Do Cross-border Mergers and Acquisitions Import Insider Trading?

Transcription

1 Do Mergers and Acquisitions Import Insider Trading? Lixiong Guo and Han Lin Australian School of Business University of New South Wales June 8, 2014 Abstract Using a sample of 5,000 M&A transactions targeting U.S. public firms between 2002 and 2011, we find evidence of significantly higher level of informed trading prior to deal announcements in cross-border deals than in domestic deals (i.e. deals involving only U.S. acquirers). The informed trading takes place in both stock and options markets for up to 180 days before the deal announcements. Informed option trading is concentrated in out-of-the-money options with strike prices in the vicinity of the to-be-announced deal prices. Furthermore, we find that the higher level of informed trading in cross-border deals is mainly driven by acquirers from countries with low regulatory quality as measured by the World Bank index. Our evidence suggests that cross-border M&As can potentially negatively affect the integrity of the U.S. financial markets and raises an important question for regulators to address in the new era of globalization. Keywords: mergers and acquisitions, Insider trading, information leakage; Country level governance, Investor protection JEL Classification: G34, G38 1

2 1. Introduction With globalization, the number and volume of cross-border mergers and acquisitions have increased significantly over the past decades. mergers and acquisitions accounted for 23% of the world s total M&A volume in 1998 but 45% in 2007 (Erel et al, 2012). This is followed by another 56% increase in volume from 2008 to 2013 (Grant Thornton 2013). A large number of prior literature finds these deals lead to improvements in corporate governance in firms in countries with weak law enforcement and poor investor protection regardless of the direction of the acquisitions (Bris and Cabolis, 2007; Brisk, Brieley, and Cabolis, 2008; Martynova and Renneboog, 2008). However, little is known about how these deals may affect firms and financial markets in countries with strong law enforcement and good investor protection. 1 One important question is how these cross-border deals may affect insider trading before deal announcements in financial markets in countries with strong governance. This has become a pressing issue as more and more firms from countries with weak governance are acquiring firms in countries with strong governance. It is well known that M&A deal announcements offer a great opportunity for people with inside information to earn enormous returns. In countries with strong governance, these activities by insiders are largely kept under control by strict enforcement of insider trading laws when the deal is between two domestic firms. However, in a cross-border deal, some insiders reside in another country. On one hand, the integration of financial markets across countries and the development in communication technology makes it possible for them to trade on the information in financial markets internationally or pass this 1 To be concise, hereafter, we refer to country-level strong law enforcement and good investor protection as strong governance and country-level weak law enforcement and poor investor protection as weak governance. 2

3 information to people who are located overseas to trade on it. On the other hand, the separation of legal systems makes it difficult for regulators in one country to investigate the case and enforce the law when insiders reside in another country. This is especially true when the foreign country itself has a record of weak law enforcement and poor investor protection. In this paper, we examine empirically how this divergence of legal and economic integration could create strong incentives for insiders in cross-border deals to trade on the information or leak the information to others to trade prior to the deals announcements and thus lead to a negative corporate governance spillover between the two countries involved 2. Unlike in domestic deals, insider trading in cross-border deals could involve direct trading by insiders from one country on the other country s exchanges or leakage of material information by insiders from one country to a party residing in either the acquirer s country or the target s country who then trade on the other country s exchange. For example, insiders from the acquirer s country could buy shares of the target firm on the stock exchange of the target s country before the deal announcement and sell the shares afterwards to profit from their information advantage. They could also pass the information on to others, including people who reside in the target s country, who can then trade on the target country s exchange to profit in the same way. The regulators in the country where the illegal trading takes place usually have the legal authority to investigate the case and prosecute the violators but they may find it difficult to do so when the inside traders reside in a foreign country or when the insiders who leak the information reside in a foreign country. In the U.S. government s case against the founder of the Galleon 2 We use the term insider to refer to anyone who has inside information about the deal and trade on the information. They do not have to be employees of the acquirers or target firms. 3

4 Group hedge fund, Raj Rajaratnam, for directing the most extensive insider-trading scheme in the U.S. history, prosecutors used writetaps to obtain more than 1,000 recorded calls that implicate the defendant. Obviously, such evidence would be very difficult, if not impossible, to obtain if the insiders who conduct the trades or pass the information on to others reside in a foreign country. Cooperation from foreign authorities is often needed but, depending on the law enforcement and investor protection in the country where the insiders reside in, such cooperation may not always be available and sometimes can be difficult to obtain. Such barriers of law enforcement could create additional incentives to insiders to trade on their information or leak information to others to trade prior to the announcements of cross-border deals if they perceive that it is unlikely for them to get caught if they trade on the other country s exchanges. This situation can be exacerbated when these insiders who trade or leak information come from countries with poorer law enforcement and investor protection. First, these insiders may be used to an environment of lax regulation and law enforcement in their home country. Thus they are less scrupulous in trading on material non-public information or passing the information on to others who may then trade on the information. Second, they may be unfamiliar with the insider trading laws in countries with better investor protection and may develop a false sense of immunity when directly or indirectly trading on the financial markets of countries with stricter enforcement of insider trading laws. The lack of prior insider trading cases launched against foreigners may also contribute to their false sense of immunity. Third, the poorer law enforcement and investor protection in their home country can make it more difficult for foreign regulators to investigate the insider trading cases and bring them to justice because cooperation from local law enforcement may be more difficult to obtain and evidence is more difficult to collect than 4

5 in countries with better law enforcement and investor protection. These arguments motivate our two main hypotheses that, in the context of acquiring U.S. firms, (1) the level of insider trading in the target firm stocks and options should be higher when the acquirer is a non-u.s. firm (cross-border deals) than when the acquirer is a U.S. firm (domestic deal); and (2) this effect should be stronger when the non-u.s. acquirer is from a country with poorer law enforcement and investor protection. We focus on insider trading in target firms stocks and options because, although insiders may use simple or more complicated strategies to trade, such trades typically involve buying the target firms stocks or options or both before the deal announcements. We decide to focus on deals that target U.S. firms because the U.S. is considered to the country with the most stringent enforcement of insider trading laws and offering the best investor protection. Its financial markets are also the most developed in the world and have the most complex and stringent regulations. As a result, insider trading is likely to be very limited and idiosyncratic prior to deals between U.S. firms because insiders from both the acquiring and target firms have similar knowledge about the insider trading laws in the U.S. and are subject to the same stringent scrutiny by the SEC and other regulators. This that domestic deals in the U.S. provide a clean benchmark for us to identify the effect of cross-border deals on insider trading in target firms securities, whereas in weak-governance countries insider trading prior to M&A deals is likely to be quite prevalent even for domestic deals and hence the incremental effect of cross-border deals could be small and relatively difficult to detect. Using only U.S. target firms also affords another benefit. That is, it helps us to better isolate the source of the insider trading and direction of the corporate governance spillover. This is because insiders in U.S. target 5

