plotted in Figures 2 to 5. It appears thatshocks to any market in the system lead to immediate but short-lived fluctuationduring the first period, quickly fading after 7 to 9 weeks (Figures 2 and 4).However, the Korean and Taiwanese markets do not share this transitory naturein responses over the post-liberalization periods. Shocks to any of the markets inthe system lead to an initial hump-shape and last for a long time (Figures 3 and 5).The responses are initially volatile, but stabilize quickly and persist to last well after24 weeks of the post-shock horizon.

Figure 3 reveals the responses of the Korean market to shocks in any of theother markets in the system in the post-liberalization period. Interestingly, a

Figure 2 Impulse responses of Korea market from a one-standard-deviation shock to US, Taiwan, Malaysia and Thailand: pre-liberalization


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one-standard-deviation shock in the US and Malaysia induces a contempor-aneous and persistent negative effect in the Korean market of –0.0012 units and –0.004 units respectively. On the other hand, a one-standard-deviation shock inTaiwan and Thailand induces a contemporaneous and persistent positive effect inthe Korean market of 0.004 units.

5 . CONCLUSIONS AND POLICY IMPLICATIONS

We investigated the linkages among the national stock markets and among thenational stock prices of the four Asian economies with the US and Japan. Themethodology employed utilizes the unit root test and the Johansen–Juseliuscointegration test. This was followed by the VECM, variance decomposition andimpulse response analysis in order to capture the dynamics both within and out ofthe sample period.

Comparing the results of this study with other similar studies on stock markets,several conclusions can be reached. First, the lack of cointegrating relationshipsamong stock indices as reported in Cheung and Mak (1992) and Cheung and Lee(1993) may be due to the fact that the data employed in the analysis were mostly

Figure 3 Impulse responses of Korea market from a one-standard-deviation shock to the US, Taiwan, Malaysia and Thailand: post-liberalization


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from the pre-liberalization era. However, the results reported by Chung and Liu(1994), Masih and Masih (1999) and Chowdhury (1994) among others, using amore recent sample period are comparable with the results obtained over thepost-liberalization period. Specifically, the four Asian stock markets are integratedwith the major markets in the post-deregulated period. Second, most of the earlierstudies have shown the dominance of the US in the actively traded internationalmarkets. The results of variance decomposition analysis indicate that themovement of the US stocks account for a sizeable portion of the forecast-errorvariance in the Asian stock markets. In addition, our results based on thesub-sample analysis suggest that Japan has not overtaken the US in dominatingthe Asian equity markets. Finally, the finding that the Asian regional markets areclosely linked is consistent with the results reported recently by Roca et al. (1998),Masih and Masih (1999), Habibullah et al. (2000) and Cha and Oh (2000). Thisfinding is also consistent with the currency crisis and stock market turmoil in theregion.

The importance of the Japanese market in the Asian region can be traced backto the late 1980s. Being the largest market in Asia and the second largest worldeconomy, Japan’s price movements have an important impact on the smallermarkets in the region. The findings suggest that as one moves to the present the

Figure 4 Impulse responses of Taiwan market from a one-standard-deviation shock to the US, Korea, Thailand and Malaysia: pre-liberalization


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Asian markets are becoming less integrated with Japan. This evidence is notsurprising since Japan has had a recession for a large part of the 1990s. On theother hand, the US continues to dominate Japan in the Asian equity market. Thisresult confirms the findings mentioned in the introduction: the US influences allthe other markets while the other markets have little, if any, influence on the USmarket. Asian markets are no exception. Masih and Masih (1999) argued that theprice leader of the US market may be attributed to two factors: (i) the US market,with its dominance in the global market, is also the most influential producer ofinformation; and (ii) international investors often overreact to news from the USmarket and place less weight on information from other markets. Hence, innova-tions in the US market could be used as an indicator to predict the performanceof emerging Asian stock markets.

Financial reforms affect co-movements of national equity prices in the Asianregion. The Asian markets are fully integrated with the international financialmarkets in recent years. Thus, the benefit from international diversificationborders may not be as high as in the pre-liberalization period given the stronglinkages in the Asian markets in recent years. The evidence of cointegration

Figure 5 Impulse responses of Taiwan market from a one-standard-deviation shock to the US, Korea, Malaysia and Thailand markets: post-liberalization


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implies that there is a common force such as arbitrage activity, which brings thestock markets together in the long run. However, as pointed out by several authors,cointegration among markets does not rule out the possibility of arbitrage profitthrough diversification across these countries in the short-run terms, which maylast for quite a while.

The fact that Taiwan and Korea are relatively closed with tight restrictions oncross-country investing in the 1980s explains why these two markets were able toinsulate their stock markets from foreign shocks, including those from the US. Theimpulse response analysis shows that Korea and Taiwan are relatively responsiveto foreign innovation over the post-liberalization period as most of the barriers tocapital movements have been phased out. In South Korea, for example, mostrestrictions on foreign direct investment (FDI) and foreign ownership have beenlifted following the financial crisis. Innovations from other markets are instan-taneously transmitted and last for long periods (over 24 weeks). It appears thatassets in Asia are priced according to international factors as one moves to thepresent. This is consistent with the views that domestic investors are becomingmore aware of the economic interdependencies of international markets in recentyears by reacting to the developments in foreign markets.

