The effects of delisting an
American Depository Receipt.
Author:
Stijn Swaans
Student number: 5942640
Supervisor:
Jeroen Ligterink
Study:
MSc Business Economics; specialization Finance
Field:
Finance
Credits:
15
Topic:
ADR Delisting
Dataset:
Wharton Research Data Services, DataStream
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Legend
Introduction
p2.
Literature review
p4.
Hypothesis
p11.
Methodology
p14.
Results
p17.
Conclusion & Discussion
p21.
Appendix
p23.
Robustness checks
p.33
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I.
Introduction
The aim of this research is to examine the consequences of delisting an American Depository Receipt(ADR) since the introduction of rule 12h-6. An ADR is a certificate that is traded on a US-financial market, but represents a bundle of stocks of a non-US firm. ADRs are, in general, a well examined subject with articles as Miller(1999), Karolyi(2008) and Doidge(2004). However, the specific topic of the consequences of delisting an ADR, is a less developed area. The topic of delisting has gained more interest with the increasing number of delisting firms since the year 2000 (Marosi, 2008). In the decade of the 1990s a total of ten firms deregistered from American exchanges (Marosi, 2008). In the period of 2000 till 2004 the amount of deregistration’s already had summed up to 74 (Marosi, 2008). Marosi(2008) states that the increase in the amount of delisting’s is likely due to the changes in SEC registration requirements. The total deregistration numbers from 1990 till 2006 are presented in table A1, located in the appendix.
During the 1990s, the US capital market had the biggest pool of foreign listings and was the biggest player in the field of raising capital. In the period of 2000 till 2005 the US market share in the field of foreign listings dropped dramatically (Zingales, 2007). The significant increase in the compliance costs of a cross-listing is seen as the most important reason for the decrease in market share (Zingales, 2007). Doidge(2009) links the increase in compliance cost, as described by Zingales(2007), to the introduction of the Sarbanes-Oxly Act (SOX) in 2002 (Sarbanes, 2002). The SOX law increased the costs for firms, and tightened the obligated accounting rules associated with cross-listings. According to Doidge(2009). the introduction of the SOX law is also responsible for the increase in outflow of listed firms. Daugherty(2011) confirms the theory that the introduction of SOX causes mainly the increase in delisting’s. Doidge(2010) adds that rule 12h-6 introduced in March 2007, changed the situation even more. Rule 12h-6 makes it easier to delist from a US exchange in comparison with the standard set by the SOX law (Doidge, 2010). Specifically, the requirements in order to terminate are decreased. Prior to rule 12h-6, SEC reporting requirements were only suspended at time of planning a delisting. A twelve-month period followed the suspension before a 15-F form for definite delisting could be handed. After the introduction of rule 12h-6, a more direct termination of the reporting requirements is possible, due to a quantitative benchmark. If the trading volume in the US is lower than five percent of the total world trading volume of the firm; delisting is a possibility. Under rule 12h-6, firms no longer have to suspend their reporting
requirements and, therefore, follow the long track of the SEC. It is currently much easier for firms to deregister (Rule 12h-6, 2007). All the adoptions in rule 12h-6 combined form an easier and more transparent process (Rule 12h-6, 2007).
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The question that arises in current literature from here is then: what the effects are of the delisting
of an ADR on the stock in the home market, since the introduction of rule 12h-6. To answer this
question, and to make a contribution to the existing literature, different hypotheses are made. These hypotheses specifically concern the following: return, liquidity, governance, ownership and firm size. As will be described in the literature review, return and liquidity are the two main ratios to measure performance. Main articles such as Doidge(2010) and You(2012) use these ratios. Besides these variables there are also other factors that influence delisting performance. Doidge(2010) and Daugherty(2011) describe that governance structure in the home country influences after delisting performance as well. Hence, this variable is taken into account as well. Doidge(2010) also describes the effect of insider ownership structure on performance. The last variable that is taken into account is the size of the firm as described by Yang(2013). The results of research on these topics will help in answering the main question of this thesis.
The research of this thesis expands the existing knowledge as described in the literature review by examining the effects of delisting an ADR, following the introduction of rule 12h-6. The research is a contribution due to the uncertainty surrounding the true effects of a delisting in current times. In the literature review it will be explored what the consequences are of delisting, before rule 12h-6 and around the introduction of rule 12h-6. However, long term effects were not extensively covered in prior research. The manner in which the direct effect of delisting under rule 12h-6 develop over time, and what the long term delisting effects are, is unclear at this stage. In the existing literature this part has not been covered extensively. Which means that this research contributes in that it covers the current consequences of the delisting of an ADR. It helps to guideline the decision making process in the question to delist or not.
To answer the research question the following steps will be taken. In the second part of this thesis, the existing literature of ADRs will be described. The topics on what the motivation is to undertake a cross-listing in the first place, and what the effects are of a cross-listing on the stock in the home market will be deepened in this part of the thesis. Major articles on these topics are compared to summarize the current situation. The third part will exist of the hypotheses of the research. Hypotheses on stock return, liquidity, governance structure, ownership and size are formed. The fourth part of this thesis will consist of the methodology of the research. The event study
methodology, regressions and motivation on why and how to get to an answer of the hypotheses are explained in this part of the thesis. In the fifth part, the results of the research will be presented. The assumptions that underlie the results are deepened. The implementations and economic effects follow then. In the sixth part a summary and the conclusion will be presented.
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II.
Literature review
To examine what the effects of delisting an ADR are, first it must be explained what an ADR exactly is. After this explanation, the motivation for a cross-listing will be discussed together with the additional benefits associated with a cross-listing. Next, the reasons to conduct a delisting of an ADR are discussed. After this, the consequences of delisting are explained and the current situation with the defects on this topic are deepened.
- What is an ADR?
The abbreviation ADR stands for “American Depository Receipt”. It is a certificate that is listed and/or offered on an US financial market, but represents a specific number of shares in a
foreign(non-US) company. At time of the cross-listing, an investment bank in the home country is the depository bank of the shares that form an ADR, Miller(1999). The depository bank in the home country keeps holding these shares, while an investment bank in the US issues the ADR. ADRs are used primarily as an instrument for accessing a foreign capital market. The first time an ADR was listed on a US stock exchange was in 1927, Miller(1999).
ADRs are divided into four main divisions. Level I ADRs are listed in the “over the counter”(OTC) market. In a level I type of registration the firm does not have to fully comply with the US Securities and Exchange Commission(SEC) regulations. The drawback of level I ADRs is that they are only listed and not offered. With a level II depository receipt, a company is listed on one of the largest US stock exchanges, for example the NYSE, NASDAQ or AMEX. The fee entering cost for a level II registration are on the other hand much higher, in comparison with level I ADRs (Miller, 1999). Level II ADRs have to fulfill the US GAAP regulations, which generate additional cost to the registration. While level I and level II ADRs are created by existing shares, level III ADRs on the other hand use an Initial Public Offering(IPO) as a method to raise new equity capital (Miller, 1999). The Main difference between level II and level III, is that in addition to being listed, a level III ADR is offered. The fourth level of ADR is called a Rule114A registration and represents a private placement. The difference with the first three levels of ADRs and a Rule144A is that this type of registration does not have to fulfill the SEC regulation requirements. This lack of SEC registration causes that only qualified institutional buyers can trade in these type of ADRs (Saunders, 1994). An overview of the levels of ADRs and their requirements is situated table A2, located in the appendix. The reasons why to conduct a cross-listing, and what the benefits are for the US investor and for the foreign company, are discussed in the next part of this literature review.
