The impact of globalization on companies
during the starting period of crises
Are stock returns of companies from open economies more affected by a crisis
than stock returns of companies from closed economies?
Poppema, M.L - Studentnummer: 2405563
Master Thesis 2013-2014 - Rijksuniversiteit Groningen - Faculteit Economie en Bedrijfskunde
A B S T R A C T
Using a sample of 1267 companies from ten open economies and ten closed economies, we test to what extent globalization has an effect on the stock returns during the starting period of a crisis. Using a combination of existing literature and statistical testing, we analyze eight crises between 1994 and 2008. We find that companies from open economies are more negatively affected by a crisis than companies from closed economies when the crisis initially started in an open economy. We also find contagion effects during crises when a crisis starts in an open economy.
JEL Classification: F02, F3, F31, F4, F60, F65, G1, G01
Keywords: Globalization, Crisis, Contagion, Stock market, Economic integration, Financial crisis, Banking crisis, Currency crisis, Open economies, Closed economies
Words1: 10.585
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I. Introduction
Globalization and integration in the world market has increased radically over the last decades (Brewer, Chase-Dunn and Kawano, 2000). Product and capital markets are more integrated, new markets are rising and globalization is an important issue for companies worldwide (Moeller and Schlingemann, 2005). However there are also negative effects of globalization. One of the negative effects are the consequences that countries which have been highly integrated into the global economy will be more affected by a crisis than countries which have not (Bakri and Zulkefly, 2014; Basco, 2014; Joyce and Nabar, 2009; Lawrence, 2009; Rousseau and Wachtel, 2011)
The most recent financial crisis (2007-2009), also known as the Global Financial Crisis, has been a problem to many countries of the world. This crisis is considered by many economists as the worst financial crisis since the Great Depression of the 1930s (Shahrokhi, 2011). This crisis started in the United States and has heavily affected countries worldwide. This supports the view of the findings mentioned before, since the United States has a globally integrated economy (according to the rankings of The Heritage Foundation in participation with The Wallstreet Journal).
For the purpose of this paper, we examine whether the stock returns of companies from open economies are affected more during the starting period of a crisis than the stock returns of companies from closed economies. Therefore the research question is: To what extent does globalization has an effect on stock returns during the starting period of crises? In order to analyze this, we construct a dataset covering twenty countries with in total 1267 companies to measure the globalization effect during the starting period of a crisis. We use a combination of existing literature and statistical testing to find an answer on the research question. We use the Wilcoxon rank sum, Chi-squared, and the Van der Waerden test to statistically test the hypotheses, which will be defined in the next chapter.
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in the world which have a closed economy. We also find that the countries in which a crisis started and which have said to be open economies, have contagion effects to other countries. Using the Granger causality test, we find that the Global Financial Crisis, the Icelandic crisis and the crisis of 9/11 have had contagion effects to many other countries in the world.
The paper is organized as follows: In the following chapter, the definitions and explanations about the different crises tested in this paper are described. Also, the definitions about globalization are given. Thirdly, we discuss empirical literature about to what extent globalization has an effect on the impact of a crisis and the possible contagion effects of a crisis. Finally, we present the hypotheses. In the third chapter, the sample is described, which includes the used tools, techniques and methods used for statistically testing the hypotheses. The fourth chapter shows the results of the main study. The fifth chapter shows an extra test about the contagion effects of a crisis started in one country. In the sixth chapter, we discuss the findings of this paper. Finally, in the last chapter of this paper the conclusions of the study are presented.
II. Literature review
In this chapter we discuss the literature review. In the first section of this chapter we shortly define a crisis and give a description of the eight crises we test. In the next section, we discuss the definitions of globalization. Thirdly, we discuss the empirical literature which explains how globalization affects the impact of a crisis. In addition, theoretical findings about potential contagion effects are illustrated. Finally, the hypotheses are given.
A. Description of the crises
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situation with negative effects on organizations and the economy as a whole, which very often goes along with a fall in stock markets (Coombs, 2012; Mir, 2013).
In this paper we test the effects of an announcement of a crisis on the stock returns of companies from open and closed economies. We test this for a set of multiple crises. We shortly describe the eight different crises we test for in chronological order. We take into account the crises occurring since 1994, starting with the Mexican crisis, until 2008, ending with the Icelandic crisis. We chose this period because of the data availability. We could not find enough data of the stock returns of only the same companies over the period before 1994 and after 2008. We exclude the Russian crisis because DataStream does not provide data of the Russian index. We also exclude the dot.com crisis because this crisis only affected the United States.
First, we find the Mexican currency crisis. This crisis started with the devaluation of the peso in December 1994 (Gordon & Davis-Friday, 2005; Brière, Chapelle & Szafarz, 2012; Caprio, Saunders & Szafarz, 2012). This devaluation resulted from the decision of the Mexican government to allow the peso to float freely against the dollar. As a result, the peso lost more than 50 percent of its value relative to the dollar which has led to an extreme impact on the Mexican economy. One of the consequences of this crisis was that the inflation rate increased from 7 percent in 1994 to 52 percent in 1995. Also the stock market decreased with almost 50 percent (Caprio, Saunders & Szafarz, 2012).
Secondly, we test for the Asian crisis of 1997. The Asian crisis started with the collapse of the Thai baht’s peg after the Thai government was forced to float the baht on July 2, 1997 (Baig and Goldfajn, 1998). The regional markets of Asia found increasing pressure in the period after the devaluation of the bath. This pressure was reflected in the separation of the managed currencies in Indonesia and Malaysia. News of economic distress affected other countries as well and it appeared that any event happening in one country put additional pressure on the other markets in Asia (Baig and Goldfajn, 1998).
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to float, there arose fear inside and outside Brazil of a return of high levels of inflation and default on the public debt (Victor Bulmer, 1999).
Fourth, the Turkish crisis of 2001. In December 1999 the Turkish government launched an exchange rate stabilization program in order to bring inflation down. This program ran into difficulties starting in the last quarter of 2000. Consequently, it became apparent that the program was not sustainable and faced too harsh problems with their currency until the crisis really started in February 2001 (Akyüz, 2003; Ari, 2012). As a result, interest rates rose sharply and employment and economic activity became depressed (Akyüz, 2003).
The fifth crisis, also started in 2001, is the terror attack on the World Trade Center in the United States at 9/11. This attack caused large disturbances to the economy of the United States as well as the financial system. The stock markets of the United States were even closed for four days. Indexes worldwide, such as the FTSE 100 in London and the DAX in Frankfurt lost more than 6 and 8.5 percent respectively (Pat Obi, 2007).
The sixth crisis is the Argentina crisis of 2001. Before the crisis really started, Argentina was already in deep recession since 1998. In the second half of 2001 it already became apparent that Argentina could face an enormous disaster in the near future. The governments' financial position got worse due to the decrease in tax revenues. By the end of 2001 the government of Argentina froze deposits in bank accounts in order to prevent the loss of capital, but precisely this has led to the collapse of the payment system (Leavell, Maniam and Patel, *2004).
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At last, we test for the Icelandic crisis of 2008. Iceland suffered a large breakdown when their three largest banks collapsed and became nationalized. Their Prime Minister, Geir Haarde, stated in the beginning of October: ‘There is a very real danger, fellow citizens, that the Icelandic economy, in the worst case, could be sucked with the banks into the whirlpool and the result could be national bankruptcy.’ (Prime Minister’s Office, 2008). Iceland started to become uncertain about future prospects of the country and as a result, hundreds of firms declared bankruptcy (Ásgeirsdóttir, Corman, Noonan, Ólafsdóttir and Reichman, 2014).
B. The definition of globalization, open economies and closed economies
Globalization is according to Velasquez (2011), defined as: 'the way nations are becoming more connected so that goods, services, capital, knowledge, and cultural artifacts move across national borders at an increasing rate.' Bhagwati (2013) describes globalization as the integration of a national economy into the world economy. Additionally, Prempeh (2013) describes globalization as the development of an increasingly integrated global economy, specifically defined by free trade, free capital flows and cheaper labor markets. Finally, Bakri and Zulkefly (2014), find that as free trade in a country increases, as a percentage of GDP, economic openness is increased. We define globalization as the integration of national economies into the world economy, so that goods, services, capital, knowledge, culture, and labor move across national borders at an increasing rate.
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rights and freedom from corruption. They have grouped the numerical results into five subgroups: open economies, mostly open economies, moderately open economies, mostly closed economies and repressed economies.