6 firms are subject to strict U.S. insider trading laws and stringent disclosure requirements on their trades in their own firms stocks. Hence, we expect insider trading in target firms securities on the U.S. markets to be mainly driven by information from insiders from the foreign acquirers in our sample. The issue we examine is well exemplified by the recent insider trading case associated with the $28 billion takeover of the American food processing giant, H.J. Heinz Company, by a consortium headed by Berkshire Hathaway and Brazilian private equity firm, 3G Capital in On February 13, 2013, one day before the deal announcement, the U.S. Securities and Exchange Commission (SEC) noticed highly suspicious purchases of Heinz s out-of-money options, which resulted in nearly 2,000% increase in value after the news was incorporated into Heinz s stock price. Because the trades were conducted through a Swiss brokerage account, the SEC had to get an emergency court order to freeze the account and wait for the people behind the account to claim the ownership. The case was eventually settled eight months later with two Brazilian brothers paying $5 million without admitting or denying the charge. The source of the information is still unknown. Interestingly, the Brazilian private equity firm, 3G Capital, is associated with another SEC insider-trading probe prior to its buyout of Berge King in Although we have no way to know if 3G Capital is the source of the inside information, this anecdote evidence does have many elements that fit our description of the potential relation between cross-border deals and insider trading prior to deal announcements. In the present study, we examine the systematic differences in the pre-announcement levels of informed trading 3 in the target firms among four types of deals: 1) domestic M&As, 2) cross-border 3 Since the goal of our study is not to identify individual insider trading cases, to be conservative, we refer to suspicious insider trading activity identified in our sample as informed trading. 6

7 M&As as a whole, 3) cross-border M&As involving acquirers with strong country-level governance, and 4) cross-border M&As involving acquirers with weak country-level governance. In general, it is difficult to identify individual cases of insider trading from the price and volume data or transaction data alone except in a few extreme cases, because informed traders would try to hide in the crowd by spreading out their trades over different markets and days. However, when all informed trades are examined as a whole, we should be able to statistically identify some abnormal price and volume patterns that are consistent with informed trading. Hence, rather than attempt to detect each individual insider trading case, our goal is to infer informed trading from systematic patterns of observed price and volume data on target firms stocks and options at an aggregate level. We develop the following strategies to test our hypotheses. Firstly, we make cross-sectional comparisons of the levels of informed trading between different types of deals to test if such level is systematically higher in a type of deals. Secondly, for each type of deals we select an estimation or a benchmark period that is considerably uncontaminated by the M&A announcement events, and compare if the increase in the level of informed trading during the event period is systematically higher in one of the deal types. Thirdly, we construct event windows with extending beginning dates to document the cumulative levels of informed trading for different window lengths for each of the above two tests, so we can have a big picture of overall which deal type experiences a higher level of informed trading. Lastly, we also construct segmented event windows with same lengths for each of the two tests to capture the patterns of the informed trading in each deal type. Utilizing a sample of 5,000 M&A announcements targeting U.S. public firms and five stock-based and option-based measures (1) stock cumulative abnormal returns, 2) informed option trading volume, 3) 7

8 scaled informed option trading volume, 4) implied volatility spread and 5) call-put volume imbalance) as proxies for informed trading, the present study makes the following findings. Firstly, we find that the level of informed trading is higher in cross-border compared to domestic M&A deals, supporting our expectation that the cross-border nature of an M&A creates law enforcement barriers to the target country s regulators that incentivises cross-border informed trading. Secondly, the higher level of informed trading in cross-border deals is mainly driven by weak-governance acquirers. This is also in line with our second main hypothesis that the poorer regulatory quality in the acquirer county further encourages such cross-border informed trading activity. Thirdly, we find no significant difference in the levels of information leakage between domestic deals and cross-border deals with strong-governance acquirers. We explain this insignificant difference as the net effect or offsetting effect between the better regulatory quality in the strong-governance acquirer countries that overall discourages insider trading, and the legal enforcement barrier created by the cross-border nature that encourages cross-border informed trading. Fourthly, within cross-border transactions, we find the level of informed trading to be higher in the ones where a weak-governance acquirer is involved. If we assume that the positive and negative corporate governance transfers brought by strong-and weak-governance acquirers are similar in magnitude, then this result would confirm our implication from the first finding that the cross-border nature does create a negative impact on the level of pre-announcement informed trading in an M&A deal. In addition, we also identify the general patterns of cross-border informed trading activity, which show that informed traders enter into the stock and options markets as early as 6 months prior to the initial M&A announcements. 8

9 Our study contributes to the existing literature in the following ways. Firstly, the current study is the first to study how the cross-border nature of an M&A transaction can affect the level of pre-announcement informed trading in target firms securities. It raises an important issue to financial regulators around the world as the evidence we document calls for more international cooperation in tackling cross-border insider trading activities. Secondly, we are the first to link the country-level regulatory quality to the level of informed trading prior to cross-border M&A announcements. This is different from past studies who focus on the effects of firm-level corporate governance in M&As, as it shows how the acquirer countries law enforcement and investor protection regulations can affect the integrity and investor protection on the financial markets of the target countries. Thirdly, unlike past studies which focus on the impact of corporate governance transfers after the deal announcement, we demonstrate how this difference in the regulatory quality between acquirer and target countries can have impacts on target firms and even target country s financial markets months before the announcement through cross-border informed trading activity. We document supportive evidence for both the positive and negative corporate governance spillover effects, which also has important policy implications regarding how to prevent the negative transfers by enforcing insider trading laws globally, while encouraging the positive spillover. The rest of our paper is organised as follows: Section 2 reviews related literature. Section 3 develops the main hypotheses. Section 4 describes data and sample. Section 5 presents the empirical results. Section 6 conducts robustness checks. Section 7 concludes. 2. Literature Review 9

10 Even though past studies have not directly touched on the issues we intend to examine, there are two strands of literature that our study fits in: 1) pre-m&a announcement informed trading, and 2) corporate governance spillover in cross-border M&As Pre-M&A Announcement Informed Trading The current study contributes to the literature on informed trading s influences on market prices before M&A announcements. Information leakage and insider trading phenomenon has been observed and studied extensively in both developed markets, including the US, UK, Australia and Canada (e.g. Dodd 1980; Jarrell & Poulsen 1989; Betton & Eckbo 2000; and Bris 2005) and emerging markets (e.g. Ma, Pagán & Chu 2009; and Sehgal, Banerjee & Deisting 2012) around the world. Previous studies have consistently documented evidence from both the stock and options markets. Evidence from the stock market suggests that there is likely to be an abnormal price run-up and increased trading activities in the target firm s shares days or even weeks before the initial M&A announcement. However there are two main hypotheses that attempt to explain this phenomenon. One explanation suggests this abnormal price and volume run-up is attributable to information leakage and insider trading activities. Using measures such as CAR, studies that investigate past takeover announcements and insider trading cases consistently find that insider trading contributes to a significant portion of the pre-announcement abnormal stock return of the target firm (Meulbroek 1992; Keown & Pinkerton 1981; Jarrell & Poulsen 1989; Cornell & Sirri 1992; and Ma, Pagán & Chu 2009). The other theory attributes the abnormal run-ups to the market anticipation of a takeover. It argues that there are other observable sources of information, such as rumours, a firm s market position and the consolidation 10