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- Why perform a cross-listing?There are several major reasons why a cross-listing is performed. Starting with the US investors point of view: with cross-listing US investors can invest in a foreign company (Karolyi, 2008). The investment in foreign companies diversifies the portfolio of the investor and therefore the risk level is lowered (Jiang, 1998). In addition to this advantage, an ADRs also has lower transaction cost when compared to a direct investment in the home country exchange market of a foreign company (Saunders, 1994). The US investor benefits as well from investing in an ADR because they often have larger growth opportunities, in comparison with US stock options. This means that investing in an ADR will give US investors attractive returns (Jiang, 1998). In the sense of currency exchange fees, an additional advantage is that the dividends are paid out in the home currency of US dollars. The benefits combined of home currency, lower transaction cost, growth opportunities and
diversification benefits, form the main advantages for the US investor when investing in an ADR. For the non-US companies that issue an ADR, the advantages of performing a cross-listing are as follows: a cross-listing is beneficial for a non-US company in a way that it can attract new investors. The US is one of the largest pools of capital investments in the world, and with a cross-listing a non-US firm benefits by attracting these investors (Saunders, 1994). A benefit for a non-non-US company is also the exposure of the brand name in the US. With the increase in investor recognition, more value is added to the company (Baker, 2002). On the point of reducing the costs, a benefit is that ADRs can improve stock based pay to US employees (Saunders, 1994). The article of Pagano(2002) specifies the benefits for non-US firms extensive, and finds additional significant benefits. These are: foreign expertise, liquidity benefits. In terms of foreign expertise this means that, for example, high-tech firms have a slightly higher probability to cross-list. This is due to the fact that tech firms benefit more from the developed technological industry in the US. Concerning the risk levels that come with cross-listing, Karolyi(1998) finds that domestic risk levels are reduced after a cross-listing. Due to diversification, the global market risk decreases and therefore lowers the cost of equity causing the domestic risk levels to reduce (Karolyi, 1998). Linking this to the cost of capital, Karolyi(1998) finds results that due to the cross-listing, and therefore the reduction in risk, the cost of capital decreases. The benefits in terms of attracting capital, investor recognition, foreign expertise, liquidity benefits, risk reduction, and the decrease in cost of capital together form the advantages for a non-US firm to perform a cross-listing on a US financial market. What the specific benefits are for the home stock and what kind of premiums are created, are discussed in the next part.
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- What kind of premiums are created by an ADR at time of a cross-listing?
The return fluctuations of cross-listings have been examined extensively in the past. One of these articles is of Jayaraman(1993), which finds evidence for a positive abnormal return for the underlying stock at the announcement date of the ADR. This means that with the issuance of an ADR, there is value attached for the underlying stock in the home market. Miller(1999) also examines the returns for the underlying stock after a cross-listing and finds evidence for a positive abnormal return around the time of the announcement, thus coming to the same conclusion as Jayaraman(1993). The results do, however, differ for different type of ADRs. The positive abnormal returns were specifically for type II ADRs. The remark here is that when the distinction is made between public firms and private firms, another result is found by Miller(1999). Private depository receipts cause, contrary to the public ones, a negative abnormal return. The article of Foerster(1999) confirms these findings of a positive abnormal return that come with a cross-listing as described in Jayaraman(1993) and Miller(1999). There is, however, evidence that these returns differ for the type of industry according to Foerster(1993). The remark in the article of Foerster(1999) is that it finds evidence that the positive abnormal returns only exist in the period before and around the listing. While in the long run period after the delisting, the abnormal returns becomes negative. You(2012) finds the same results with the most recent study on cross-listing premiums. In this research, with a similar research method as Foerster(1999), the premiums exists of a large increase in the stock return before and around the listing, but becomes significantly negative in the period after the listing (You, 2012).
An event study methodology is used for calculating the abnormal returns in the articles named above. For the calculation of the returns in Jayaraman(1993), an event study is used with a time frame of 150 days before and 150 days after the listing date. The article uses a research period of 1983 till 1988. Miller(1999) uses an extended research period of 1985 till 1995, with timeframes of 150 days before and at least 125 days after the listing date. The research of Miller(1999) exists of 181 firms from 35 countries. To adjust for time differences between countries, a three day time window around the listing date was used in Miller(1999). Foerster(1999) uses a research period of 1976 till 1992, with 153 firms from 11 different countries. The time frames that Foerster(1993) uses exists of 250 days before till 250 days after the listing. Foerster(1999) presents the following numbers in his results: the pre-listing period results in a positive abnormal return of 19%. Around the listing this abnormal return is 1,2%. While in the post-listing period the abnormal returns is negative, with a 14% loss. The research period that You(2012) uses in a similar research is 1997 till 2007. The reason that such an abnormal stock return premium exists, is discussed is the next part.
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- Why does the cross-listing premium exists?Evidence for the existence of a premium as described in Jayaraman(1993), Miller(1999) and
Foerster(1999) is found by the article of Doidge(2004). In this article it is presented that the existing shareholders at time of the listing have reduced incentives to exploit private benefits of control. These private benefits arise when a company has growth opportunities that cannot be exploited in the home market. Listing in the US will make it more difficult to extract private information for controlling shareholders (Doidge, 2004). Instead of exploiting these private benefits, the existing shareholders exploit the growth potential of the company and, therefore, an abnormal return arises. A small remark to the article of Doidge(2004) is made. Due to the dataset that they use, it is possible that the premiums may have risen to such an extent due to the fact that the growth companies were successful in a market that was already performing well. These conditions were present in the American stock exchanges in the 1990s, the time period from which the data of the research of Doidge(2004) is taken. Lang(2003) adds as a potential reason for the existence of a premium that analyst coverage and forecast accuracy increases. With the fact that cross-listing improves coverage and accuracy, the link is made to value enhancement. In general, an increase in accuracy and coverage enhances value. So cross listing is value enhancing through the fact that tools as coverage and accuracy increase (Lang, 2003).
- Why perform a delisting?
With the value enhancement that comes with a cross-listing as described in Jayaraman(1993), Miller(1999) and Foerster(1999), the increase in delisting’s is unclear. Marosi(2008) examines possible explanations and finds evidence that the increase in delisting’s is mainly due to the introduction of the Sarbanes-Oxley Act(SOX). Before the 2000s there was hardly any delisting activity. This changed after the introduction of the SOX act in 2002. The SOX law is an additional set of rules consisting of a combination of extra accounting obligations and a rise in compliance costs (Sarbanes, 2002). Marosi(2008) finds results that the SOX act caused a reduction of the net benefits of cross-listing registration at a US stock exchange, leading to an increase in the number of
delisting’s. The reduction in net benefits was especially the case for relatively smaller firms with low trading volume and high inside control. From the results Marosi(2008) concludes that cross-listing is less beneficial after, then before the introduction of the SOX law. The article of Daugherty(2011) examines the effects of the introduction of the SOX act as well. Similar to the article of
Marosi(2008), it finds that the introduction of the SOX act decreases the benefits for listing in the US and therefore firms have more incentive to delist. In the explanation of the reason for the increase in delisting’s, Daugherty(2011) also focusses on the aspect of cultural differences.