C. Existing literature about the effects of globalization on companies in relation to crises
In the above, we described the phenomenon of crises and the definition of globalization. In this part of the chapter we discuss the existing literature about the relation between the effects of globalization and its impact on companies during a crisis. Furthermore, we discuss the closely related subject of possible contagion effects during crises.
According to Fakuda (2014), when a country opens their borders to facilitate exports and imports and it allows capital to flow freely, it is more likely to bring benefits to financial development, as it can strain competition in financial markets. Huang (2006) and Law (2008) also contribute to the positive globalization effects. One of these positive effects is economic growth, due to integration within the world economy.
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and Nabar (2009), contribute to the statement that openness of economies in countries results in negative consequences. We conclude that more financially developed and integrated countries have a greater possibility of having economic difficulties due to a crisis than less developed and globally integrated countries. At last, according to Keane (2012), it was initially not expected that the financial crisis of 2007 would have impacted the low-income countries (African and Asian), due to limited connections with the developed countries. This supports the view that more closed economies, which have limited connections with the developed countries, are less affected in the event of a crisis.
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D. Hypotheses
Based on the above, the following hypotheses are derived:
H0 The effect of an announcement of a crisis on stock returns is the same for companies from open economies and for companies from closed economies.
H1 The effect of an announcement of a crisis on stock returns is larger for companies from open economies than the effect of an announcement of a crisis on stock returns for companies from closed economies.
We test these hypotheses by measuring the adjusted returns from a company calculated during the period surrounding the announcement day, which we refer to as the starting period of a crisis.
III. Data and Methodology
In this chapter we provide the sample design of the study and the methodology used for testing the hypotheses.
A. Sample design
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In this study the difference between the estimation period with normal returns and the period surrounding the announcement day is tested. The countries with an open economy, used in this survey, are the most open economies of the world whereof data was available. On the contrary, the countries with a closed economy, used in this survey, are the most closed economies of the world, whereof data was available.
In table I Observations we present a summary of the dataset used for this research. The third column gives the distinction between open (O) and closed (C) economies. From this table we can observe that we use a total of 702 companies within ten countries with open economies, and 565 companies within ten countries with closed economies. We also use datasets of Argentina, Mexico and Iceland because we test for the Argentina crisis of 2001 (closed economy), the Mexican crisis of 1994 (closed economy) and the Icelandic crisis of 2008 (open economy).
Table I Observations
The table presents the number of observations and the number of trading days for the full sample and for the different countries. The data sets are composed of the indices of every country2.
2 Of which you can find the complete list of countries and companies in Appendix A.
Dataset Country O/C Nr. of companies
Nr. of observations
Range
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In table II Crises we present a list of crises we test in this paper. These crises are presented in chronological order. Also, we provide the country in which the crisis started. For most of the crises it is clear in which country the crisis initially started. For example, the Mexican crisis of 1994 obviously started in Mexico. This does not apply for the Asian crisis, 9/11 terror attack and the Global Financial Crisis. For the Asian crisis, some academia finds Thailand as the initial country where this crisis started. Unfortunately, there is not enough data to find of the stock market of Thailand. However, Huyghebaert and Wang (2010) find that Hong Kong and the Singaporean stock markets play the most important role in spreading the crisis in East Asia and the rest of the world. Additional, Masih & Masih (1999) and Dekker, Sen & Young (2001) find that Hong Kong has the strongest influence on the other stock markets in Asia, even on the more isolated markets (Dekker, Sen & Young, 2001). We therefore take the stock market of Hong Kong as the country out of which the crisis has spread itself and therefore to test how other countries have responded to the Asian crisis. Secondly, the 9/11 crisis and the Global Financial Crisis started in the United States according to Pat Obi (2007), Achayra et al (2009) and Shahrokhi (2011).
Table II Crises
The table presents the different crises we test in this survey. Also the origin crisis country, pre-crisis period and crisis period are displayed. At the end of the table the literature and breakpoint test to determine the crisis periods are shown.
Year Crisis Origin country Pre-crisis period Crisis period tested*
1994 Mexican crisis Mexico July 18, 1994 to December 19, 1994 December 20, 1994 to January 31, 1995 1997 Asian crisis Hong Kong February 12, 1997 to July 1, 1997 July 2, 1997 to July 22, 1997
1999 Brazilian crisis Brazil August 26, 1998 to January 11, 1999 January 13, 1999 to January 15, 1999 2001 Turkish crisis Turkey September 14, 2000 to February 15, 2001 February 16, 2001 to February 28, 2001 2001 9/11 United States April 24, 2001 to September 10, 2001 September 11, 2001 to September 21, 2001 2001 Argentina crisis Argentina May 14, 2001 to September 27, 2001** September 28, 2001 to October 30, 2001 2007 Global Fin. crisis United States March 3, 2007 to July 19 2007 July 20, 2007 to August 28, 2007 2008 Icelandic crisis Iceland May 9, 2008 to September 24, 2008 September 25, 2008 to October 31, 2008
* Mexican crisis: Brière, Chapelle and Szafarz (2012); Caprio, Saunders and Wilson (2000); Gordon and Davis-Friday (2005) Asian crisis: Huyghebeart and Wang (2010); and Brière, Chapelle and Szafarz (2012) Brazilian crisis: Dungey, Fry, González-Hermosillo and Martin (2006); Brière, Chapelle and Szafarz (2012) Turkish crisis: Akyüz (2003); Ari (2012) 9/11 crisis: Brière, Chapelle and Szafarz (2012) Argentina crisis: Brière, Chapelle and Szafarz (2012) Global fin. crisis: Breakpoint test of Bai-Perron (1998) Icelandic crisis: Breakpoint test of Bai-Perron (1998) ** Left out the 9/11 crisis period
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to take care of the overlay of some crisis periods. The crisis periods used, are determined in a similar approach as was used by earlier research3. These findings in previous studies show the start date (announcement date) of the crisis. Besides, we take as the crisis period, the period in which the stock returns are unstable and decreasing until the stock returns became stable again. Although academia agree on the start of the Mexican crisis, Asian crisis, Brazilian crisis, Turkish crisis, 9/11 crisis and the Argentina crisis, this is not the case for the Global Financial Crisis and the Icelandic crisis. Therefore we use the breakpoint test of Bai-Perron (1998)4 for the Global Financial Crisis (2007) and the Icelandic crisis (2008). With this test of Bai-Perron (1998), we can estimate the ‘breakpoint’. Meaning, that at this point the stock returns of the companies show a simultaneous and sudden break.
B. Methodology
The stock returns surrounding the announcement day of the crisis are collected. The average returns of the pre-crisis and crisis period are calculated, of which we can calculate the adjusted returns (abnormal, crisis period returns minus normal, pre-crisis returns).
As mentioned before, we test for the breakpoint in stock returns to define the crisis periods of the Global Financial Crisis and the Icelandic crisis. We use the Breakpoint test of Bai-Perron (1998), using a linear regression model and following Andrews (1993), the test is defined as:
) (1) where the sup Ft (k; q) is a sup F-type test of the null hypothesis of no structural break versus the alternative of a fixed number of breaks k. Andwhere ) minimizes the global sum of squared residuals under the specified trimming, which is equivalent to maximizing the F-test assuming spherical errors.’ (Bai and Perron, 2003).
The Jarque-Bera test is used for normality. This test is performed since financial data is usually non-normal and in case of non-normal data we have to compare medians instead of means. The Jarque-Bera test is a goodness-of-fit test, which tests whether the sample data has a skewness and kurtosis matching normal distribution.
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Akyüz (2003); Ari (2012); Briére, Chapelle and Szafarz (2012); Caprio, Saunders and Wilson (2000); Dungey, Fry, González-Hermosilo and Martin (2006); Gordon and Davis-Friday (2005); Huyghebeart and Wang (2010)
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The test is defined as:
JB = (2) where n is the number of observations, S is the sample skewness, and K is the sample kurtosis. For the explanation of the outcomes we used an alpha of 5%. Since financial data is mostly non-normal, medians should be compared instead of means. When eventually the data is actually non-normal according to the chi-squared distribution, the data should be tested using a ‘Wilcoxon Rank Sum Test’.
As a reminder, in chapter II Literature review, we test our data for the following hypotheses: H0 The effect of an announcement of a crisis on stock returns is the same for companies
from open economies and for companies from closed economies.