11 trend in a particular industry, which can contribute to the formation of the market s takeover anticipation, and hence abnormal trading activities cannot be used as evidence of insider trading (King & Padalko 2005; and Gao & Oler 2008). However, Jabbour, Jalilvand, and Switzer (2000) put forward a very interesting result that reconciles the two hypotheses: he finds that the early stage abnormal share price performance is attributed to information leakage and corporate insider trading while the run-up immediately prior to the initial M&A announcement is likely to be due to market anticipation. Out results are consistent with this reconciled theory as we find informed trading evidence not only immediately, but up to 5 months prior to the announcements. Past findings also support the existence of informed trading activities in the options market (e.g., Roll, Schwartz & Subrahmanyam 2010; Cremers & Weinbaum 2010; Xing, Zhang & Zhao 2010; Johnson & So 2012; and Lin, Lu & Driessen 2013). Compared to the stock market, the literature has identified the following extra benefits that informed traders enjoy when trading in the options market: 1) the nature of limited risk; 2) no uptick rule on short-selling; 3) high leverage position allowed; and 4) relatively low cost of trading when traders attempt to replicate an option trade with a series of stock trades (Black 1975; Diamond & Verrecchia 1987; and Jayaraman, Frye & Sabherwal 2001). As a result of the above advantages, investors with private information about the forthcoming deals can trade more profitably in the options market than in the stock market as long as the options market is deep enough. Thus, the options market is arguably a better place to look for evidence of informed trading prior to M&A announcements. Cao, Griffin & Chen (2003) find that the pre-announcement volume increase tends to be much more severe compared to that in the stock market. In our study, we focus on option volume and use 11

12 stock volume as a robustness check. Our finding is consistent with the above literature that stock volume tends to be very noisy and hence is a not good proxy for informed trading. Surprisingly, little of the literature is directly related to pre-m&a announcement informed trading in the options market. The two most relevant papers to the present study are Cao, Griffin and Chen (2003) and Chan, Ge and Lin (2013). The former finds that strong pre-announcement volume imbalance between buyer-and seller-initiated call options is positively associated with target firms announcement-day stock return, while the latter finds a positive relationship between implied volatility (IV) spread and target firms cumulative abnormal return around announcement day. Their results suggest that both the volume imbalance and IV spread are good proxies for informed trading prior to M&A announcements, as positive volume imbalance and IV spread both send a bullish signal of future stock returns and reflects informed traders updated view of future stock prices when they trade on favourable private information (Pan & Poteshman 2006; Bali & Hovakimian 2009; Cremers & Weinbaum 2010; Doran & Krieger 2010; Xing et al. 2010; and Ang et al. 2012). Interestingly, Doran, Fodor and Jiang (2013) find a generally negative relationship between IV spread and future out-of-money call option returns, but argue that this negative predictability is mainly driven by unsophisticated liquidity traders, while IV spread s positive stock return predictability is attributable to informed trading. Our results are consistent with informed trading in target firms options, as we find both the IV spread and volume imbalance 4 to be significantly positive prior to initial M&A announcements. 4 We do not follow Cao, Griffin and Chen (2003) in constructing the volume imbalance between buyer-and seller-initiated call options. Instead, we construct call-put volume imbalance in a similar way of constructing IV spread. 12

13 2.2. M&As and Corporate Governance Spillover Effect This paper is also related to the growing literature on corporate governance transfer or spillover through cross-listings and cross-border M&As. Coffee (1999) and Stulz (1999) propose that firms cross-list their shares on foreign exchanges with stricter regulations and more stringent disclosure requirements than their home country to bond them to higher governance standards. A number of empirical studies find evidence that supports the bonding hypothesis (Reese and Weisbach, 2002; Doidge, 2004). Martynova and Renneboog (2008) argue that in a cross-border M&A, if the acquirer s country-level corporate governance is stronger than that of the target, the acquirer s corporate governance practices will be applied to the target firm after the acquisition, thus improving that of the target firm; this is known as the positive spillover hypothesis. However, if the acquirer s country-level corporate governance is weaker than that of the target, the corporate governance in the target firm may deteriorate if the acquirer s corporate governance standards are applied to the target firm (the negative spillover hypothesis ) or improve if the acquirer voluntarily bootstraps itself to the higher governance standards of the target. Empirical evidence in general supports the positive spillover hypothesis and the bootstrapping hypothesis (e.g. Bris, Brisley & Cabolis 2008; Martynova & Renneboog 2008; Rossi & Volpin 2004; and Bhagat, Malhotra & Zhu, 2011). Unlike these studies which focus on changes in firm-level corporate governance after a cross-listing or M&As, we study how the acquirer countries law enforcement and investor protection regulations can affect the integrity and investor protection on the financial markets of the target countries. Although the large existing cross-listing and cross-border M&A literature in general finds a positive transfer or 13

14 spillover from countries with strong corporate governance to the ones with weak governance at the firm level, we document a negative transfer or spillover at the market level. Our evidence also suggests that, despite the expected improvement in firm-level corporate governance, corporate insiders in acquirers from countries with weak corporate governance regulations may profit at the expense of shareholders in both the acquirers and the targets before the completion of the deal. 3. Hypothesis Development In the current study, we seek to understand two main issues: 1) whether the cross-border nature of an M&A transaction induces a higher level of informed trading in the target s stocks and stock options; and 2) whether the involvement of an acquirer with a weak country-level regulatory quality exacerbates such informed trading activity. We are interested in the first research question because of the abundant evidence from cross-border insider trading cases (e.g. the Heinz case ) and the absence of relevant empirical research. Intuitively, cross-border deals may encourage informed trading for the following three reasons. Firstly, the host country s regulatory body is likely to encounter problems in asserting legal jurisdiction when prosecuting a foreign suspect, especially when he or she conducts the trades online. Secondly, in case the assertion of legal jurisdiction fails, the host country s regulator has to rely heavily on cross-border cooperation from foreign regulators who, however, are not guaranteed to be cooperative. Lastly, given the resource constraint, the detection and prosecution of cross-border crimes are unlikely to be the regulator s top priority. Therefore, even though the U.S. has the longest history of insider trading regulations dating back to the 1934 Securities Exchange Act, and it is possible to apply the U.S. insider trading rules 14

15 extraterritorially, cross-border insider trading cases like the Heinz case are in practice less likely to be pursued by the SEC. Our interest in the second research question is an extension of the first. As mentioned above, cross-border prosecution puts a host country s regulator in a passive position as it has to rely heavily on international cooperation; however such cooperation is likely to be particularly difficult to achieve in relation to countries with weak regulatory framework. As many emerging economies may suffer from a poor legal environment as well as weak enforcement of existing laws, it is likely that they have either very weak or no insider trading laws, thus making international cooperation less feasible. Consequently, M&A transactions initiated by acquirers from weak-governance countries may provide a breeding ground for information leakage and cross-border insider trading. Our hypotheses are a direct product of the above two research questions we attempt to address. From our first proposed question, we hypothesise the following: Hypothesis I: M&As, compared to domestic M&As, are associated with a higher level of pre-announcement informed trading in the target firm s stocks and options From our second research question, we hypothesise the following: Hypothesis II: M&As involving acquirers with weak country-level corporate governance, compared to domestic M&As, are associated with a higher level of pre-announcement informed trading in the target s stocks and options. It is relatively easy to understand the above two hypotheses, especially when weak-governance 15