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Daugherty(2011) finds evidence that, after the introduction of the SOX act, the group of firms that has the most incentive to delist, is the group with the most cultural similarities with the US. In the pre-SOX period, the opposite was true(Daugherty, 2011). The conclusion made from this, is that the US lost their direct competitive advantage and, therefore, the amount of delisting’s have risen to such an extent after the introduction of the SOX act (Daugherty, 2011).
Opposite of Marosi(2008) and Daugherty(2011), the article of Doidge(2009) finds results that the SOX introduction did not affect the existence of the cross-listing premium, and therefore the probability to delist. Doidge(2009) finds results that, even after the introduction of SOX, the cross-listing premium still exists. However, the dataset used in this article only covers a period until 2005. Thus, with the result that the premium still exists, Doidge(2009) states that the true effect of the introduction of the SOX law can only be truly examined in a couple of years. The article of Doidge(2010) extended this research of Doidge(2009) and finds also contradictory results in comparison with Marosi(2008) and Daugherty(2011,) on the reason for the increase in delisting’s. Doidge(2010) states that the effect of SOX on the stock price return does not affect the delisting decision process and gives an explicit reason. According to Doidge(2010), the introduction of the exchange act rule 12h-6 is the main reason for the increase in delisting’s since 2007. The rule 12h-6 law made it easier for firms to deregister from the SEC and, therefore, it is easier to delist in general. Introduced in March 2007 as a counterpart of the SOX law, it had a negative effect on the US
markets (Fernandes, 2010). What the effects are for the returns and liquidity of the firms that are delisting from the US stock exchanges, is deepened in the next part.
- What are the effects of delisting, on the home stock?
The effects of a delisting on the returns in the home market is first examined by Liu(2005). They investigate the voluntary delisting’s of US firms from Japanese exchanges. The results are that there is not a significant price change after a delisting (Liu, 2005). This signals that the delisting does not have any negative effect for the home market stocks. A remark on Liu(2005) is that US- firms do not benefit as much from cross-listing in comparison with non-US firms that list on a US stock exchange. A second remark is that in the long term the price of the stock decreases. A paper that specifically examines the delisting effects for firms leaving the US stock exchanges is You(2012). This article finds significant results of a negative return effect for the stock price in the home market, although this does slowly diminish in the long run. Meaning that, in the long run, no significant price change is found. You(2012) uses an event study with a timeframe of 1997 till 2007. The article of Yang(2013) examines the abnormal returns in comparison with the firms still listed on a US exchange. Compared to these firms, there is also no significant change in the abnormal return.
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- General consequences of delisting an ADR.The act of deregistering also influences, in addition to the price, other determinants. The article of You(2012) finds a significant effects on the liquidity trading volume. The result is that the trading liquidity decreases significantly after a delisting. This is due to the fact that companies that perform a delisting, often already have a decreasing trend in there trading volume levels. The expectation is that this trend will continue after the delisting (You, 2012). The decrease in trading volume after a delisting follows from this, but is not so logical as it seems. The article of Amihud(2002) described earlier the relationship of returns and liquidity. This article finds that if the illiquidity rises, in other words if the liquidity decreases, then the returns will increase. In the case described in You(2012) where the liquidity decreases, the return decreases or remains the same in the long run. The reason that You(2012) and Amihid(2002) have conflicting results is unclear at this time.
Doidge(2010) finds specific result concerning governance quality. It finds that firms from weaker investor protected countries exert more negative abnormal price reactions after a delisting. The timeframe that Doidge(2010) uses for the research is 2002 till 2008. Yang(2013) finds, similar to Doidge(2010), that weaker governance quality causes significantly worse operating performance. Fernandes(2010) finds, in line with these articles, that with the introduction of rule 12h-6 the firms from countries with weaker investor protection perform worse. This worse performance is due to the relatively easier option to return to the less stringent regulation rules of the home country, in comparison with the US. The article of Yang(2013) also finds evidence that the growth in the post-listing period is significantly negative in comparison with listed firms. In addition to the governance quality and growth issues, the article of Yang(2013) also finds signals that larger firms perform worse after a delisting. A possible explanation for this is that larger firms have less problems dealing with the requirements of the SEC. This is because larger firms often have larger financial assets and therefore a higher buffer. The default risk also increases after a delisting due to the diminishing of diversification. This causes that higher leveraged firms perform worse after a delisting (Yang, 2013). A summary of a the main articles described in this literature review are presented in table 1, situated on the next page.
The world of delisting has changed in the last couple of years. Delisting is a problem for the US financial sector, because it causes a loss in competiveness. This problem was magnified with the exchange act rule 12h-6, which made is easier to deregister. The introduction of rule 12h-6 caused a huge increase in the amount of delisting’s (Doidge, 2010). There is no research available that specifically examines the long run effect of the introduction of the rule 12h-6 law. For the non-US firms that want to delist, the question arises what the consequences are now that the markets have
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responded to the easier possibilities to delist. This thesis will attempt to fill this gap in the literature by examining the effects on firms after a delisting, since the introduction of the exchange act rule 12h-6 in March 2007. The combination of these results will help firms in the decision making process of conducting a delisting of an ADR, in current times.
Table 1: “Overview literature review”.
Short summary of the findings of the main articles that are relevant for this thesis.
Article: Timespan Test Outcome
Marosi(2008) 2000-2007 Did the introduction of SOX caused the large increase in delisting’s?
“Net benefits of cross-listing dropped due to SOX. Particularly for small firms with a low trading volume.”
Daugherty(2011) 2000-2010 How did the introduction of SOX change the number of delisting’s?
“Post-SOX there is a higher probability to delist if a firm is from a country with similar cultural characteristics as the US.”
Doidge(2010) 2002-2008 Stock price reactions to deregistration. “Impact of SOX is not a determinant to deregistration . Stock price reactions are negative. Less negative around introduction rule 12h-6. Weaker investor protected countries exert more negative abnormal price reactions.”
You(2012) 1997-2007 Test on the consequences of delisting, in terms of risk and liquidity.
“Negative effect on stock price after delisting, but diminishes in long run. Trading volume decreases significantly after the delisting.”
Yang(2013) 2002-2008 Test on performance after deregistration.
“No significant abnormal return changes with firms that stay listed. Weaker governance quality is associated with significant worse operating performance. Growth performs relatively worse in post-listing period. Relatively Large and more leveraged firms perform significant worse in terms of return.”
Fernandes(2010) March-2007 Test of the market reaction on the introduction of Rule 12h-6.
“Cross-listing is most valuable for firms from weaker investor protected countries. So the market reacts more negative for firms from weak investor protected countries.”
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III.
Hypothesis
The research of this thesis examines what the effects are of the delisting of an ADR on the stock in the home market, since the introduction of rule 12h-6. As described in the literature review the introduction of SOX caused a fluctuation in the world of delisting’s. Existing knowledge on returns, liquidity, governance structure, insider ownership and size are all affected by SOX. With the introduction of rule 12h-6 by the SEC, as a counterpart of SOX, delisting effects changes even more (Rule 12h-6, 2007). Especially the impact regarding local governance issues and inside control (Doidge, 2010). Rule 12h-6 makes it in general easier to delist (Doidge, 2010). The two main ratios to measure impact on the stock market used in prior research are: return and liquidity. Hypotheses on all these topics are tested in order to answer the main research question.