H1 The effect of an announcement of a crisis on stock returns is larger for companies from open economies than the effect of an announcement of a crisis on stock returns for companies from closed economies.
In a similar approach as was used in Wang (2014), we test these hypotheses by the rank-based non-parametric Wilcoxon Rank Sum test. We also perform the following rank-rank-based non-parametric tests: Chi-squared median test and Van der Waerden test.
We first explain the Wilcoxon Rank Sum test. The Wilcoxon Rank Sum test tests whether the location of a 'closed poplulation is at the same location as the 'open economy'-population. To test this, the mean of the ranks and standard deviation of the sample has to be calculated as follows:
E(T) = (3)
σ(T) =
(4) where n is the number of observations, and T is the rank sum of the sample. In order to obtain the test statistic, the following equation is used:
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From here the p-value gives the solution to the hypotheses. We again use an alpha of 5%. Furthermore, this test is tested one-sided.
Also, the Chi-squared (X2) test is used. This test is used to test the comparison of the number of observations above and below the overall median in each subgroup. This test is sometimes referred to as the median test. We here test whether the value of the median is associated with the type of economy. The value of the test-statistic is:
= (6)
where Oi is the observed value, Ei is the expected value and n is the number of classes. The degree of freedom (df) is in this case 1, because it is calculated as the number of classes minus one. In this study we use two classes, namely companies from open economies and companies from closed economies. The value contributed to this degree of freedom is 3.481 with a probability of 5%5. The null hypothesis is rejected when the observed X2-value exceeds the X2-value of the table.
The third test used is the van der Waerden test. This is also a statistical test that assumes that population distribution functions are equal. It converts the ranks from a standard Kruskal-Wallis test to quintiles of the standard normal distribution. These quintiles are called normal scores. The test can be defined as whether one of the populations tends to have larger observations compared to the other population. The normal scores are calculated as:
(7) where N denotes the sample size for all groups, Xij represents the ith value in the jth group, R(Xij) denotes the rank of observations Xij and where ∅-1 denotes the normal quintile function. The average and variance of the normal scores for each group are computed as:
(8) (9)
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At last the test statistic:
(10) where T1 > X2α, k-1 is the critical region. Where X2α, k-1 is the α-quintile of the chi-squared distribution with k-1 degrees of freedom. The null-hypothesis is rejected if T1 lies within the critical region.
In order to establish the contagion effect, as mentioned in chapter II Literature review, we test for interdependency. In a similar approach as was used in Wang (2014), we implement the multivariate Granger causality test to decide on the stock market interdependencies. We conclude that Y is causing X, denoted by Yt →Xt, if:
– (11)
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IV. Results
In this chapter we describe the results of the explained statistical tests in the methodology part of this paper.
Primarily, we present the descriptive statistics of the sample used. In table III Descriptive statistics we present these results. In the first column we give statistics of the country in which the corresponding crisis started. In the second column we provide the results of all the companies from open economies. In the third column we provide the summary statistics of the companies from open economies to be equally weighted, so that each country is equally rated and that difference in the number of companies is solved. This is because we find, for example, 201 companies in India and 66 companies in Sri Lanka. This could have led to disturbances, which in this situation is not the case. In the fourth and fifth column the same features are explained as in the second and third column, here for the companies from closed economies. We used the adjusted returns in every column, which means that we subtracted the normal returns of the abnormal returns.
If we analyze the results from the first column, we find negative means and medians for all the countries in which the crisis initially started. The crisis of 9/11 gives the lowest value, which has a mean of -1.69% and a median of -1.64%. If we compare the second column with the third, and the fourth column with the fifth we do not find large differences in the values of the means and medians. Meaning that we do not have to equally weight each country and therefore we can conclude that we can use the complete list of companies to compare the results of open economies with closed economies. Besides, for the equally weighted columns we only use ten countries and thus ten inputs, which is a too small sample. This would have led to insignificant values of Jarque-Bera for the equally weighted columns. Thus to conclude, we use the statistics of the complete list of companies from open economies as to compare with the complete list of companies from closed economies.
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Table III
Descriptive Statistics
This table provides the descriptive statistics of the eight crises described before. It shows the statistics of the returns of the country in which the crisis started (origin), the total sample statistics of the companies out of the open and closed economies (open/closed), and the statistics of the returns equally weighted of every country with still a distinction between open and closed economies (open eq./closed eq.).
Origin Open Open eq. Closed Closed eq. 9/11 Mean -0.0169 -0.0125 -0.0158 -0.0098 -0.0089 Median -0.0164 -0.0104 -0.0171 -0.0070 -0.0063 Max. 0.0082 0.1374 -0.0083 0.0435 -0.0008 Min. -0.0576 -0.1408 -0.0255 -0.0773 -0.0318 Std. Dev. 0.0121 0.0159 0.0065 0.0130 0.0092 Skew. -0.7038 -0.0410 -0.0459 -0.9583 -1.6102 Kurt. 3.7667 20.0772 1.5347 6.0144 4.8253 JB 15.5223 8530.3990 0.8982 300.3909 5.7096 Prob. 0.0004 0.0000 0.6382 0.0000 0.0576 Obs. 145 702 10 565 10 Argentina Mean -0.0079 0.0037 0.0039 0.0029 0.0029 Median -0.0100 0.0033 0.0043 0.0017 0.0037 Max. -0.0002 0.0256 0.0072 0.0384 0.0146 Min. -0.0133 -0.0409 0.0005 -0.0308 -0.0059 Std. Dev. 0.0068 0.0058 0.0019 0.0085 0.0059 Skew. 0.5261 -0.2222 -0.2255 0.1093 0.3025 Kurt. 1.5000 8.3791 2.5824 5.4039 2.9744 JB 0.4197 852.1214 0.1574 137.1615 0.1528 Prob. 0.8107 0.0000 0.9243 0.0000 0.9264 Obs. 3 702 10 565 10 Asian Mean -0.0037 -0.0001 -0.0004 0.0018 0.0002 Median -0.0026 0.0000 -0.0003 0.0004 -0.0010 Max. 0.0129 0.0203 0.0027 0.0572 0.0079 Min. -0.0348 -0.0481 -0.0032 -0.0249 -0.0055 Std. Dev. 0.0089 0.0056 0.0022 0.0089 0.0044 Skew. -1.6710 -1.2867 0.0531 1.0370 0.5456 Kurt. 8.0117 13.5637 1.6182 6.7265 1.9863 JB 34.7737 3457.7920 0.8003 428.1917 0.9242 Prob. 0.0000 0.0000 0.6702 0.0000 0.6300 Obs. 23 702 10 565 10 Brazilian Mean -0.0091 -0.0020 -0.0062 -0.0087 -0.0073 Median -0.0153 -0.0023 -0.0050 -0.0072 -0.0096 Max. 0.0908 0.0756 0.0042 0.0900 0.0022 Min. -0.1033 -0.0524 -0.0188 -0.1034 -0.0155 Std. Dev. 0.0386 0.0122 0.0072 0.0183 0.0062 Skew. 0.1538 0.4851 -0.3393 0.1069 0.5159 Kurt. 5.4789 6.5226 2.0877 9.7781 1.8505 JB 4.4198 390.4903 0.5386 108.2628 0.9941 Prob. 0.1097 0.0000 0.7639 0.0000 0.6083 Obs. 17 702 10 565 10
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We find a p-value of 0.0000, contributing to the Jarque-Bera statistic, for all the open and closed columns of all crises. Therefore we can conclude that the data is thus non-normally distributed.
The next step for a non-normal distribution is to compare medians. We use the Wilcoxon Rank Sum test, Chi-squared test and the Van der Waerden test to check whether the medians of the companies from open economies statistically differ from the medians of the companies from closed economies.
In table IV Results we find the results of the tests. We find lower medians for the companies from open economies for the 9/11 crisis, the Asian crisis, the Global Financial Crisis and the Icelandic crisis. These four crises all started in a country with an open economy. On the contrary, we find lower medians for the companies from closed economies for the other four crises, which started in closed economies. We can thus conclude, that these results present that the medians from the open economies are lower in the case of which the crisis started in an open economy, and that the medians from closed economies are lower in the case of which the crisis started in a country with a closed economy. The second row in the table of the results, presents the values of the mean rank given to the adjusted returns. In all cases, where the median is the lowest, the mean rank is also the lowest. We test whether these results are significant with the three tests explained before.