16 acquirers are involved; however it is unclear to us as to how the level of informed trading would be when the acquirer is from a country with strong governance. While the cross-border nature of an M&A creates a barrier to the host country s financial regulators in practising insider trading laws overseas, countries with strong regulatory framework typically well enforce their insider trading laws domestically; such good practice, to some extent, may create a positive spillover effect that significantly reduces the level of informed trading which is otherwise severe when weak-governance acquirers are involved. Thus, we propose the following hypothesis: Hypothesis III: There is no significant difference between cross-border M&As involving acquirers with strong country-level corporate governance and domestic M&As in the level of pre-announcement informed trading in the target s stocks and options. As we believe a strong country-level regulatory quality of the acquirer can create a positive spillover effect, significantly reducing the potential informed trading activity initiated by insiders from the acquirer, while weak governance of the acquirer might similarly bring a negative spillover effect to the target country in the form of informed trading, we assume the both effects are similar in magnitude and only different in signs. Therefore we expect the level of informed trading to be higher in cross-border deals with weak-than strong-governance acquirers, and this difference should be mainly attributable to the informed trading incentive created by the cross-border nature of the deal since the positive and negative spillover effects tend to cancel each other out in this comparison. We therefore hypothesise the following: Hypothesis IV: M&As involving acquirers with weak country-level corporate governance, compared to cross-border M&As involving acquirers with strong country-level corporate 16

17 governance, are associated with a higher level of pre-announcement informed trading in the target s stocks and options. 4. Data and Sample 4.1 Sample Construction The M&A sample of our study consists of 5,000 M&A announcements, and is collected from Securities Data Corporation s (SDC) Platinum Global and US mergers and Acquisitions database. The M&A deal announcement selection criteria are as follows: 1) the deal announcement date is between 1 January 2002 and 31 December 2011; 2) target firms are publically listed firms incorporated in the United States; 3) percentage share sought by the acquirer in the target is greater than 50%; and 4) the deal value paid by the acquirer, excluding fees and expenses, is greater than US$1 million. Additionally, we obtain daily option and share price data from OptionMetrics and CRSP databases respectively. Table 1 summarises, by year of announcement, our main sample and the subsample that has option data available. The total number of transactions drops significantly from 5,000 in the main sample to 929 in the subsample due to the fact that only a limited number of target firms issue tradable options. 4.2 Variables Definition To test our hypotheses and capture informed trading activities, we test five proxies for informed trading in both the stock and options markets. Specifically, we employ one stock-based measure: 1) cumulative 17

18 abnormal return (CAR), and four option-based measures: 1) informed options trading volume, 2) scaled informed options trading volume, 3) implied volatility (IV) spread and 4) call-put volume imbalance. See Appendix for detailed construction of each dependent variable. We use the Regulatory Quality (RQ) index from Worldwide Governance Indicators (WGI) constructed by the World Bank to proxy for country-level regulatory quality. The regulatory quality index captures perceptions of the ability of a country s government to formulate and implement sound policies and regulations, which represents the country s degree of law enforcement, and thus has been employed in many past studies as a proxy for country-level corporate governance (e.g. Neumayer 2002; and Das & Andriamananjara 2006). The RQ index ranges from negative 2.5 to positive 2.5, with negative 2.5 indicating the lowest level of governance. We define an acquirer country with a governance index of less than 1.40 as having a low level of regulatory quality, or having weak corporate governance; this is because during our sample period, the host country in our study, the U.S., experienced 1.40 as its lowest level of corporate governance. We also account for other determinants of the abnormal trading activities in the target s securities through including a number control variables, including percentage of cash payment, deal size, monthly stock return, monthly stock return volatility, tender offer and hostile takeover. 4.3 Even and Estimation Windows We choose the period from the 180 th day before the announcement day to the 1 st day before it, or [-180, -1], as our event window and [-360, -181] as our estimation window. Choosing such a long event window can effectively help us capture sufficient, if not all, pre-announcement informed trading activity, 18

19 since in practice the negotiation phase of M&A deals often last for more than half a year, so there exists the chance that sophisticated insiders start informed trading early and spread out the subsequent trades across time. After determining the length of the event window, we apply a 15-calander day interval both continuously and separately to create two types of windows. We define the first type of windows, cumulative windows, as event windows that have a fixed ending date of t = -1, but an increasing length of period by interval of 15 days (e.g. [-15, -1], [-30, -1], [-45, -1], etc.). In contrast, the second type of windows, segmented windows, are defined as event windows that have a fixed period length of 15 days, but with beginning and ending dates changing by an interval of 15 days (e.g. [-15, -1], [-30, -16, [-45, -31, etc.). It is important that we study both types of windows as cumulative windows measure a cumulative level of informed trading up to 1 day before the announcement, while segmented windows measure the levels of informed trading in each separate 15-day window, providing more information on their patterns. In other words, the comparisons by the former help us understand whether a specific group of M&As are associated with a higher level of pre-announcement informed trading, while the comparisons by the latter will tell us when the most significant differences occur Summary Statistics We present the summary statistics of the five dependent variables in Table 2. It is divided into three categories: domestic deals, cross-border deals involving strong-governance acquirers, and cross-border deals involving weak-governance acquirers. By cumulative window, we find the mean values of all the five measures to be higher for cross-border deals, particularly the ones with weak-governance acquirers. 19

20 We notice a general trend of decreasing in the of the option-based informed trading measures as the event window extends further back away from the announcement day, indicating more severe informed trading closer to the announcement. By segmented window, we see a steadily increasing average level of informed trading as the event window approaches the announcement day. We also notice that for both domestic and cross-border deals, the of CAR experience their largest increase in value during window [-30, -16], and all the option-based measures experience their first jump in mean values during a wider window [-60, -31]. These patterns indicate that large-scale informed trading activity in the stock market begins around half to 1 month before the initial announcements, while such activity is detected to have started up to 1 month earlier in the options market. These results offer a preliminary support to H2, H3 and H4 that cross-border deals with weak-governance acquirers experience higher level of informed trading compared to both domestic and strong-governance cross-border deals, while we expect no significant difference between domestic and strong-governance cross-border deals. The summary statistics of the other independent variables are presented in Table 3. The results show an average country-level governance index of for weak-governance acquirers in cross-border deals, compared to for domestic acquirers and for cross-border strong-governance acquirers. In terms of deal characteristics, all deals have around 93-94% of transaction value paid in cash, but cross-border M&As on average involve larger transaction size, more tender offers, and more hostile takeovers compared to domestic deals. In addition, the targets in cross-border deals on average experience higher monthly stock return than that of domestic deals as of each event date. 5. Empirical Results 20