The first hypothesis examines the effect on the return of the stock. To define what the expectation is of this first hypothesis, the literature review is consulted. Regarding the effect of stock returns after a delisting, there is no consensus in the current literature. Namely, You(2012) finds results for a negative effect on the stock price at the announcement, but this negative effect fades away in the long run. The remark here is that the dataset that You(2012) uses is until 2007, so prior to the introduction of rule 12h-6. Doidge(2010), however, did find negative returns at the announcement and in the long run. The remark here is that the dataset Doidge(2010) uses contains data from before rule 12h-6, and some data from shortly after the introduction. As rule 12h-6 is now fully adopted, the expectation for this research is that the stock effect returns has changed. This is because all the home stock markets have adopted to the changes on cross-listing, and have anticipated on the increased possibility to delist. Therefore the first hypothesis that tested is as follows:
H1: “There is no negative return effect on the home stock, at the announcement or after the delisting of an ADR, since the introduction of rule 12h-6.”
The second hypothesis examines the consequences for the trading volume liquidity in the home market, after the delisting of an ADR. Concerning the case of liquidity You(2012) finds results
signaling that the home market liquidity level drops after the delisting. Although a remark is made by Amihud(2002) that this is unlikely. The liquidity level that is tested in You(2012) uses the local market trading volume as a proxy in the regression. You(2012) states that trading volume is a significant proxy in examining the movement of liquidity. Since the introduction of rule 12h-6 it is relatively much easier for firms with very low US trading volume to delist (Rule 12h-6, 2007). These type of firms have hardly any benefit in terms of liquidity anymore at time of the listing.
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Hence, the expectation is that the liquidity levels in the home market do not suffer any negative effect anymore at the announcement or in the long run. Therefore, hypothesis number two is as follows:
H2: “Trading volume liquidity does not decrease significantly, at the announcement or after the
delisting of an ADR, since the introduction of rule 12h-6.”
To specify the results and consequences of the hypotheses more, the results are also examined for sub-divisions that are influenced. After the introduction of the SOX law the relationship concerning governance and delisting are changing. Since 2002 good governance countries are more likely to delist, contrary to the pre-SOX period (Daugherty, 2011). This is partly due to the tighter regulation and delisting rules introduced with SOX. Doidge(2010) also finds evidence for results concerning the level of investor protection. The higher probability of good governance countries to delist causes a significantly more negative return for firms from bad governance countries. This is because firms from bad governance countries are expected to have more difficulty deregistering, from the tightening SEC rules (Doidge, 2010). Since the introduction of rule 12h-6 it is much easier to deregister from these tight regulations. With this, the expectation that firms from bad governance countries will experience more difficulty with deregistration, is vanishing. Markets will react to the increase in probability to delist of firms from bad governance countries. The substantiation of why firms from bad governance countries perform worse is not complete anymore. Therefore, the following hypothesis arises:
H3: “Returns are not related to the level of governance structure in the home country, at the announcement or after of the delisting of an ADR, since the introduction of rule 12h-6.”
Another aspect that is directly influenced by the introduction of rule 12h-6 is the topic of insider ownership. Insiders benefit from a cross listing when there are growth options that are significantly valuable (Doidge, 2010). If there is no more need for external capital funding, and the growth opportunities are weak, insiders do not benefit from a cross-listing. Due to rule 12h-6 it is easier to delist. This increase in the probability to delist gives insiders the opportunity to exploit private benefits more easily when they occur. The expectation is that minority shareholders signal delisting, in combination with an increase in insider ownership, as a method to exploit private benefits (Doidge, 2010). This leads to the expectation that minority shareholders will leave the company and that, in turn, leads to negative price reaction. The hypothesis following these expectations is then:
H4: “An increase in insider ownership after the delisting of an ADR causes a negative price effect, since the introduction of rule 12h-6.”
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Another aspect that is examined is the relationship between firm size and the after delisting performance. In current literature there is no consensus on the influence of firm size. Yang(2013) states that the larger the firm, the more negative the performance is after the delisting. This is because larger firms can handle the requirement costs of a cross-listing better, and therefore, the expectation is that a larger firm only delists if this is really necessary. As a proxy for firm size
Yang(2013) takes the average value of total assets in a given period. This is contrary to Doidge(2010), which states that size has no impact on delisting performance, examined shortly after the
introduction of rule 12h-6. This is because under rule 12h-6, size is no longer a determinant of delisting. The expectation for this thesis is that firm size does not influence the after delisting performance. Markets respond to the increased probability to delist for all firms, and the lowered delisting requirements. Hence, the expectation is that firm size does not influence after delisting performance. This leads to the following hypothesis:
H5: “Performance is not significantly influenced by the size of the firm, at the announcement or after the delisting of an ADR, since the introduction of rule 12h-6.”
The combination of results of these hypotheses form the foundation in answering the main research question of this thesis.
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IV.
Methodology
In order to determine what the effect is of delisting an ADR on the underlying stock are, and to make a contribution to the existing literature, a methodology is set out. In the existing literature on this topic, there is a clear consensus in methodology. Kim(2000), Jayaraman(1993), Miller(1999), Foerster(1999) and You(2012) all use an event study methodology to calculate the effects on the stock return after a listing or delisting. With the combination of these papers and the acknowledged paper on event studies of Lyon(1999) and MacKinlay(1997), the methodology is defined. The
combination of methods, described in the methodology part, give an answer on the main research of this thesis.
The data that is necessary for testing hypothesis one of this research are; a list of companies that processed the delisting of an ADR, the delisting announcement dates of these companies, their stock prices and the stock prices on the home markets where the underlying stock is active in. All this data is found in DataStream international or in the Wharton Research Data Services(WRDS) center. To begin with all data is collected of firms with an ADR listing in WRDS. This dataset is corrected for the firms that performed a delisting in the chosen time period. This dataset is then separated between involuntary and voluntary delisting’s. The data set of the voluntary delisting’s of an ADR in the period since the introduction of rule 12h-6, forms the sample for this thesis. With DataStream international are all stock prices of the firms and the home market index collected. With this total sample all calculations are performed. The effect is measured with the formulas of abnormal returns, pointed out in Liu(2005), You(2012), Yang(2013) and Lyon (1999). These formulas are the following:
𝐴𝑅𝑖,𝑡= 𝑅𝑖,𝑡− 𝐸(𝑅𝑖,𝑡)
𝐴𝑅𝑖,𝑡 = 𝑅𝑖,𝑡− 𝛼𝑖− 𝛽𝑖∗ 𝑅𝑏,𝑡
𝐶𝐴𝑅𝑖,𝑡 = ∑ 𝐴𝑅𝑖,𝑡
In this formula “i” represents the security and “t” the timespan of the return. The benchmark group is represented by the other stocks that are active in the firms main home stock exchange. For the research, various different timespans are used. The most recent papers on ADR delisting’s use a time span of (-3,3) and (-20,20) around the announcement of the delisting. For the long term, a one year stretch is taken. This is similar to Liu(2005), You(2012) and Lyon(1999), that all use a one year period to examine to long term effect: {1-250}. This thesis uses an abnormal return for the measurement of the long term, in contrast with the buy and hold used in MacKinlay(1997). The timeframe that is used to create the sample of this research are delisting’s from March 2007 till September 2013.