The Wilcoxon Rank Sum test presents significant answers. We find that all statistics have a significant p-value (p < 0.05). As a result, we can conclude that in case of which a crisis started in an open economy it leads to significant results of that the sample of companies from closed economies are less negatively affected by the crisis than companies from open economies. However, when a crisis has started in a closed economy the results are vice versa.
The Chi-squared test for medians presents that the p-values are also significant (p < 0.05), except for the Asian crisis. Finally, we can conclude that the value of the median is associated with the type of economy.
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larger impacts during the crisis as compared to the other population. Meaning, that previous found results from the Wilcoxon Rank Sum test and the Chi-squared test are confirmed by the Van der Waerden test as well.
We can conclude that the medians of the companies from open economies have significantly lower values than the companies from closed economies in cases where the crisis started in an open economy. Therefore we can conclude that a country with an open economy is more negatively affected by a crisis started in an open economy than a closed economy. Note, when we used the equally weighted samples with only ten inputs for open economies and ten inputs for closed economies, it gave us insignificant answers. This is probably due to the sample size, which is very small.
Table IV Results
This table provides the results of the statistical tests which are performed in this survey. It provides the results of the Wilcoxon Rank Sum/Mann-Whitney test, the median’s Chi-square, the Kruskal-Wallis and Van der Waerden tests. The inputs of this test are the adjusted returns of 702 companies out of 10 open economies and 565 companies out of 10 closed economies. The values shown in between the brackets are the p-values.
9/11 crisis Argentina crisis Asian crisis Brazilian crisis
Open Closed Open Closed Open Closed Open Closed
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Continuing, Table IV Results
Global Fin. crisis Icelandic crisis Mexican crisis Turkish crisis
Open Closed Open Closed Open Closed Open Closed
Median -0.0040 -0.0031 -0.0086 0.0119 -0.0003 -0.0029 -0.0010 -0.0020 Mean rank 600.71 675.36 363.25 970.40 746.40 494.34 661.03 600.41 Mean score -0.1064 0.1322 -0.6877 0.8544 0.2987 -0.3711 0.0676 -0.0839 Wilcoxon/Mann-Whitney 3.6098 29.3590 12.1887 2.9313 (0.0003) (0.0000) (0.0000) (0.0034) Wilcoxon/Mann-Whitney (tie-adjusted) 3.6098 29.3590 12.1887 2.9313 (0.0003) (0.0000) (0.0000) (0.0034) Med. Chi-square 5.4873 842.1332 88.6139 5.2536 (0.0192) (0.0000) (0.0000) (0.0219) Adj. Med. Chi-square 5.2257 838.8560 87.5530 4.9977
(0.0223) (0.0000) (0.0000) (0.0254) Van der Waerden 17.9942 751.2356 141.6853 7.2484
(0.0000) (0.0000) (0.0000) (0.0071)
V. Robustness
Inspired by the empirical findings about the contagion effect, as mentioned in chapter II Literature review, we test for interdependency. As used in a similar approach by Wang (2014), we implement the multivariate Granger causality test to decide on the stock market interdependencies.
Based on the definitions of globalization, described in chapter II Literature review, we expect countries with an open economy to be more affected by the country in which the crisis started initially, especially when this origin country has also an open economy.
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returns of the United States caused movements on the stock returns for six out of the ten countries with an open economy. For the Brazilian crisis and Mexican crisis we found weak evidence of a causal relationship. However some evidence is found about a Granger cause relationship between the origin country and the other countries. The Brazilian crisis had Granger causal effects on Australia, Denmark, Japan, the Philippines, Singapore and the United Kingdom. The Mexican crisis had Granger causal effects on India, Japan, the Netherlands, Pakistan and the Philippines. These two crises did not have a clear separation of its effect on only open or closed economies. At last, we did not find significant evidence of a causality effect of the Asian crisis, Argentina crisis and Turkish crisis.
Table V Granger causality
Granger causality test results. This table presents the results on the multivariate Granger causality tests. We first run the models with 15 days as a maximum lag length and implemented a lag-length test. In this table we present the Granger causality of the origin country on the other countries. The values shown in between the brackets are the p-values.
O/C 9/11* USA Argentina** Argentina Asian** Hong Kong Brazilian** Brazil Global** USA Icelandic* Iceland Mexican*** Mexico Turkish** Turkey Australia O 2.1654 (0.0170) 0.9647 (0.3842) 1.1868 (0.3089) 4.3122 (0.0158) 7.2953 (0.0000) 2.6862 (0.0028) 1.3753 (0.2532) 0.0734 (0.9293) Brazil C 0.8530 (0.6110) 0.1241 (0.8834) 1.8918 (0.1555) NA 0.3496 (0.7057) 3.6918 (0.0000) 1.1543 (0.2138) 1.4460 (0.2398) Canada O 1.5130 (0.1272) 0.6861 (0.5056) 0.5637 (0.5707) 0.9421 (0.3930) 3.2610 (0.0418) 2.5615 (0.0043) 0.2779 (0.8412) 2.9572 (0.0560) China C 1.0707 (0.3973) 0.0191 (0.9811) 2.02746 (0.1364) 2.3706 (0.0984) 1.1320 (0.3258) 0.9472 (0.5136) 0.8876 (0.4495) 2.9713 (0.0553) Denmark O 1.8678 (0.0439) 2.9044 (0.0588) 1.9524 (0.1466) 7.5856 (0.0008) 2.8950 (0.0000) 4.5357 (0.0000) 0.3059 (0.8211) 6.0784 (0.0031) Hong Kong O 1.3731 (0.1877) 0.4823 (0.6186) NA 1.0300 (0.3605) 4.0454 (0.0000) 2.1327 (0.0180) 1.4954 (0.2188) 0.0042 (0.9958) India C 0.4974 (0.9276) 0.6097 (0.5453) 3.8378 (0.0244) 0.6547 (0.5217) 8.6955 (0.0003) 2.4134 (0.0071) 4.0558 (0.0086) 0.1830 (0.8330) Indonesia C 1.3390 (0.2057) 1.1524 (0.3195) 0.9147 (0.4036) 0.0830 (0.9204) 7.1806 (0.0011) 3.8682 (0.0000) 1.7391 (0.1621) 0.1772 (0.8378) Japan O 1.9530 (0.0336) 0.6472 (0.5254) 0.2345 (0.7914) 4.8097 (0.0100) 2.7395 (0.0000) 3.0556 (0.0000) 3.0338 (0.0316) 0.8708 (0.4214) Kenya C 1.2806 (0.2397) 1.5741 (0.2117) 0.2155 (0.8064) 0.7440 (0.4777) 2.4351 (0.0919 1.6319 (0.0881) 0.2219 (0.8811) 0.4459 (0.6414) Morocco C 0.8250 (0.6401) 0.6703 (0.5136) 0.8143 (0.4455) 0.5538 (0.5764) 1.3969 (0.2514) 1.6262 (0.0896) 0.44524 (0.7211) 0.1823 (0.8336) Netherlands O 2.9463 (0.0013) 2.7474 (0.0683) 0.6826 (0.5074) 1.6687 (0.1934) 20.452 (0.0000) 2.9520 (0.0011) 2.6778 (0.0497) 2.7399 (0.0689) Pakistan C 0.9064 (0.5556) 1.0159 (0.3653) 1.6852 (0.1900) 1.2945 (0.2783) 0.0276 (0.9727) 0.3787 (0.9774) 4.6179 (0.0042) 0.1131 (0.8932) Philippines C 1.5724 (0.1072) 3.2077 (0.0541) 0.4603 (0.6323) 3.3039 (0.0406) 2.6130 (0.0000) 4.0629 (0.0000) 3.5873 (0.0156) 0.4261 (0.6541) Singapore O 1.4702 (0.1436) 1.1878 (0.3087) 0.1451 (0.8651) 5.7852 (0.0041) 3.9504 (0.0000) 3.5682 (0.0001) 2.0866 (0.1051) 0.6117 (0.5442) Sri Lanka C 0.7013 (0.7662) 0.2791 (0.7569) 2.0347 (0.1354) 4.9348 (0.0890) 0.2748 (0.7602) 1.9972 (0.0280) 0.2092 (0.8899) 0.3984 (0.6723) Switzerland O 2.2581 (0.0126) 2.9106 (0.0585) 1.5924 (0.2079) 1.0178 (0.3649) 1.6351 (0.0000) 3.0700 (0.0008) 2.6408 (0.0521) 0.0739 (0.9288) Turkey C 1.1612 (0.3224) 2.0987 (0.1273) 1.4524 (0.2383) 2.3559 (0.0998) 5.7534 (0.0041) 2.9358 (0.0012) 0.1307 (0.9417) NA United Kingdom O 3.6059 (0.0001) 1.2694 (0.2850) 2.2592 (0.1091) 6.0162 (0.0034) 1.8988 (0.0000) 2.8931 (0.0014) 2.0778 (0.1063) 0.9483 (0.3904) United States O NA 1.6163 (0.2031) 0.6737 (0.5118) 0.7431 (0.4781) NA 2.7393 (0.0023) 1.1328 (0.3383) 1.9910 (0.1413)
22
VI. Discussion
In this part of the paper we discuss the findings derived from the performed statistical tests. We also check whether the results are in line with the empirical literature described in the second chapter Literature review.