21 To test our four hypotheses, we make the following comparisons among four deal types: 1) domestic deals and cross-border deals; 2) domestic deals and cross-border deals with weak-governance acquirers; 3) domestic deals and cross-border deals with strong-governance acquirers; and 4) cross-border deals with strong-and weak-governance acquirers Univariate Analysis We conduct difference-in- tests for each of the five informed trading proxies, and the results by cumulative and segmented window are summarised in Table 4 and Table 5 respectively. The results by cumulative window in Table 4 support all of four our hypotheses. All the five measures suggest that cross-border M&As are associated with a higher level of informed trading than domestic deals, and apart from few exceptions that are statistically significant at the 5% level, all event windows are significant at the 1% level. These findings support H1. When comparing domestic and weak-governance cross-border deals, we find the latter to be associated with a higher level of informed trading at the 1% statistical significance for almost all the event windows of option-based measures and the four shortest event windows of CAR. The largest significant difference in CAR occurs during [-60, -1], with informed traders from weak-governance acquirers making an average 9.43% higher abnormal stock return than those in domestic deals. These results all support H2. The comparisons between domestic and strong-governance cross-border deals show conflicting results, suggesting there is no very distinct difference in the level of informed trading between the two deal types, thus weakly supporting H3. Lastly, even though comparisons by CAR find no significant difference in the level of informed trading between 21

22 cross-border deals initiated by strong-governance and weak-governance acquirers, all the option-based measures find such level to be significantly higher with weak-governance acquirers. These results are statistically significant at the 1% level for the majority of the event windows. Thus, H4 is also supported. The test results by segmented window in Table 5 show the patterns of the difference in levels of informed trading among the four deal types. It is shown that cross-border M&As experience a significantly higher level of informed trading than their domestic counterparties. This is particularly true at their peak levels short before the announcement during windows [-15, -1] and [-30, -16], as the differences in by four out of the five measures are at their highest levels and the statistical significance are all at the 1% level. These results support H1. We also find similar patterns for comparisons between domestic and weak-governance cross-border deals, except that the magnitude of the differences in are greater and the results tend to be more statistically significant for option-based measures, which supports H2. When comparing domestic with strong-governance cross-border deals, we find statistically insignificant difference in their level of informed trading in both IV spread and call-put imbalance, while the results are mixed in other measures, again supporting H3. For the comparisons within cross-border deals, unscaled and scaled informed option volume and call-put volume imbalance all find the level of informed trading to be higher with weak-governance acquirers than strong-governance acquirers, significant at the 1% level in the windows leading to announcements. Even though the results of CAR and IV spread are less significant, in general H4 is supported. In addition, we notice for all four groups of comparisons, the most economically significant increase in the mean values occur during [-30, -16] for CAR and [-45, -31] for the option-based measures, suggesting cross-border informed traders, 22

23 especially the ones from weak-governance acquirers, start trading vigorously in the stock market about days before the initial announcements and about days in the options market Multivariate Analysis To further test our hypotheses, we conduct multivariate analyses to compare both the levels of pre-announcement informed trading across the different deal types and acquirer regulatory quality, and how these levels change relative to their benchmark periods as time approaches the announcement. For display simplicity, we only report the coefficients and istics of the key explanatory variables Levels of Pre-announcement Informed Trading To test whether there are systematic differences in the levels of informed trading among the types of deals, we make cross-sectional comparisons by employing the following empirical model to test H1 to H3: Dependent variable = α + β 1 cross border + control variables + ε + industry fixed effect + year fixed effect + clustering by deal(1) and the one below to test H4: Dependent variable = α + β 1 weak_gov + control variables + ε + industry fixed effect + year fixed effect + clustering by deal (2) where both cross_border and weak_gov are dummy variables, referring to a cross-border transaction and a cross-border transaction with weak-governance acquirer, respectively. We include industry-fixed effect to control for industry-specific time-invariant factors. Year-fixed 23

24 effect is also included to control for unobservable firm-or deal-invariant factors. Clustering by deal is used to address the potential serial correlation between the standard errors among the event days within an M&A announcement. Table 6 summarises the regression outputs of comparisons by cumulative window. Findings by four out of the five measures in Panel A show significantly higher level of informed trading in cross-border deals for up to 180 days before the announcements, which is consistent with the findings in univariate analyses above, and lends support to H1. The results in Panel B show the level of informed trading is higher in weak-governance cross-border deals, which is statistically significant for up to 90 days before the announcements for CAR and IV spread, and for up to 180 days for the other three measures. The difference in CAR between the two deal types experiences its highest level during [-60, -1] at the 1% significance level, with informed traders from weak-governance acquirers earning 8.1% higher abnormal stock returns than those in domestic deals; such differences by the option-based measures, however, reach their highest level within 15 days before the announcements. This is consistent with the results from the univariate analyses, and again supports H2. Despite the significantly positive result by CAR in in Panel C, none of the option-based measures finds any significant difference in the levels of informed trading between domestic and strong-governance cross-border deals, supporting H3. Lastly, we also find supportive, though relatively weaker, evidence for H4 in Panel D as only two measures (scaled informed option volume and call-put imbalance) show significantly positive results in weak-governance countries compared to strong-governance ones. Other measures, while finding no statistical significance, in general report positive coefficients, which do not conflict with our expectation outlined in H4. 24

25 The outputs for regressions by segmented window are presented in Table 7. Through results in Panel A, we find significantly higher level of informed trading in cross-border deals short before the announcements (i.e. [-15, -1]) for all measures except scaled informed option volume. The results provide evidence that informed trading becomes most vigorous within 1 month before the announcement days in both the stock and options markets, and once again lends support to H1. We also find support for H2 since the results of all five measures are both economically and econometrically stronger in Panel B than those in Panel A. In addition, we notice that the first statistically significant coefficient by CAR is found in [-180, -166], implying the potential inception of informed trading in the stock market. For the option measures, the first economically significant increases in the coefficient value take place during a 30-day window [-165, -136]. Even though their coefficient estimates are not all statistically significant, their strong economic significance implies that informed traders from weak-governance countries start entering into the options market as early as 5 months before the initial M&A announcement. In sum, the patterns we find suggest there are three typical periods when detectible large-scale informed trades in weak-governance cross-border deals enter into the stock markets: [-180, -166], [-120, -106] and [-30, -16], and they enter into the options market during similar timeframe: [-150, -121], [-90, -61] and [-45, -16]. In Panel C, the mixed results again support H3, while all five measures in Panel D find support for H4, despite the results by IV spread find the contrary in one window ([-75, -61]) Changes in Pre-announcement Informed Trading Apart from the difference in levels of pre-announcement informed trading across the four deal types, we are also interested in how these levels change, relative to a clean estimation or benchmark period, across 25

26 time, since it is possible that one or more of the option-based informed trading measures we employ are inherently and constantly higher or lower in a particular type of deals. To investigate this, we employ the model below to test H1 to H3: Dependent variable = α + β 1 cross_border event + event + control variables + ε + deal fixed effect + clustering by deal (3) and when testing H4, we adjust the above model to: Dependent variable = α + β 1 weak_gov event + event + control variables + ε + deal fixed effect + clustering by deal (4) where Dependent variable excludes CAR since it is a cumulative measure which already represents changes in stock values, event is a dummy variable which equals 1 when the day being tested falls in the event window and 0 if it falls in the estimation window of [-360, -181]. As deal-fixed effect is used, explanatory and control variables that do not change across the estimation and event windows for the same deal (i.e. cross-border, percentage cash, deal size, tender offer and hostile) will be excluded from the model because they are subsumed into the deal-fixed effect. The results for the comparisons by cumulative window are presented in Table 8. In Panel A, both scaled informed option volume and IV spread find significantly larger increase in the level of informed trading in cross-border compared to domestic deals, suggesting that cumulatively there are more trades on informed options in cross-border than domestic deals after adjusting for their respective benchmark-period volume. While the other two measures report positive but statistically insignificant 26