~ 15 ~
This time frame is chosen because it is a time period which has not been examined before and captures fully the current situation of rule 12h-6. Delisting’s more recent then September 2013 were, at time of this research, not possible due to the long term effect that has to be studied in the period after the delisting takes place. The returns in the timeframes are, among others, corrected for stock splits and dividends. A summary off the sample with the delisting’s dates, their underlying country, and the type of ADR are presented in table A3, located in the appendix.
After all the abnormal returns are calculated for each time period, the differences are compared and analyzed. To analyze the significant impact of the results of hypothesis’s, a test is conducted. The t-test exists of the following formula:
𝑡 = 𝐴𝑅 𝜎(𝐴𝑅)
√𝑛 ⁄
In the case the absolute value of the “t” value is higher than 1,96, the result are significant at a five percent significance level. The results of any t-tests are located in the appendix.
Hypothesis two, concerning the liquidity effect, is measured by the trading volume liquidity formula, as You(2012) uses. The data that is necessary to measure this liquidity ratio are: the shares traded per day, and the shares outstanding. The liquidity data is retrieved from DataStream International. The differences in liquidity levels tested for their significance with the t-test. The change in liquidity is measured with a before period. This period contains data from {-250,-60} prior to the event. A gap of 60 days between the announcement date is taken to control for speculations. The formula for calculating the liquidity from You(2012) is as follows:
𝑇𝑟𝑎𝑑𝑖𝑛𝑔 𝑣𝑜𝑙𝑢𝑚𝑒 𝑙𝑖𝑞𝑢𝑖𝑑𝑖𝑡𝑦 = 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑆ℎ𝑎𝑟𝑒𝑠 𝑡𝑟𝑎𝑑𝑒𝑑 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑆ℎ𝑎𝑟𝑒𝑠 𝑜𝑢𝑡𝑠𝑡𝑎𝑛𝑑𝑖𝑛𝑔
Hypothesis three, concerning the governance structure, uses data from Fernandes(2010). This article examines the influence of home market governance structure around the time of the introduction of rule 12h-6. Fernandes(2010) examines the governance structure based on the disclosure
measurements set by Porta(2006). In this article the governance levels are calculated based on a set of disclosure measurements, together with other accountancy policy rules. This research uses the same measured disclosure numbers as used by Fernandes(2010). The disclosure requirements taken from Fernandes(2010) represent the different levels of investor protection around the world. A larger disclosure requirement implies a higher investor protection level. The disclosure
~ 16 ~
The total regression formula is then tested to determine what the influences and relationships are of home investor protection levels on stock returns, after the delisting of an ADR, and since the
introduction of rule 12h-6.
Hypothesis four examines the ownership structure. The case of insider ownership is interesting because insiders benefit from cross-listing and, therefore, also can benefit from delisting (Doidge, 2010). Insider ownership is described in Doidge(2010) as the shares held by corporate insiders. With the “Closely held shares” databases of DataStream international, the proxy for ownership is created. In a regression formula, as done in Doidge(2010), the change and influence of inside ownership after the delisting is calculated. With this methodology, the relationship between inside ownership and stock returns is defined in the period after the delisting of an ADR. The results follow from the regression.
Hypothesis five examines the influence of firm size on delisting performance. From DataStream international the data of average market assets is collected for the sample in each timespan. The data of these firms are then added as a proxy to the total regression formula, as done in similar research of Yang(2013). With the regression formula and the t-test of significance, a judgment is made concerning the influence of firm size on after delisting performance.
The regression formula of this thesis is formed by four proxies and several control variables. The four main proxies are related to the five hypotheses described in part III of this thesis. Namely return, liquidity, governance, ownership, and size. As done in the similar researches of Doidge(2010), Daugherty(2011), and Yang(2013), the regression controls for external consequences. The control variables are: type of ADR, time, and industry effects. The type of ADR is added in order to examine any possible difference in types. Time is a necessary proxy because we want to examine to the consequences of the long term effect of rule 12h-6. With time as a dummy the growth pattern of the effects of rule 12h-6 is studied. Industry effects are taken into account because in Foerster(1993), it was proven that firms from different industries exert different premiums. The dummies ADR type 1, year 2012 and industry health are eliminated in the regression. This is to control for omitted variable bias. The total regression formula is presented directly below:
𝐶𝐴𝑅𝑖,𝑡= 𝛼 + 𝛽1𝐿𝐼𝑄𝑖,𝑡+ 𝛽2𝐺𝑂𝑉 + 𝛽3𝑂𝑤𝑛𝑒𝑟𝑠ℎ𝑖𝑝𝑖,𝑡+ 𝛽4𝑆𝑖𝑧𝑒𝑖,𝑡+ 𝛽5𝑇𝑦𝑝𝑒2 + 𝛽6𝑇𝑦𝑝𝑒3 +
𝛽7𝑇2007+ 𝛽8𝑇2008+ 𝛽9 𝑇2009+ 𝛽10𝑇2010+ 𝛽11𝑇2011+ 𝛽12𝑇2013+ 𝛽13𝐼𝑐𝑜𝑛+ 𝛽14𝐼𝑐𝑜𝑚𝑚+
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V.
Results
In the time period of March 2007 till September 2013, 160 firms performed a delisting, as seen in the Wharton research data services(WRDS) database. The 160 firms represent a mix of all levels of ADRs. The firms come from 31 different countries and are listed on exchanges located on all continents. To capture the true effects on the movement of a stock after a delisting, the firms used for this research need to fulfill certain requirements. The requirements are; that firms conduct a voluntary delisting, and that the stock still exists one year after the delisting. The last requirement is necessary in order to calculate the long term effects of a delisting. These are the same requirements as in You(2012) and Doidge(2010). A total of 115 firms fulfilled the requirements. The other firms are eliminated because they did not meet the requirements for several different reasons. The most common reasons being; bankruptcy and merger activities. The sample contains mostly type II ADRs. The selected list of firms with their delisting dates, home country and ADR level is presented in table A3. In order to measure the effect of a delisting an event study is conducted, as described in the
methodology part. The data for the firms in this sample, that is required to conduct the event study, are retrieved from DataStream International. The timespan of the event studies are {-3,3}-{-20,20} and {1,250}, as explained in the methodology part of this thesis. A table with the abnormal returns for each timespan is presented in table 2, as shown directly below.
Table 2: Average Abnormal returns
The average abnormal returns for the periods,{-3,3}-{-20,20} and {1,250}. Attached is the
t-statistic, in order to determine if the values differ significantly from zero.
Average Abnormal returns
CAR(%) T-stat
{-3,3} -0.03 -0.04
{-20,20} -.8733 -0.43
{1,250} -1.50 -0.44
The three average abnormal returns as shown in table 2 give different results. All the three abnormal returns are negative. The negative effect increases in the long run in comparison with the periods {-3,3} and {-20,20} of around the event. Besides the fact that all values are negative, none of them are significant different from zero. This means that in none of the three time periods there is a significant negative effect.