We find that the stock returns of companies from open economies are more negatively affected during the starting period of a crisis than companies from closed economies, but only when a crisis started in an open economy. Meaning that, once a crisis begins in a country, which is said to be an open economy, other countries with an open economy are more influenced by this event then other countries in the world which have a closed economy. This is in line with previous research, indicating that economical openness to trade and finance can bring risks (Lawrence, 2009). Also, those countries with open economies are said to be more affected during any sort of foreign external shock (Bakri and Zulkefly, 2014; Basco, 2014; Rousseau and Wachtel, 2011; Joyce and Nabar, 2009; Keane, 2012).
In contrary to these findings, we find that when a crisis starts in a country with a closed economy, the companies from open economies are not affected the most by the event. We find that the companies from closed economies are the most negatively influenced in this case. We do not find evidence that this finding is due to the fact that closed economies are more interrelated with each other than with countries with open economies. Additional to this, we did not find strong evidence of contagion effects of crises starting in a closed economy.
23
Global Financial Crisis has been considered as the worst financial crisis since the Great Depression of the 1930s. He also finds that this crisis has affected many other countries around the world. In case of the Global Financial Crisis our findings are in line with previous research. We find that the United States had Granger causal effects to fourteen (out of twenty) other countries during the starting period of the Global Financial Crisis. For the Icelandic crisis, we find that there is also a contagion effect to many countries. This is in line with the findings of Brière, Chapelle and Szafarz (2012) and Calvo and Mendoza (2000), because they find that globalization is hard to separate from contagion. Meaning, that more integrated countries, such as Iceland and the United States, should face contagion effects. We also find Granger causal effects to other countries in the world after the terror attack of 9/11. This is not consistent with the findings of Cheng and Ma (2005), because they did not find any causal relation between the stock markets of the United States and other regional or worldwide stock markets. However, Cheng and Ma (2005) only tested crises which occurred before the year of 2000, meaning they did not test for the terror attack of 9/11 and the Global Financial Crisis.
VII. Conclusion
24
Wachtel, 2011; Joyce and Nabar, 2009; Keane, 2012). We thus find that our results are substantiated by empirical literature.
We also find that the countries in which a crisis started, and which are said to be open economies, have contagion effects to other countries. We find that the Global Financial Crisis, the Icelandic crisis and the crisis of 9/11, have had contagion effects to other countries in the world. This is tested by the Granger causality test of Granger (1969). Our findings with regard to contagion effects are in line with the findings of Brière, Chapelle and Szafarz (2012) and Calvo and Mendoza (2000), because they find that globalization and contagion are related. However, these findings are in contrast with the empirical literature of Cheng and Ma (2005), who did not find any evidence of contagion effects derived from the stock markets of the United States. Forbes and Rigobon (2002) did not find contagion effects during the crises they analyzed either, such as the Asian crisis, Mexican crisis and the United States' market crash of 1987. However, our results are in line with the findings of Forbes and Rigobon (2002) for the Asian crisis and the Mexican crisis. We do not find explanations about why Cheng and Ma (2005) and Forbes and Rigobon (2002) did not find contagion effects derived from the stock market of the United States and that we did find contagion effects from the United States. However, there is room for further research on this topic.
25
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Appendix A
In this appendix we show the complete list of countries and companies used for the sample.
Table VI Sample
In this table we provide a complete list of countries and companies used for the sample.
HONG KONG SINGAPORE SWITZERLAND AUSTRALIA NETHERLANDS
BANK OF EAST ASIA CHEUNG KONG HOLDINGS CLP HOLDINGS
HANG SENG BANK HONG KONG AND CHINA GAS
HSBC HOLDINGS HUTCHISON WHAMPOA NEW WORLD DEV. POWER ASSETS HOLDINGS SUN HUNG KAI
PROPERTIES SWIRE PACIFIC 'A' WHARF HOLDINGS SINO LAND HENDERSON LD.DEV. HANG LUNG PROPERTIES CATHAY PACIFIC AIRWAYS CHINA RES.ENTERPRISE CITIC PACIFIC KUNLUN ENERGY GALAXY ENTERTAINMENT GP. LI & FUNG CHINA MRCH.HDG.INTL. CHINA OS.LD.& INV.
DBS GROUP HOLDINGS HONG KONG LAND HDG. JARDINE CYC.& CARR. JARDINE MATHESON HDG. OVERSEA-CHINESE BKG. UNITED OVERSEAS BANK KEPPEL CITY DEVELOPMENTS SINGAPORE PRESS HDG. SINGAPORE AIRLINES JARDINE STRATEGIC HDG. SEMBCORP MARINE CAPITALAND GENTING SINGAPORE ABB 'R' HOLCIM 'R' NESTLE 'R' NOVARTIS 'R' ROCHE HOLDING SWISS RE ZURICH INSURANCE GROUP
CREDIT SUISSE GROUP N UBS 'R' ADECCO 'R' SGS 'N' RICHEMONT N ADELAIDE BRIGHTON AGL ENERGY ALUMINA AMCOR ANSELL BEACH ENERGY BHP BILLITON BRAMBLES COCA-COLA AMATIL CSR GPT GROUP GUD HOLDINGS JAMES HARDIE INDS.CDI. CROMWELL PROPERTY GROUP CALTEX AUSTRALIA AUS.AND NZ.BANKING GP. WESTFIELD GROUP STOCKLAND
QBE INSURANCE GROUP WOODSIDE PETROLEUM WESTPAC BANKING TWENTY-FIRST CENTURY FOX CDI.'B' SANTOS RIO TINTO ORIGIN ENERGY (EX BORAL)
ORICA OIL SEARCH LEND LEASE GROUP LEIGHTON HOLDINGS NATIONAL AUS.BANK GOODMAN GROUP DEXUS PROPERTY GROUP WESFARMERS
HORIZON OIL ILUKA RESOURCES NEWCREST MINING BANK OF QLND. BENDIGO & ADELAIDE BANK
FAIRFAX MEDIA SEVEN WEST MEDIA OZ MINERALS SIMS METAL MANAGEMENT TELECOM CORP.NZ. (ASX) COMMONWEALTH BK.OF AUS. NUFARM HARVEY NORMAN HOLDINGS ARB VILLAGE ROADSHOW SENEX ENERGY PREMIER INVESTMENT REGIS RESOURCES SIRIUS RESOURCES PERPETUAL ALS
31
Continuing, Table VI Sample
UNITED STATES UNITED KINGDOM CANADA
EXPEDITOR INTL.OF WASH. HUNT JB TRANSPORT SVS. VERIZON COMMUNICATIONS UNITEDHEALTH GP. AT&T DOMINION RESOURCES NORFOLK SOUTHERN HOME DEPOT NIKE 'B' CSX FEDEX KIRBY WILLIAMS COS. WALT DISNEY WAL MART STORES UNITED TECHNOLOGIES UNION PACIFIC TRAVELERS COS. SOUTHWEST AIRLINES SOUTHERN RYDER SYSTEM PUB.SER.ENTER.GP. PROCTER & GAMBLE PG&E
PFIZER NISOURCE MERCK & CO. NEXTERA ENERGY MCDONALDS MATSON KANSAS CTY.STHN. JP MORGAN CHASE & CO. JOHNSON & JOHNSON INTERNATIONAL BUS.MCHS. INTEL GATX GENERAL ELECTRIC FIRSTENERGY EXXON MOBIL EXELON EDISON INTL. E I DU PONT DE NEMOURS DUKE ENERGY CONSOLIDATED EDISON CON-WAY COCA COLA CHEVRON CENTERPOINT EN. CATERPILLAR BOEING AMERICAN EXPRESS AMER.ELEC.PWR. ALASKA AIR GROUP 3M JABIL CIRCUIT GENERAL GW.PROPS. O REILLY AUTOMOTIVE FOSSIL GROUP ACE MICROCHIP TECH. INTUIT MORGAN STANLEY ACTAVIS CHESAPEAKE ENERGY PATTERSON COMPANIES STARBUCKS PRAXAIR
EXPRESS SCRIPTS HOLDING D R HORTON
BED BATH & BEYOND KOHL'S BOSTON SCIENTIFIC MOHAWK INDS. TIME WARNER ROPER INDS.NEW MACY'S
WHOLE FOODS MARKET GILEAD SCIENCES PERRIGO QUALCOMM OWENS ILLINOIS NEW KIMCO REALTY AMPHENOL 'A' BIOGEN IDEC TYCO INTERNATIONAL VERTEX PHARMS. AES US.STEEL MARATHON OIL REGENERON PHARMS. AUTOZONE XILINX CBS 'B' VIACOM 'B' AUTONATION SAFEWAY RANGE RES. CISCO SYSTEMS CABOT OIL & GAS 'A' EOG RES.