27 results, these results are economically significant and do not conflict with the findings of the above two measures; thus H1 is supported. In Panel B, we find all the four measures to be associated with positive coefficients of the key explanatory variable, and for all the measures, these coefficients display a trend of steadily increasing economic significance as event window narrows. This that the level of informed trading is increasingly higher in weak-governance cross-border deals closer to the announcements. Even though the results of informed option volume are not statistically significant for any event window, its strong economic significance (e.g. during [-15, -1], there are on average 3066 more suspicious informed option trades in weak-governance cross-border than in domestic deals) are in line with the statistically significant results by the other measures, supporting H2. In Panel C, while using two measures (informed option volume and call-put volume imbalance) we find the level of informed trading, after adjusting for benchmark-volume, to be significantly lower in strong-governance cross-border than domestic deals, the associated economic significance is negligible compared to that in Panel B. As the other two measures both find no significant differences, H3 is supported. Lastly in Panel D, we find supportive results for H4 in IV spread and call-put imbalance, which are both economically and statistically significant, and in the other two measures which are economically significant. Table 9 presents the findings of comparisons by segmented window. Through the results in Panel A, we find the higher levels of informed trading, adjusted by benchmark-period volume, in cross-border deals to be mainly driven by suspicious informed trades within 45 days before the announcement date, while the first large-scale informed trading activity by cross-border informed traders can date back to about 3-4 months prior to the initial announcements. When comparing domestic and weak-governance 27

28 cross-border deals, we find three interesting windows in Panel A: [-150, -136], [-90, -61] and [-16, -45]. During the three window, all the measures experience their first jump in coefficient value of the key explanatory variable, from which we conclude the following pattern: informed traders from weak-governance acquirers seem to start trading as early as 5 months before the announcement, which is followed by a period of fluctuations before the informed trading activity picks up again about 2-3 months prior to the announcement, and the last surge in the level of informed trading takes place around 1 month before the announcement, leading the activity to its peak. This pattern is consistent with the finding in Panel A, and is also in support of H2. In Panel C, even though the results of informed option volume suggests significantly different levels of informed trading between domestic and strong-governance cross-border deals, the magnitude of this difference is economically insignificant when compared to that in Panel A. Together with the insignificant results found by other measures, we conclude that H3 is supported. Lastly in Panel C, even though two measures do not find any statistical significance for any event window, again their results exhibit strong economic significance, thus also supporting H4. In sum, all the four hypotheses are well supported by the empirical test results. 6. Robustness Checks 6.1. Uninformed Call Options To check the robustness of our main results, we rerun the above multivariate analyses, but using uninformed call options as the sample. If the results are much weaker than or the reverse of our main results, it our selection criteria for suspicious informed options are correct. We define uninformed call options as the call options that do not meet our criteria for an informed option; more specifically, an 28

29 uninformed call option meets the following criteria: a) the call option is in-or at-the-money ; b) the strike price of the option is higher than or equal to the offer price of the M&A transaction; and c) the expiration day of the option is before the announcement day or 30 days after it. We do not report the regression outputs but overall they show much weaker results, both economically and econometrically, or even opposite coefficients compared to our main results, supporting our selection criteria for the informed options Other Informed Trading Measures We also attempt to check the robustness of our results using other potential proxies for informed trading. We employ both stock volume and bid-ask spread as additional stock-based measures and re-conduct the above multivariate analyses with them; however, the results do not appear to be supportive and hence we do not report the results. Our interpretation of the non-supportive results is that both measures are not good proxies for informed trading. Stock volume is not a satisfactory measure because, unlike option volume which can be relatively easily deconstructed into the informed and uninformed, it is very difficult to filter out the noise or uninformed portion of a stock s trading volume, unless trade-specific intraday data is available. As for the bid-ask spread, it can be decomposed into information asymmetry component and non-informational content; only the former is of our interest. 7. Conclusions 29

30 Using M&A data spanning 10 years with 5,000 domestic and cross-border transactions involving U.S. targets, we compare the levels of pre-announcement informed trading between domestic and cross-border transactions, and investigate the effect of the acquirers country-level corporate governance on the level of informed trading. We study both daily stock and option data and include five stock-and option-based measures as proxies for informed trading, and employ both cumulative and segmented 15-day event windows of up to 180 days before the initial announcements to study not only the cross-sectional difference in the level of informed trading across deal types, but also the changes in such level relative to benchmark-period value and their patterns. Our results show the following four key findings. Firstly, we find that cross-border M&As are associated with a higher level of pre-announcement informed trading than the domestic counterparties. This is in line with our expectation that the cross-border nature of the transaction adds a barrier of legal enforcement to the host country s financial regulators in practising insider trading laws, thus incentivising overseas information leakage and cross-border insider trading. Secondly, we find the higher level of informed trading in cross-border deals is mainly driven by acquirers from countries with weak regulatory regimes. We believe this is evidence of the negative spillover effect, as the poor governance in the acquirer nation spills over to the target country s financial market in the form of informed trading on the target securities. Thirdly, we find no significant difference in the level of informed trading between domestic and strong-governance cross-border deals before the announcements. This is also consistent with our expectation that the positive spillover effect brought by strong-governance acquirers acts to offset the informed trading incentive created by the cross-border nature of the transaction. Lastly, within 30

31 cross-border M&As, we find the level of pre-announcement informed trading to be higher when a weak-governance acquirer is involved. Under the assumption that the positive and negative spillover effects are similar in magnitude but different in signs so tend to offset each other in this comparison, this finding further supports our argument for the existence of incentives, created by the cross-border nature of an M&A, to trade on private information in the deal. In addition to the above main results, we also identify the general pattern of informed trading activity prior to cross-border M&A announcements involving poor-governance acquirers. Our data shows there are three major time windows when detectible informed traders or trades enter into the markets between 166 and 180 days, 106 and 120 days, and 16 and 30 days, respectively, into the stock market, and between 136 and 150 days, 61 and 90 days, and 16 and 45 days before the announcement day, respectively, into the options market. It appears that informed traders enter into the stock market earlier than into the options market, which can be justified by the higher costs of options with longer maturity. A possible reason for an early entry into the markets is that some more sophisticated insiders choose to start trading on their private information early, and spread out subsequent trades as time approaches the announcement; this way, they may more effectively hide in the crowd and reduce the chance of being detected, despite the higher cost of out-of-money call options they are likely to face. The contribution of the current study to the literature is threefold. Firstly, we are the first to study how the cross-border nature of an M&A transaction can affect the level of pre-announcement informed trading in target firms securities. As we document such level to be higher prior to cross-border transactions, it provides strong policy implications regarding how to overcome the legal enforcement barriers created by 31