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In the articles of Doidge(2010) and You(2012) it is described that before the rule 12h-6 was introduced, there was a negative effect around the announcement of the delisting. A total summarizing overview on the return data is presented in table A5, located in the appendix. To test hypothesis one of this thesis, the abnormal returns are tested for their significance. The abnormal returns in respectively the periods {-3,3}-{-20,20} and {1,250} are not significant with t-values of 0,04, 0,43, 0,44. On the basis of this research, there is no significant statistical evidence that a delisting causes a negative effect. Relating this to hypothesis one: “There is no negative return
effect on the home stock, at the announcement or after the delisting of an ADR, since the introduction of rule 12h-6”, It leads to the conclusion that there is no statistical evidence of a
negative return delisting effect. Therefore, hypothesis one is considered true.
Hypothesis two examines the liquidity effect with the hypothesis: “Trading volume liquidity does not
decrease significantly, at the announcement or after the delisting of an ADR, since the introduction of rule 12h-6.” In table 3, presented directly below, a summarizing table of the liquidity effect is
presented, for respectively each time period.
Table 3: Summarize Liquidity effect
Summarizing table for the liquidity values in the home market for each time span. With the
number of firms, mean liquidity level, the average standard deviation, the minimum value,
and the maximum value.
Liquidity effect
N Mean Std. dev Min Max
LIQ {-3,3} 115 .6369347 1.294297 0 10.88332
LIQ {-20,20} 115 .6113994 .904722 0 7.319736
LIQ {1,250} 115 .2041877 3.791219 -39.04251 8.606651
LIQ before 115 .5628401 .5797115 .0007088 4.350298
Table 3 shows that the liquidity levels in the home market drop in the after period, in comparison with the before period. The difference is -0,36% between the before and the after period. This indicates a decrease in liquidity in the period after a delisting. In the periods around the
announcement the liquidity levels are somewhat higher, in comparison with the before period. The values are respectively 0.63% and 0.61%. The results of the significance tests of hypothesis two are presented in table A6, A7 and A8 located in the appendix. In table A6 the significance between the before period and the period {-3,3} is tested. With an absolute t-value of 0,87 there is no significant difference at the five percent significance level.
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In table A7 the significance between the before period and {-20,20} period is tested. With an absolute t-value of 1,03, there no significant difference at the five percentage significance level. In table A8, it is presented that the liquidity turnover indeed declines in the period after the delisting {1,250}. The remark is that with an absolute t-statistic of 1,02 it is not significant at the five
percentage level, see table A8.
These results lead to the conclusion that, although there is a signal that indicates a decline in turnover after the delisting, this thesis cannot give significant evidence for this theory. There is no statistical evidence that states that hypothesis two is incorrect, and, therefore, hypothesis two is considered correct. This is in contrast with the article of You(2012), that found evidence for negative liquidity effect after a delisting.
Hypothesis three, four and five are tested by the total regression formulas presented in table A9, A10 and A11, located in the appendix. The total regression formulas for the three periods have abnormal return as the dependent variable. The independent variables are liquidity, governance level, ownership, and firm size. In combination with the dummies of ADR type, year and industry a regression is made with an as large as possible fit. The regressions in table A9 till A11 have a fit varying from 15 till 30%. This means that a clear judgment is made based on these regressions, but there is still a large part of the movement that cannot be explained. The increase in fit of the model is based on economic theory and must not suffer from biases. Therefore, some multicollinearity tests are performed to control for this. The outcome of these tests are shown in the part of the Robustness Checks, located directly after the appendix on page 33.
To test hypotheses three the calculations of the total regression formula of table A9 till A11 are used. Hypothesis three states: “Returns are not related to the level of governance structure in the
home country, at the announcement or after of the delisting of an ADR, since the introduction of rule 12h-6.” If this hypothesis is connected to the results in tables, the following conclusion is formed. In
the period {-3,3} the relationship between return and governance is close to zero with a t-statistic of 0,04. In the periods {-20,20} and {1,250} it shows a negative return. This means that the higher the level of investor protection in the home country, the more negative the return after the delisting. The remark here is that this result is not significant at the five percentage level, with an absolute t-value of 1,80 in the period {1,250}. In the period {-20,20} the t-value also isn’t significant with an absolute t-value of 1,56. Therefore, there is no evidence found that the return is dependent on governance structure. Hence, there is no proof that governance levels in the home country are related to performance at the announcement of the delisting, or in the period after.
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The result coincides with what is stated in hypothesis three, therefore it is considered true. This in contrast of prior research of Doidge(2010).
Hypothesis four states: “An increase in insider ownership after the delisting of an ADR causes a
negative price effect, since the introduction of rule 12h-6.” The regression formula in table A11, is
used to clarify this hypothesis. The results of the regression formula indicate that a percentage increase in insider ownership causes a positive return for the firm in the period after the delisting. This result is not significant at the five percentage level, with an absolute t-value of 1,37. This result is in contrast with the expectation of this research. As seen in the part-three of this thesis, a negative price effect is expected. There is no economic theory that can support these results. Future research should explore if the results of this thesis are a lasting phenomenon or how these results can be explained. With the results of table A11 the provisional conclusion is made that hypothesis four is false.
Hypothesis five states: “Performance is not significantly influenced by the size of the firm, at the
announcement or after the delisting of an ADR, since the introduction of rule 12h-6.” In tables A9 till
A11 the results are presented. The periods around the announcement show that the larger the size of the firm, the relatively more negative the effect is. The remark is that the results are not
significant with absolute t-values of 0,33 and 0,37. In the period after the delisting {1,250} it shows that the relatively larger the firm, the better the performance.This result is on the other hand also not significant with an absolute t-value of 1,07. One can thus conclude, based on this research, that there is no statistical evidence that firm size influences performance in the period after a delisting. Therefore, hypothesis five is considered true. This is in line with Doidge(2010).
The conclusions that follow from the results of the five hypotheses, form the foundation in
answering the central research question of this thesis. The summary and discussion of these results and the thesis as a whole are discussed in the next part.
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VI.
Conclusion & Discussion
The research of this thesis examines what the consequences are of delisting an ADR at the announcement and in the long run, since the introduction of rule 12h-6. To create a result for the main research of this thesis, the current literature is defined. Table 1 represents an overview from the literature review of the existing knowledge on the delisting’s of ADRs. Before the introduction of rule 12h-6, the world of delisting’s was formed by the introduction of SOX and the changing
environment of raising capital, Sarbanes(2002) and Marosi(2008). Rule 12h-6 changed this by making it easier to delist from the tight SEC regulations (Doidge, 2010). To answer the research question and to define the current status of delisting’s, five hypotheses are defined. The results of these
hypotheses come from event studies and regressions, as done in similar prior research of You(2012) and Doidge(2010). The results of these hypotheses form the foundation of this thesis.