ELECTRONIC ARTS VENTAS SYMANTEC ALLERGAN PLUM CREEK TIMBER STAPLES LABORATORY CORP.OF AM. HDG. PEOPLES UNITED FINANCIAL WASTE MAN. ALTERA CHARLES SCHWAB FASTENAL DENTSPLY INTL. CELGENE CARNIVAL ALLEGHENY TECHS. TIFFANY & CO BAKER HUGHES AIRGAS MOSAIC CERNER AMEREN COCA COLA ENTS. HARMAN INTL.INDS. UNUM GROUP ADOBE SYSTEMS HCP SUNTRUST BANKS DEVON ENERGY ROSS STORES HONEYWELL INTL. NOBLE MONSTER BEVERAGE CABLEVISION SYS. ORACLE MICROSOFT T ROWE PRICE GP. EMC CONSTELLATION BRANDS 'A' HARLEY-DAVIDSON LINEAR TECH. ANADARKO PETROLEUM FISERV CITIGROUP AUTODESK PERSIMMON BT GROUP KINGFISHER ANTOFAGASTA BAE SYSTEMS TUI TRAVEL SAINSBURY (J) WPP PEARSON MORRISON(WM)SPMKTS. MEGGITT BARRATT DEVELOPMENTS IMI WOLSELEY WHITBREAD WEIR GROUP TESCO UNILEVER (UK) STANDARD CHARTERED SMITHS GROUP SMITH & NEPHEW SCHRODERS
RSA INSURANCE GROUP ROYAL DUTCH SHELL B ROYAL BANK OF SCTL.GP. RIO TINTO REXAM REED ELSEVIER RECKITT BENCKISER GROUP PRUDENTIAL NEXT
MARKS & SPENCER GROUP LEGAL & GENERAL LAND SECURITIES GROUP JOHNSON MATTHEY ITV HAMMERSON GLAXOSMITHKLINE GKN DIAGEO BUNZL BRITISH LAND BRITISH AMERICAN TOBACCO BP BARCLAYS AVIVA ASSOCIATED BRIT.FOODS HSBC HDG. (ORD $0.50) SSE
ABERDEEN ASSET MAN. ANGLO AMERICAN SAGE GROUP
UNITED UTILITIES GROUP SEVERN TRENT TULLOW OIL BABCOCK INTERNATIONAL CAPITA VODAFONE GROUP ROLLS-ROYCE HOLDINGS BG GROUP ASHTEAD GROUP TRAVIS PERKINS PARAMOUNT RESOURCES 'A' PAN AMER.SILV. TRANSGLOBE ENERGY POWER FINL. CANADIAN WESTERN BANK PARKLAND FUEL CATAMARAN CANFOR LAURENTIAN BK.OF CANADA CCL INDS.'B' BONTERRA ENERGY BARRICK GOLD SHAW COMMS.'B' TALISMAN EN. CANADIAN UTILITIES 'A' EMPIRE 'A'
HOME CAP.GP.'B' FINNING INTL. BOMBARDIER 'B' ATCO CLASS 1
PENN WEST PETROLEUM THOMSON REUTERS NAT.BK.OF CANADA ROGERS COMMS.'B' EXTENDICARE MAGNA INTL.
CANADIAN NATURAL RES. TOROMONT INDUSTRIES FAIRFAX FINL.HDG. SHAWCOR INTL.FOREST PRDS. 'A' SUBD.VTG.SHS. AGF MANAGEMENT 'B' IMPERIAL OIL AGNICO EAGLE MINES POWER CORP.CANADA CANADIAN TIRE 'A' RUSSEL METALS WESTON GEORGE TRANSALTA TORONTO-DOMINION BANK TECK RESOURCES 'B' ROYAL BANK OF CANADA LOBLAW
ENCANA
CANADIAN IMP.BK.COM. CAE
BK.OF NOVA SCOTIA BANK OF MONTREAL ENBRIDGE BCE TRANSCANADA AGRIUM SUNCOR ENERGY METRO INTERTAPE POLYMER GP. ELDORADO GOLD CAPSTONE MINING EMERA
CGI GROUP 'A' SEMAFO
DUNDEE 'A' SUBD.VTG. DOREL INDS.'B' SBVTG. METHANEX
32 Continuing, Table V Sample JAPAN DENMARK TNSC.'A' SBVTG. BONAVISTA ENERGY TRANSFORCE ENSIGN EN.SVS. BLACKPEARL RESOURCES NEW GOLD
FIRST MAJESTIC SILVER ENERPLUS
POTASH CORPORATION OF SASKATCHEWAN GOLDCORP
TOREX GOLD RESOURCES PRECISION DRILLING DOMINION DIAMOND FIRST QUANTUM MRLS. ADVANTAGE OIL & GAS PACIFIC RUBIALES ENERGY OSISKO MINING NEWALTA AECON GROUP FORTIS NORBORD NOVAGOLD RESOURCES ONEX COTT IGM FINL. QUEBECOR 'B' JEAN COUTU GP.PJC 'A' GREAT WEST LIFECO WEST FRASER TIMBER LINAMAR SNC-LAVALIN GP. TERUMO TOKYO ELECTRON SEVEN & I HDG. YAMATO HDG. NIPPON ELEC.GLASS UNY GROUP HOLDINGS FANUC TOYOTA TSUSHO AEON SECOM KYOCERA YOKOHAMA RUBBER YOKOGAWA ELECTRIC YASKAWA ELECTRIC YAMAHA UNITIKA UBE INDUSTRIES TOYOTA MOTOR TOYOBO
TOYO SEIKAN GROUP HDG. TOTO TOSOH TOSHIBA TORAY INDS. TOKYU TOPPAN PRINTING TOKYO TATEMONO TOKYO GAS
TOKYO ELECTRIC POWER TOKYO DOME TOKUYAMA TOKAI CARBON TOHO ZINC TOHO TOBU RAILWAY TEIJIN TDK TAKEDA PHARMACEUTICAL TAKASHIMAYA TAKARA HDG. TAIYO YUDEN TAISEI TAIHEIYO CEMENT SUZUKI MOTOR SUMITOMO REAL.&DEV. SUMITOMO OSAKA CEMENT SUMITOMO MITSUI FINL.GP. SUMITOMO METAL MINING
SUMITOMO HEAVY INDS. SUMITOMO ELECTRIC IND. SUMITOMO CHEMICAL SUMITOMO
SONY
SHOWA SHELL SEKIYU SHOWA DENKO KK SHIZUOKA BANK SHISEIDO SHIONOGI SHIN-ETSU CHEMICAL SHIMIZU SHARP SEKISUI HOUSE SAPPORO HOLDINGS RICOH RESONA HOLDINGS PIONEER PANASONIC PACIFIC METALS OSAKA GAS OLYMPUS OKUMA OKI ELECTRIC IND. ODAKYU ELECTRIC RY. OJI HOLDINGS OBAYASHI NTN NSK NOMURA HDG. NITTO DENKO NITTO BOSEKI NISSHINBO HOLDINGS NISSHIN SEIFUN NISSAN MOTOR NISSAN CHEMICAL INDS. NIPPON YUSEN KK NIPPON SUISAN KAISHA NIPPON STL.& SUMIT.MTL. NIPPON SODA
NIPPON SHEET GLASS NIPPON MEAT PACKERS NIPPON EXPRESS NIPPON KAYAKU NIKON NICHIREI NGK INSULATORS NEC MS&AD INSURANCE GP.HDG. MITSUMI ELECTRIC MITSUI OSK LINES MITSUI MNG.& SMELT. MITSUI ENGR.& SHIPBLDG. MITSUI FUDOSAN MITSUI CHEMICALS MITSUBISHI MATERIALS MITSUI MITSUBISHI LOGISTICS AJINOMOTO ALPS ELECTRIC AMADA ANA HOLDINGS ASAHI GLASS