32 cross-border transactions. Secondly, unlike past studies who focus on the effects of firm-level corporate governance in M&As, we are the first to link the country-level corporate governance to the level of informed trading prior to cross-border M&A announcements, and document such level to be higher when the acquirer institution is subject to weaker regulatory regimes. This allows us to study how the acquirer countries law enforcement and investor protection can affect the integrity and investor protection on the financial markets of the target countries. Lastly, we are again the first to demonstrate that the transfer of country-level corporate governance practices can have immediate impacts on an M&A target s firm value and even target country s financial markets even months before the initial announcement through informed trading, and document supportive evidence for both the positive and negative spillover effects. Our findings are of particular significance to the negative spillover effect, as such theory or phenomenon has historically lacked supportive evidence, and hence not been attracting sufficient attention from empirical researchers and policy makers. 32

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36 Appendix: Details of Construction of Key Variables 1. Cumulative Abnormal Return (CAR) The pre-announcement stock price run-up is measured using CAR. Following Brown and Warner (1985), we utilise a standard event study methodology and compute market model abnormal returns. The daily abnormal return is measured as the actual ex-post return of the security over the event window minus the daily expected return for the security over the event window. The daily expected return is estimated using a one-factor market model. This model relates the return of a given security to the return of the market portfolio. The market model assumes the following linear relation between the return of any security and the return of the market portfolio: R i,t = α i + β i R m,t + ε i,t (5) 2 E(ε i,t = 0) Var(ε i,t ) = σ εi (6) where R i,t and R m,t are the returns on security i and the market portfolio during the t th time period and ε i,t is the zero mean disturbance term. α i and β i are the parameters of the market model. The daily returns of the CRSP Equally Weighted Index are used to proxy for the market portfolio. We estimate the market model parameters using daily stock returns and daily market returns over the pre-announcement period [-361, -540]. A half-year gap is kept between the event window and the estimation period to prevent the event from contaminating the estimation of benchmark return. Abnormal return for each stock during the event window is then calculated as the difference between the actual realised returns and the expected returns predicted by our market model, and the daily abnormal returns are summed over the event days to compute the CARs: AR it = R i,t α i β i R m,t (7) where CAR(t, n) denotes the CAR for the period between t and n. n CAR(t, n) = t=1 AR t (8) 36

37 2. Informed Options Trading Volume In this paper, we consider out-of-money call options as the suspicious informed trades, or the informed options, as past studies have revealed that short-term deep out-of-money call options are a perfect choice for insiders to exploit their private information prior to a positive announcement (E.g. Cao, Griffin & Chen 2003; and Pan & Poteshman 2006). However, we did not apply the short-term and deep out-of-money criteria. This is due to the following two reasons. Firstly, even though informed traders understand that trading short-term deep out-of-money call options can help them realize the profit faster (Chan, Ge & Lin 2013), there is also the possibility that more sophisticated informed traders start trading early and spread out their subsequent trades as time approaches the announcement; this way, their trades will attract less attention immediately before the announcement, so that the chance of their activity being detected is minimized. Secondly, we are also interested in how the levels of informed trading change in the event windows relative to the estimation window; the short-term and deep out-of-money restrictions would most likely eliminate both the volume of informed trades conducted relatively long before the announcement day and the benchmark volume in the estimation period. Specifically, we apply the following criteria to select the informed options: a) The option is an out-of-money call option; b) The strike price of the option is less than the offer price of the M&A transaction; and c) The expiration day of the option is within 30 days after the announcement day. We compute the daily informed option volume according to the followings: N i,t Inf Vol i,t = k=1 Inf Vol i,t,k (9) where Inf Vol i,t,k is the informed option volume of the k th trade of security i on day t, and Inf Vol i,t represents the daily volume of the informed trades, or the sum of volume of all trades of security i on day t. 3. Scaled Informed Options Trading Volume 37

38 The daily volume of suspicious informed trades in the options market is also scaled by the volume of the total options traded on the underlying stock on the day to account for the different levels of option liquidity across stocks: Inf Vol Scaled it = Inf Vol i,t /Tot Vol i,t (10) where Inf Vol i,t is the informed option volume of security i on day t, and Tot Vol i,t is the daily volume of the total option trades of the same underlying stock on the same day. 4. Implied Volatility (IV) Spread To measure deviations from put-call parity, we follow Cremers and Weinbaum (2010) and Chan, Ge and Lin (2013) in constructing IV spread. It is constructed as the average difference in implied volatilities between a security s call and put options that have the same strike price and same maturity. Mathematically, N i,t IV Spread i,t = IV calls i,t IV puts i,t = w i j,t (IV i,call j,t IV i,put j=1 j,t ) (11) where IV Spread i,t is the IV spread for security i on day t, j refers to pairs of calls and puts with the i same strike price and maturity, N i,t denotes the total number of valid pairs for the security on the day, w j,t i is the weight calculated as the average open interest of call and put in each pair, and IV i,t represents the Black and Scholes (1973) implied volatilities for each call and put. In addition, we restrict the call of each pair to only the suspicious options, and options with zero open interest or zero best bid price are excluded. 5. Call-Put Volume Imbalance Inspired by the design of IV spread, we attempt to evaluate the volume imbalance between call and put options by constructing the call-put imbalance measure in a similar way. Specifically, we compare the volume of calls and puts with same strike prices and maturity dates, but instead of finding the difference between them, we find their ratio. Mathematically, 38

39 N i,t CP Imb i,t = Vol calls i,t /Vol puts i,t = w i j,t (Vol i,call j,t /Vol i,put j=1 j,t ) (12) where CP Imb i,t is the call-put volume imbalance for security i on day t, j refers to pairs of calls and puts with the same strike price and maturity, N i,t denotes the total number of valid pairs for the i security on the day, w j,t is the weight calculated as the average open interest of call and put in each pair, i and Vol i,t represents the volume for each call and put. Similarly, we also restrict the call of each pair to only the suspicious options, and options with zero open interest or zero best bid price are excluded. 39

40 Table 1 M&A Sample Description Panel A: M&A Sample with Stock Data Year High Governance Low Governance Subtotal Total Total Panel B: M&A Sample with Option Data Year High Governance Low Governance Subtotal Total Total