The first hypothesis describes the effect of the return on the stock in the home market. It is expected by this hypothesis that there is no negative return at the announcement of, or after the delisting, since rule 12h-6. This expectation is based on the theories found in the literature review. In
particular, the articles of You(2012) and Doidge(2010). Based on the findings of the event study that is presented in table 2, hypothesis one is considered to be true. This means that, based on this research, there is no statistical evidence for a negative return effect, since the introduction of rule 12h-6. The second hypothesis, concerning the liquidity turnover, states that the expectation is that there is no significant decrease in the level of liquidity, at the announcement of, or after a delisting. Although tables A6, A7 and A8 show volatilities, these results are not significant. Therefore, it is considered that since the introduction of rule 12h-6 the liquidity level does not decrease significantly around or after a delisting. Hypothesis three states that the return, at the announcement of, or after a delisting, is not related to the level of governance structure in the home country. With the
regression that is presented in tables A9,A10 and A11 the conclusion arises that the returns after the delisting are not related to the level of governance structure. Based on the regressions conducted in this thesis there is no proof that states otherwise. Hypothesis four states that a potential increase in the level of insider ownership causes a significant negative decrease in terms of return. The results of the regression in table A11 show different results. There is no economic theory to support these results. But for now, hypothesis four is considered false. Hypothesis five examines the relationship between firm size and the after delisting performance. The results of this hypothesis are presented in table A9, A10 and A11. There is no statistical evidence for a significant relationship. Therefore, it is considered that the after delisting performance is not affected by firm size. So hypothesis five is considered true.
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To answer the research question, the findings of the results of the various hypotheses are combined. The effects of the delisting of an ADR on the stock in the home market, since the introduction of the rule 12h-6 are the following. There is no statistical evidence that there is a negative effect in terms of decreasing returns with a delisting of an ADR. There is also no statistical evidence that the level of liquidity significantly decreases with a delisting. These results are in contrast with prior research of You(2012) and Doidge(2010). The consequences of rule 12h-6 that make it easier to delist causes this shift in return and liquidity effects, in contrast with the prior research .The delisting
performance is not influenced by the level governance of the home country. This was the case since the introduction of SOX, as explained in Doidge(2010). The change in delisting probability that is associated with the introduction of rule 12h-6 influences the topic of insider ownership as well. The economic theory does not support the results of this thesis that there is no relationship between inside ownership and performance. Future research should this explore more extensively. Firm size and after delisting performance are also not related based on this research. This is in line with Doidge(2010).
If the above results are connected to the main research question, the regression results presented in table A9, A10 and A11 form the foundation of this thesis. Firms that are planning the delisting of an ADR can use these tables to capture the possible effects of the delisting of an ADR. In these tables, the main consequences are shown and this could help firms in the decisions making process. The remark is still that a large part of the movements is unclear and inexplicable. More extensive research should further investigate the situation from this point. New research must show how the situation of delisting’s since the introduction of rule 12h-6 develops. Future research should
specifically investigate if the results of this thesis form a lasting phenomenon. Markets can adapt to these changes and future research should indicate if the findings of this thesis are permanent, in the constantly changing environment of cross-(de)listing.
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APPENDIX:
Table A1: Total deregistration across the years. “Marosi(2008).”
The amount of delisting’s of ADRs for each time span since the 1990s and the percentage of delisted firms in comparison with the total active ADRs in that time span.
Number of foreign deregistration’s
Total deregistration Deregistration/Active(%).
2006 29 3.76 2005 32 3.91 2004 28 3.40 2003 19 2.33 2002 18 2.09 2001 5 0.55 2000 7 0.75 1990-1999 10 1.17
Table A2: Types of ADRs. “Foerster(1999)”
For each of the four levels of ADR are the requirements for a cross-listing and the index of trading presented.
No Capital raising
Capital raising
ADR type:
LEVEL I ADR
LEVEL II ADR
Level III ADR
Rule144A
Description
Unlisted Listed on majorUS exchange
Offered & listed on major US exchange
Private US
placement to QIBs
Trading
OTC: pink sheettrading NYSE, AMEX, NASDAQ NYSE, AMEX, NASDAQ US private placement market / PORTAL
SEC-registration
Registration statement form F-6 Registration statement form F-6 Forms F-1 and F-6 for an IPO NONEUS reporting
requirements
Exempt under Rule 12g3-2(b) Form 20-F filed annually Form 20-F filed annually; forms F-2 & F-3 for SEOsExempt under Rule 12g3-2(b)
GAAP
requirements
No GAAP reconciliation requiredOnly partial GAAP reconciliation for financials Full GAAP reconciliation for financials No GAAP reconciliation required
~ 24 ~