ASAHI GROUP HOLDINGS ASAHI KASEI ASTELLAS PHARMA BANK OF YOKOHAMA BRIDGESTONE CANON CASIO COMPUTER CHIBA BANK CHIYODA CHUBU ELEC.POWER CITIZEN HDG. CHUGAI PHARM. COMSYS HOLDINGS CREDIT SAISON DAI NIPPON PRINTING DAIICHI SANKYO DAIKIN INDUSTRIES DAINIPPON SCREEN MNFG. DAINIPPON SUMIT.PHARMA DAIWA HOUSE INDUSTRY DAIWA SECURITIES GROUP DENKI KAGAKU KOGYO KK DOWA HDG. DENSO EBARA EISAI FUJI ELECTRIC FUJIFILM HDG. FUJI HEAVY INDS. FUJIKURA FUJITSU FURUKAWA FURUKAWA ELECTRIC GS YUASA
HEIWA REAL ESTATE HINO MOTORS HITACHI HITACHI ZOSEN HOKUETSU KISHU PAPER HONDA MOTOR IHI ISETAN MITSUKOSHI HDG. ISUZU MOTORS ITOCHU J FRONT RETAILING JAPAN STEEL WORKS JGC JTEKT KAJIMA KANSAI ELECTRIC PWR. KAO KAWASAKI HEAVY INDUSTRY
KAWASAKI KISEN KAISHA KEIO KEISEI ELEC.RAILWAY KIKKOMAN KIRIN HOLDINGS KOBE STEEL KOMATSU KONICA MINOLTA KUBOTA KURARAY
KYOWA HAKKO KIRIN MARUBENI MARUI GROUP MAZDA MOTOR MINEBEA MEIDENSHA MITSUBISHI MITSUBISHI ELECTRIC MITSUBISHI ESTATE MITSUBISHI HEAVY INDS. SUMITOMO MITSUI TST.HDG.
NIPPON TELG. & TEL. FUKUOKA FINANCIAL GP. HITACHI CON.MCH. MITSUBISHI MOTORS KONAMI
A P MOLLER - MAERSK 'A' A P MOLLER - MAERSK 'B' CARLSBERG 'A' CARLSBERG 'B' DANSKE BANK DFDS EAST ASIATIC FLSMIDTH & CO.'B' GN STORE NORD HOJGAARD HOLDING 'A' COLOPLAST 'B' BANG & OLUFSEN 'B' ALK-ABELLO NOVO NORDISK 'B' SYDBANK NKT JYSKE BANK
GREENTECH ENERGY SYS. AMBU 'B'
UNITED INTL.ENTS. TK DEVELOPMENT SPAR NORD BANK SIF FODBOLD 'B' SCANDINAVIAN BRAKE SYS. SANISTAL 'B'
PER AARSLEFF NEWCAP HOLDING JEUDAN GLUNZ & JENSEN SKAKO
LAND & LEISURE 'B' GYLDENDAL 'A' NORDICOM TORM DMPKBT.NORDEN GRONLANDSBANKEN ROBLON 'B' BRD KLEE 'B' REALIA HARBOES BRYGGERI 'B' RIAS 'B' NORRESUNDBY BANK HOJGAARD HLDG.'B' TOTALBANKEN BRODRENE HARTMANN 'B' ANDERSEN & MARTINI ARHUS ELITE 'B' VICTORIA PROPERTIES VESTJYSK BANK VICTOR INTERNATIONAL TOPSIL SEMICON.MATS. TIVOLI 'B' SP GROUP SOLAR 'B' SALLING BANK SKJERN BANK ROYAL UNIBREW RINGKJOBING LANDBOBANK OSTJYDSK BANK NTR HOLDING NORDJYSKE BANK NORDFYNS BANK MONS BANK
33 Continuing, Table VI Sample INDIA H&H INTERNATIONAL ALM BRAND TOPDANMARK AURIGA INDUSTRIES 'B' AKTKT.SCHOUW & CO. ARKIL HOLDING BIOPORTO BOCONCEPT HOLDING 'B' BRONDBY IF DALHOFF LAR.& HORNEMAN DANTAX RADIO DANTHERM DJURSLANDS BANK DSV 'B' EGETAEPPER 'B' EXPEDIT 'B' FE BORDING 'B' FLUGGER 'B' GABRIEL HOLDING GYLDENDAL 'B' HVIDBJERG BANK INVSTSSL.LUXOR JENSEN & MOL.INVEST
GUJ.ALKALIES & CHEMS. MAX INDIA
SHIPPING CORP.OF INDIA MASTEK GUJARAT INDS.POWER TATA COMMUNICATIONS NCC DELTA CORPORATION NATIONAL ALUMINIUM CARBORUNDUM UNIVERSAL CHENNAI PETROLEUM HINDUSTAN ZINC BHARAT HEAVY ELS. MNGL.REF.& PETROCHEM. STEEL AUTHORITY OF INDIA RASHTRIYA CHEMS.& FERT. BHARAT PETROLEUM HINDUSTAN PETROLEUM DCM SHRIRAM CONSOLIDATED AARTI INDUSTRIES KOTAK MAHINDRA BANK TATA ELXSI GUJARAT GAS LINDE INDIA WELSPUN INDIA HSIL RELIANCE INDL.INFR. MAHARASHTRA SEAMLESS CHOLAMANDALAM INV.& FIN.
AGRO TECH FOODS RADICO KHAITAN J M FINANCIAL AMARA RAJA BATTERIES PRAKASH INDUSTRIES P&G.HYGIENE & HLTH.CARE 3M INDIA WYETH SHRIRAM TRAN.FIN. ROLTA INDIA ATUL RELIANCE CAPITAL BALMER LAWRIE DEWAN HOUSING FINANCE LAKSHMI MACHINE WKS. HINDUSTAN OIL EXP. CANFIN HOMES VARDHMAN TEXTILES ABB HEG TATA INVESTMENT UNICHEM LABORATORIES ANANT RAJ INDIA CEMENTS TINPLATE CO.OF INDIA KSB PUMPS AMTEK AUTO
INGERSOLL-RAND (INDIA) WIPRO
MAHINDRA UGINE STEEL CO.
BLUE STAR SWAN ENERGY KESORAM INDUSTRIES
KANSAI NEROLAC PAINTS KAJARIA CERAMICS HOUSING DEVELOPMENT FIN. CROMPTON GREAVES BASF INDIA BAJAJ ELECTRICALS ASTRAZENECA PHARMA INDIA WHIRLPOOL OF INDIA WEST COAST PAPER VOLTAS
VIP INDUSTRIES VENKY'S (INDIA) VST INDUSTRIES UTTAM GALVA STEELS USHA MARTIN UNITED SPIRITS UNITECH TUBE INVESTMENTS OF IDA. UFLEX TRENT TITAN COMPANY THOMAS COOK (INDIA) TATA STEEL
TATA POWER TATA MOTORS
TATA GLOBAL BEVERAGES TATA CHEMICALS T V S MOTOR SWARAJ ENGINES SUPREME INDUSTRIES SUNDRAM FASTENERS STATE BANK OF INDIA SRF SKF INDIA SIEMENS SHRENUJ SHREE CEMENT SHANTHI GEARS SESA STERLITE RUCHI SOYA INDUSTRIES RELIANCE INFRASTRUCTURE RELIANCE INDUSTRIES RAYMOND RANBAXY LABS. RALLIS INDIA PIRAMAL ENTERPRISES PHOENIX MILLS PFIZER PENINSULA LAND PATEL ENGINEERING MRF MERCK MANGALORE CHEMS.& FRTZ.