Universiti Putra, Malaysia

ACKNOWLEDGEMENTS

The authors are grateful to the two anonymous referees, the editor of this journaland Abul M. M. Masih for their suggestions and insightful comments that helpedto improve this paper. The first author appreciates research support from thegovernment of Malaysia (IRPA). Any errors that remain in this paper are solelythe responsibility of the authors.

NOTES

1 Masih and Masih (1997a, 1997b, 1999), Kohers and Kohers (1995), Chowdhury(1994), Cheung and Lee (1993), Taylor and Tonks (1989), and Eun and Shim (1989),among others, have analysed the relationship among national stock markets.

2 See, for example, Eun and Shim (1989), Chung and Liu (1994), Masih and Masih(1997b) and Cha and Oh (2000).

3 The benefit of diversifying into emerging markets is documented in Cheung and Mak(1992), Hung and Cheung (1995) and DeFusco et al. (1996).

4 Following Ahmed et al. (1999), we differentiate these markets according to theirmaturity. Japan (and the US) is considered as a developed or established market, whileSouth Korea, Malaysia, Taiwan and Thailand will be considered as emerging markets.According to the International Financial Corporation (1993) the term ‘emergingmarket’ refers to any market belonging to low- and middle-income LDCs, with theimplication that all have potential for development.

5 The common success as well as the common crisis experienced by these economies hasled many analysts to believe that the economic development patterns of the economies


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in the region were modelled after one another: Japan started growing rapidly in the1950s. The NIEs (Korea, Taiwan, Hong Kong and Singapore) followed the path in the1980s; the ASEAN countries (Malaysia, Thailand and Indonesia) appear to follow thispattern in the 1990s.

6 For details of the liberalization programmes in the Asian emerging markets, see Roc(1995) and Stanley (1995). The South Korea Stock Exchange was opened to foreigninvestors in 1992. The Taipei Stock Exchange was opened to institutional investors in1992 and currently there is no control over portfolio investments except for foreignindividual investors and companies.

7 For more details of the salient economic statistics of the Pacific Rim stock markets, seealso Ahmed et al. (1999).

8 In 1995 the ratio of saving to GDP in these economies was at least 35 per cent.9 This surge of capital inflows is due primarily to low interest rates in Japan and Europe that

led to a decline in attractive investment opportunities in relation to available domesticsavings. Domestic investors in Japan and Europe started to seek investment opportunitiesabroad. Unlike the other developing countries, Malaysia, Korea, Taiwan and Thailandhave capital inflows in the form of private FDI rather than bonds and official lending.

10 In Malaysia and Thailand, the stock market indices of the property sector tripled in theearly 1990s.

11 Thailand, Korea, Indonesia, Malaysia, Japan and the Philippines all suffered thesevere collapse of their currencies and stock markets. Other countries (China,Taiwan, Hong Kong and Singapore) have so far suffered only the indirect conse-quence of the crisis.

12 There is a considerable disparity in the size of the economy, degree of development,rates of growth and the structural changes that are taking place in these financialmarkets. The analysis in this study did not take into account this difference. As pointedout by Koch and Koch (1991), failure to take into account the size of these markets maybias the results. The implication of ignoring the size must be considered while inter-preting the results. We thank an anonymous referee for pointing this out.

13 Assets managers in the US, the world’s largest investor, will be more interested in USdollar-denominated stock prices. However, the empirical results obtained by Hamoriand Imamura (2000) showed that the causal relationship is unaffected in local currencyand in US dollars.

14 These are available upon request from the first author.15 The Johansen iterative tests were conducted by setting the initial sample period that

ended in 1990 and then successively adding the two periods till the end of the sampleperiod (1997:02). Based on the λmax test, most of the breaks occurred in the 1992–93period for both of the models. There is a strong indication that the long-run relation-ship is unstable over time.

16 Preliminary analysis using data from 1992:01 to 1999:50 yielded unsatisfactoryresults in terms of the standard diagnostic tests (normality, RESET and ARCHeffect). More important, the statistical results obtained from this model are inconsis-tent with the conventional wisdom. For instance, we found absence of the cointegra-tion relationship between the Asian and the established markets. The Grangercausality tests indicate the causal runs from some of the smaller markets to theestablished markets. For these reasons we have reported the results for the period1997:01 to 1999:52 instead.

17 Cheung and Lai (1993) raised the issue of small sample bias in the Johansen tests. In thisstudy, we examined both tests using small-sample correction as suggested by Reimers (1992)but this does not alter our conclusion regarding the number of cointegration vectors.

18 In general, the more cointegrating vectors there are in the system, the more stable the


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system and the more constrained the long-run relationship among the variables (Leeand Jeon 1995).

19 We also employed the generalized VDCs and IRF but the results are different fromthose of the orthogonalized model. For instance, both Thailand and Taiwan (andperhaps Malaysia) appear to be exogenous to the system in both sample periods. Basedon these findings, we only report the results of the orthogonalized model. We alsolooked at the VDCs by placing the established market at the bottom of the VAR systembut the results were found to be quite similar to those reported here.

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Documents

DYNAMIC LINKAGES OF ASIAN STOCK MARKETS