Table A3: Delisting date and home country.
For each of the 115 firms contained in the sample of this thesis are the delisting date, home country and type of ADR presented.
Tickercode Name Firm Delisting
date
Home Country Type of ADR.
AAUKY ANGLO AMERICAN PLC 31-Jul-09 England 2
BAYRY BAYER AG 26-Sep-07 Germany 2
REXMY REXAM PLC 20-Nov-07 England 1
DAIEY DAIEI INC 08-Jan-09 Japan 1
FUJIY FUJIFILM HLDGS CORP 31-Jul-09 Japan 2
HGVLY EVRAZ HIGHVELD STEEL AND VAN 31-Jul-09 South Africa 1
MKTAY MAKITA CORP 19-Apr-13 Japan 2
PCRFY PANASONIC CORP 19-Apr-13 Japan 1
MITSY MITSUI & CO LTD 21-Apr-11 Japan 1
NIPNY NEC CORP 26-Sep-07 Japan 1
NSANY NISSAN MOTOR CO LTD 31-Jul-09 Japan 1
KUBTY KUBOTA CORP 15-Jul-13 Japan 1
ESV ENSCO PLC 22-Dec-09 England 2
HTHIY HITACHI LTD 26-Apr-12 Japan 2
TTDKY TDK CORP 24-Apr-09 Japan 2
TRIN. THOMSON REUTERS PLC 10-Sep-09 Canada 2
SSLTY SANTOS LTD 30-Jul-09 Australia 2
NHYDY NORSK HYDRO ASA 21-Nov-07 Norway 2
ELEYY ENDESA SA 06-Dec-07 Spain 1
NABZY NATIONAL AUSTRALIA BK 15-Jun-07 Australia 2
FIATY FIAT SPA 22-Aug-07 Italy 2
BNGPY BENETTON GROUP SPA 18-Oct-07 Italy 2
REPYY REPSOL SA 04-Mar-11 Spain 2
AKZOY AKZO NOBEL NV 24-Aug-07 Netherlands 2
TKOMY TOKIO MARINE HOLDINGS INC 25-Jul-07 Japan 2
AIBYY ALLIED IRISH BANKS 25-Aug-11 Ireland 2
AHONY KONINKLIJKE AHOLD NV 19-Sep-07 Netherlands 2
NZTCY TELECOM CORP OF N. ZEALAND 09-Jul-12 New Zealand 2
OBT ORBITAL CORP LTD 06-Dec-13 Australia 2
VITRY VITRO SAB DE CV 21-Aug-09 Mexico 2
VNLPY VERNALIS PLC 03-May-07 England 2
BCAHY BRILLIANCE CHINA AUTOMOTIVE 25-Jul-07 China 2
DANKY DANKA BUSINESS SYSTEMS PLC 14-Dec-07 England 2
AMCRY AMCOR LTD 13-Jun-07 Australia 2
FMDAY FUTUREMEDIA PLC 28-Feb-08 England 2
ARCAY ARCADIS NV 07-Jun-07 Netherlands 2
ANZBY ANZ-AUSTRALIA & NEW ZEALD BK 11-Jul-07 Australia 2
BSYBY BRITISH SKY BROADCASTING GR 19-May-10 England 2
~ 25 ~
WACLY WACOAL HOLDINGS CORP 12-Apr-13 Japan 2
KKPNY KONINKLIJKE KPN NV 03-Apr-08 Netherlands 3
KORIY KOOR INDUSTRIES LTD 15-Jun-07 Israel 2
SNSAY STOLT NIELSEN LTD 21-May-07 Norway 2
MXCYY METSO OYJ 14-Sep-07 Finland 2
MXICY MACRONIX INTL CO LTD 26-Oct-07 Taiwan 2
AISLY ASIA SATELLITE TELECOM LTD 25-Jan-08 Hong Kong 2
AXAHY AXA 25-Mar-10 France 2
SGGGY SGL CARBON SE 22-Jun-07 Germany 2
DASTY DASSAULT SYSTEMS SA 15-Oct-08 France 2
PVTCY PFEIFFER VACUUM TECHNOLOG 03-Oct-07 Germany 2
APCFY ATLAS PEARLS & PERFUMES LTD 20-Jul-07 Australia 1
SCRYY SCOR SE 13-Jun-07 France 2
DTEGY DEUTSCHE TELEKOM 18-Jun-10 Germany 3
APPTY APT SATELLITE HLDGS LTD 06-Aug-08 Hong Kong 2
EDPFY EDP ENERGIAS DE PORTUGAL SA 07-Jun-07 Portugal 3
EURO. EUROTRUST 29-May-07 England 2
EONGY E.ON SE 07-Sep-07 Germany 2
DANOY DANONE 03-Jul-07 France 2
MYTAY MAGYAR TELEKOM 11-Nov-10 Hungary 2
UUGRY UNITED UTILITIES GROUP PLC 22-Jun-07 England 2
RHAYY RHODIA 27-Sep-07 France 2
PNLYY POSTNL NV 15-Jun-07 Netherlands 2
SUBCY SUBSEA 7 SA 07-Mar-11 Norway 2
SKYEY SKYEPHARMA PLC 11-May-07 England 2
BZLFY BUNZL PLC 01-Jun-07 England 2
SCMWY SWISSCOM AG 30-Aug-07 Swiss 2
DDAIF DAIMLER AG 04-Jun-10 Germany 2
HLTOY OTE - HELLENIC TELECOM ORG 17-Sep-10 Greece 2
ITYBY IMPERIAL TOBACCO GROUP PLC 11-Sep-08 England 2
SPP SAPPI LTD 27-Sep-13 South Africa 2
DMHYY DUCATI MOTOR HOLDING SPA 13-Jun-07 Italy 2
TMICY TREND MICRO INC 30-May-07 Japan 2
EPCYY EPCOS AG 29-Nov-07 Germany 2
ENLAY ENEL SPA 19-Dec-07 Italy 2
TCLRY TECHNICOLOR SA 21-Mar-11 France 2
ICABY I-CABLE COMMUNICATIONS LTD 07-Jun-07 Hong Kong 2
MRAEY MIRAE CORP 25-Apr-08 Korea 3
STTSY. STATS CHIPPAC LTD 28-Dec-07 Singapore 3
IFNNY INFINEON TECHNOLOGIES AG 23-Apr-09 Germany 3
HANAY SK BROADBAND CO LTD 27-Jun-07 Korea 2
BASFY BASF SE 05-Sep-07 Germany 2
CSBHY CIBA HOLDING AG 19-Jul-07 Swiss 2
~ 26 ~
TTCMY TATA COMMUNICATIONS LTD 07-Jun-13 India 2
PUBGY PUBLICIS GROUPE SA 26-Sep-07 France 2
SEOAY STORA ENSO OYJ 28-Dec-07 Finland 2
HEDYY HEAD NV 28-Mar-08 Austria 3
AZSEY ALLIANZ SE 23-Oct-09 Germany 2
TKAGY TELEKOM AUSTRIA AG 16-May-07 Austria 3
TELNY TELENOR ASA 08-Jun-07 Norway 3
SAYCY SATYAM COMPUTER SERVICES 13-Oct-10 India 3
WOSYY WOLSELEY PLC 28-Dec-07 England 2
LFRGY LAFARGE SA 21-Sep-07 France 2
SPMYY SPIRENT COMMUNICATIONS 13-Jun-07 England 2
SZEZY SUEZ 19-Sep-07 France 2
MTENY MAHANAGAR TEL. NIGAM 31-Dec-12 India 2
TKPPY TECHNIP SA 15-Aug-07 France 2
VDMHY VAN DER MOOLEN NV 05-Dec-07 Netherlands 2
MTSXY METAL STORM LTD 25-Jul-08 Australia 2
TRMD TORM AS 19-Jul-13 Denmark 2
SDXAY SODEXO 13-Jul-07 France 2
AAAGY ALTANA AG 18-May-07 Germany 2
NISGY NIS GROUP CO LTD 01-Aug-08 Japan 3
NPSNY NASPERS LTD 07-Jun-07 South Africa 2
UPMKY UPM-KYMMENE CORP 05-Dec-07 Finland 2
TLKGY TELKOM SA SOC LTD 26-Aug-09 South Africa 3
AFLYY AIR FRANCE - KLM 06-Feb-08 France 2
MLGGY MELDEX INTL PLC 15-Jun-07 England 1
PGSVY PGS-PETROLEUM GEO-SERVICES 19-Jul-07 Norway 2
CXSPY CHEMGENEX PHARMACEUTICALS 08-Jul-09 Australia 2
CMEDQ CHINA MEDICAL TECHNOLGIES 06-Feb-12 Hong kong 2
PXSLY PHARMAXIS LTD 22-Jul-09 Australia 3
EVTCY EVOTEC AG 27-Nov-09 Germany 1
CMMCY CHINA MASS MEDIA CORP 16-Mar-12 China 2
~ 27 ~
T
able A4: Summary sample delisting’s of time, disclosure and country characteristics.
All 115 firms from the sample of this thesis, divided for their home country and year of delisting. For each country the disclosure levels are presented, as seen in Fernandes(2010).Disclosure 2007 2008 2009 2010 2011 2012 2013 Total Australia 0.75 4 1 3 1 9 Austria 0.25 1 1 2 Canada 0.92 1 1 China 0.83 1 1 2 Denmark 0.58 1 1 England 0.83 10 2 2 1 15 Finland 0.5 3 3 France 0.75 8 2 1 1 12 Germany 0.42 7 3 2 12 Greece 0.33 1 1 Hong Kong 0.92 2 2 1 5 Hungary 0.43 1 1 India 0.92 1 1 1 3 Ireland 0.67 1 1 Israel 0.67 1 1 Italy 0.67 4 4 Japan 0.75 3 1 4 1 1 4 14 Korea 0.75 1 1 2 Mexico 0.58 1 1 Netherlands 0.5 5 1 6 N. Zealand 0.67 1 1 Norway 0.58 4 1 5 Portugal 0.42 1 1 Singapore 1 1 1 South Africa 0.83 1 2 1 4 Spain 0.5 1 1 2 Sweden 0.58 1 1 Swiss 0.67 3 3 Taiwan 0.75 1 1 Total 63 11 16 7 5 5 8 115