MAHINDRA & MAHINDRA MAHARASHTRA SCOOTERS MADRAS CEMENT LARSEN & TOUBRO JYOTI STRUCTURES JUBILANT LIFE SCIS. JBF INDUSTRIES JB CHEMICALS & PHARMS. JAIN IRRIGATION SYSTEMS J K TYRE & INDS. J K LAKSHMI CEMENT
ITC JINDAL SAW INDIAN HOTELS INDIA GLYCOLS HOTEL LEELA VENTURE HNYWELL.AUTOMATION IDA. HINDUSTAN UNILEVER HINDUSTAN CONSTRUCTION HIMACHAL FUTR.COMMS. HERO MOTOCORP GUJARAT FLOUROCHEMICALS HINDALCO INDUSTRIES GUJ.STE.FERT.& CHEMS. GREAVES COTTON GREAT EASTERN SHIPPING GRASIM INDUSTRIES GUJ.NARMADA VLY.FCM. GODFREY PHILLIPS INDIA GLAXOSMITHKLINE PHARMS. GRAPHITE INDIA GILLETTE INDIA GHCL GABRIEL INDIA FINOLEX INDUSTRIES FINOLEX CABLES FEDERAL-MUL.GTZ.(INDIA) FAG BEARINGS INDIA EXIDE INDUSTRIES ESSEL PROPACK ESCORTS ESAB INDIA ELGI EQUIPMENTS ELECTROSTEEL CASTINGS EIH
EID PARRY (INDIA) EICHER MOTORS DR REDDYS LABORATORIES DEEPAK FERT.& PETROCHEM. DCW CUMMINS INDIA COROMANDEL INTERNATIONAL COLGATE-PALMOLIVE INDIA CIPLA
CENTURY TEXTILES & INDS. CENTURY ENKA
CLARIANT CHEMS.INDIA BRITANNIA INDS. BOSCH
BOMBAY DYEING & MNFG. BOMBAY BURMAH TRADING BHARAT FORGE BIRLA CORPORATION BERGER PAINTS INDIA BALKRISHNA INDUSTRIES BAJAJ HOLDINGS & INVS. BAJAJ HINDUSTHAN AUTOMOTIVE AXLES ASIAN PAINTS ASHOK LEYLAND ARVIND BALLARPUR INDUSTRIES ASAHI INDIA GLASS APOLLO TYRES AMBUJA CEMENTS AKZO NOBEL INDIA ACC
ABAN OFFSHORE HIMATSINGKA SEIDE SANOFI INDIA SUNTECK REALTY CORE ED.AND TECHS. MAX INDIA
34
Continuing, Table VI Sample
PAKISTAN INDONESIA BRAZIL KENYA
MILLAT TRACTORS SIEMENS ENGINEERING BATA PAKISTAN NISHAT MILLS PAKISTAN CABLES GRAYS OF CAMBRIDGE CENTURY PAPER PACKAGES ABBOTT LABS.(PAK.) ASKARI BANK ATLAS HONDA SHELL PAKISTAN ADAMJEE INSURANCE CHEARAT CEMENT COMPANY NESTLE PAKISTAN JUBILLE INSURANCE ATTOCK REFINERY MURREE BREWERY COMPANY INTERNATIONAL INDS. FEROZE1888 MILLS SONERI BANK FAUJI FERTILIZER DAWOOD HRC.CHEMS.CORP. EFU GENERAL INSURANCE SUI SOUTHERN GAS SUI NORTHERN GAS PICIC GROWTH FUND PAKISTAN TOBACCO RAFHAN MAIZE PRDS. PAKISTAN STATE OIL PAKISTAN OILFIELDS PAK SUZUKI MOTOR NISHAT (CHUNIAN) NIB BANK NATIONAL REFINERY KOHINOOR TEX.MILLS KARACHI ELECTRIC SUPP. INDUS MOTOR COMPANY ICI PAKISTAN
GLAXOSMITHKLINE PAK. ENGRO
INDO ACIDATAMA MODERNLAND REALTY MATAHARI PUTRA PRIMA ARGHA KARYA PRIMA IND. SMART
JEMBO CABLE EVER SHINE TEXTILE KMI WIRE AND CABLE SORINI AGRO ASIA CRPR. SONA TOPAS TOURISM IND.
PLAZA INDONESIA REALTY METRO REALTY KABELINDO MURNI PERMATA PRIMA SAKTI ZEBRA NUSANTARA INTILAND DEVELOPMENT KALBE FARMA NIPRESS MODERN INTERNASIONAL SEMEN GRESIK RESOURCE ALAM INDONESIA
POOL ADVISTA INDONESIA CHAROEN POKPHAND INDO.
ASIA PACIFIC FIBERS SUMI INDO KABEL ARGO PANTES VOKSEL ELECTRIC CHAMPION PACIFIC INDO. HANSON INTERNATIONAL SURYA TOTO INDONESIA ASURANSI HARTA AMAN PRA.
INDO KORDSA GUDANG GARAM CLIPAN FINANCE INDONESIA BANK ARTHA GRAHA INTSL. DUTA PERTIWI NUSANTARA INDO-RAMA SYNTHETICS BUMI RESOURCES INTANWIJAYA INTSL. INDAH KIAT PULP & PAPER ALAKASA INDUSTRINDO ULTRAJAYA MILK IND.& TRCO. TRIAS SENTOSA PAN BROTHERS ERATEX DJAJA EKADHARMA INTERNATIONAL INDOSPRING
PRIMA ALLOY STEEL UNVL. MAYORA INDAH TIGARAKSA SATRIA MERCK SHARP DOHME PHARMA SUSP - SUSP.05/09/13
PANASIA INDO RESOURCES LIONMESH PRIMA RIG TENDERS INDONESIA TEMBAGA MULIA SEMANAN PETROSEA VALE INDONESIA
RODA VIVATEX BFI FINANCE INDONESIA MILLENNIUM PHACN.INTL. HOTEL SAHID JAYA INTL. GAJAH TUNGGAL DUTA ANGGADA REALTY SUMMARECON AGUNG BUANA FINANCE PUDJIADI & SONS EST. CAPITALINC INVESTMENT METRODATA ELECTRONICS ASTRA INTERNATIONAL PABRIK KERTAS TJIWIKIMIA HERO SUPERMARKET UNITED TRACTORS UNILEVER INDONESIA UNGGUL INDAH CAHAYA TIFICO FIBER INDONESIA TAISHO PHARM.INDONESIA STAR PACIFIC SEPATU BATA SUPREME CAB.MNFG. PANIN INSURANCE PAKUWON JATI MULTIPOLAR
MULTI PRIMA SEJAHTERA PANIN FINANCIAL MULTI BINTANG INDONESIA MERCK MATAHARI DEPARTMENT SOE. MASKAPAI REASI.INDO. JAYA PARI STEEL JAPFA COMFEED INDONESIA
JAKARTA INTL.HTLS.& DEV. INTER DELTA ICT.TUNGGAL PRAKARSA HOLCIM INDONESIA GOODYEAR INDONESIA EQUITY DEVELOPMENT INV. DELTA DJAKARTA CENTEX CITRA TUBINDO BERLINA
BERLIAN LAJU TANKER SUSP - SUSP.25/01/12 BENTOEL INTL.INVESTAMA BAYU BUANA
BANK PERMATA BANK PAN INDONESIA BANK INTL.INDONESIA BANK DANAMON INDONESIA
BAKRIE SUMATERA PLTNS. ASURANSI RAMAYANA ASURANSI DAYIN MITRA ASURANSI BINA DANA ARTA
ASTRA GRAPHIA APAC CITRA CENTERTEX BAKRIE & BROTHERS ASURANSI BINTANG ITAUUNIBANCO PN OI PN ELETROBRAS ON USIMINAS PNA VALE PNA SOUZA CRUZ ON METALURGICA GERDAU PN BRASKEM PNA LOJAS AMERIC PN PETROBRAS PN ELETROBRAS PNB PETROBRAS ON LIGHT ON GERDAU PN BRADESCO PN BRADESCO ON BANCO BRASIL ON KENOLKOBIL BAMBURI CEMENT KENYA POWER & LIGHTING KAKUZI BAT KENYA STANDARD CHARTERED BANK SASINI
NATION MEDIA GROUP KENYA COMMERCIAL BANK