41 Low Governance High Governance Table 2 Summary Statistics of Key Dependent Variables This table provides summary statistics for the five informed trading measures for the full sample. The results for the five measures are presented in Panels A to E respectively. CAR measures the cumulative abnormal return for the target stock during the event window. Informed option volume represents the daily volume of the suspicious informed trades on the target s options. Scaled informed option volume equals Informed option volume divided by total daily option volume. IV spread measures the deviation from put-call parity of the target s options. Call-put volume imbalance measures the imbalance between the target s call and put options. The results are categorised into domestic M&As, cross-border M&As with strong-governance acquirers and cross-border M&As with weak-governance acquirers. The numbers in the event windows represent the number of calendar days before the initial M&A announcements Event Window By Cumulative Window No. Obs. Mean Standard Deviation Panel A: CAR Median Event Window By Separate Window No. Obs. Mean Standard Deviation Median [-15, -1] % 14.94% 0.19% [-15, -1] % 14.94% 0.19% [-30, -1] % 20.56% -0.16% [-30, -16] % 13.69% -0.43% [-45, -1] % 27.80% -0.50% [-45, -31] % 15.42% -0.45% [-60, -1] % 31.51% -0.74% [-60, -46] % 11.85% -0.33% [-75, -1] % 34.84% -1.06% [-75, -61] % 12.81% -0.50% [-90, -1] % 38.23% -1.58% [-90, -76] % 12.76% -0.50% [-105, -1] % 42.02% -1.55% [-105, -91] % 11.80% -0.32% [-120, -1] % 45.70% -2.25% [-120, -106] % 11.78% -0.77% [-135, -1] % 48.94% -2.22% [-135, -121] % 11.18% -0.40% [-150, -1] % 52.27% -2.18% [-150, -136] % 12.36% -0.33% [-165, -1] % 56.16% -2.70% [-165, -151] % 12.63% -0.43% [-180, -1] % 59.62% -3.04% [-180, -166] % 11.21% -0.36% [-15, -1] % 15.09% 1.29% [-15, -1] % 15.09% 1.29% [-30, -1] % 20.88% 5.02% [-30, -16] % 14.00% 1.76% [-45, -1] % 23.86% 5.22% [-45, -31] % 12.78% -0.15% [-60, -1] % 29.68% 6.91% [-60, -46] % 14.52% -0.33% [-75, -1] % 35.51% 5.63% [-75, -61] % 11.87% -0.24% [-90, -1] % 38.45% 6.19% [-90, -76] % 11.52% -0.26% [-105, -1] % 43.98% 5.34% [-105, -91] % 12.99% -0.34% [-120, -1] % 46.87% 4.95% [-120, -106] % 11.51% -0.37% [-135, -1] % 51.01% 4.56% [-135, -121] % 14.57% -0.47% [-150, -1] % 55.89% 3.68% [-150, -136] % 12.90% -0.31% [-165, -1] % 60.10% 0.50% [-165, -151] % 12.45% -0.78% [-180, -1] % 63.21% 2.59% [-180, -166] % 10.57% 0.30% [-15, -1] % 16.89% 2.91% [-15, -1] % 16.89% 2.91% [-30, -1] % 25.69% 6.23% [-30, -16] % 19.31% 1.92% [-45, -1] % 32.73% 8.38% [-45, -31] % 16.72% -1.52% [-60, -1] % 37.58% 6.60% [-60, -46] % 14.96% 0.51% [-75, -1] % 37.55% 4.74% [-75, -61] % 12.46% -0.63% [-90, -1] % 42.48% 5.28% [-90, -76] % 15.50% -0.45% [-105, -1] % 50.90% 4.87% [-105, -91] % 18.48% -1.41% [-120, -1] % 54.14% 3.47% [-120, -106] % 13.81% 0.26% [-135, -1] % 56.38% 7.47% [-135, -121] % 11.66% 0.24% [-150, -1] % 61.11% 7.59% [-150, -136] % 14.29% -2.21% [-165, -1] % 63.91% 9.52% [-165, -151] % 16.21% -0.54% [-180, -1] % 67.32% 7.51% [-180, -166] % 12.85% 2.26% 41

42 Low Governance High Governance By Cumulative Window Table 2 (Cont.) Summary Statistics of Key Dependent Variables Panel B: Informed Option Volume By Separate Window Event No. Standard Event No. Standard Window Obs. Mean Deviation Median Window Obs. Mean Deviation Median [-15, -1] [-15, -1] [-30, -1] [-30, -16] [-45, -1] [-45, -31] [-60, -1] [-60, -46] [-75, -1] [-75, -61] [-90, -1] [-90, -76] [-105, -1] [-105, -91] [-120, -1] [-120, -106] [-135, -1] [-135, -121] [-150, -1] [-150, -136] [-165, -1] [-165, -151] [-180, -1] [-180, -166] [-15, -1] [-15, -1] [-30, -1] [-30, -16] [-45, -1] [-45, -31] [-60, -1] [-60, -46] [-75, -1] [-75, -61] [-90, -1] [-90, -76] [-105, -1] [-105, -91] [-120, -1] [-120, -106] [-135, -1] [-135, -121] [-150, -1] [-150, -136] [-165, -1] [-165, -151] [-180, -1] [-180, -166] [-15, -1] [-15, -1] [-30, -1] [-30, -16] [-45, -1] [-45, -31] [-60, -1] [-60, -46] [-75, -1] [-75, -61] [-90, -1] [-90, -76] [-105, -1] [-105, -91] [-120, -1] [-120, -106] [-135, -1] [-135, -121] [-150, -1] [-150, -136] [-165, -1] [-165, -151] [-180, -1] [-180, -166]

43 Low Governance High Governance By Cumulative Window Table 2 (Cont.) Summary Statistics of Key Dependent Variables Panel C: Scaled Informed Option Volume By Separate Window Event No. Standard Event No. Standard Window Obs. Mean Deviation Median Window Obs. Mean Deviation Median [-15, -1] [-15, -1] [-30, -1] [-30, -16] [-45, -1] [-45, -31] [-60, -1] [-60, -46] [-75, -1] [-75, -61] [-90, -1] [-90, -76] [-105, -1] [-105, -91] [-120, -1] [-120, -106] [-135, -1] [-135, -121] [-150, -1] [-150, -136] [-165, -1] [-165, -151] [-180, -1] [-180, -166] [-15, -1] [-15, -1] [-30, -1] [-30, -16] [-45, -1] [-45, -31] [-60, -1] [-60, -46] [-75, -1] [-75, -61] [-90, -1] [-90, -76] [-105, -1] [-105, -91] [-120, -1] [-120, -106] [-135, -1] [-135, -121] [-150, -1] [-150, -136] [-165, -1] [-165, -151] [-180, -1] [-180, -166] [-15, -1] [-15, -1] [-30, -1] [-30, -16] [-45, -1] [-45, -31] [-60, -1] [-60, -46] [-75, -1] [-75, -61] [-90, -1] [-90, -76] [-105, -1] [-105, -91] [-120, -1] [-120, -106] [-135, -1] [-135, -121] [-150, -1] [-150, -136] [-165, -1] [-165, -151] [-180, -1] [-180, -166]

44 Low Governance High Governance By Cumulative Window Table 2 (Cont.) Summary Statistics of Key Dependent Variables Panel D: IV Spread By Separate Window Event No. Standard Event No. Standard Window Obs. Mean Deviation Median Window Obs. Mean Deviation Median [-15, -1] [-15, -1] [-30, -1] [-30, -16] [-45, -1] [-45, -31] [-60, -1] [-60, -46] [-75, -1] [-75, -61] [-90, -1] [-90, -76] [-105, -1] [-105, -91] [-120, -1] [-120, -106] [-135, -1] [-135, -121] [-150, -1] [-150, -136] [-165, -1] [-165, -151] [-180, -1] [-180, -166] [-15, -1] [-15, -1] [-30, -1] [-30, -16] [-45, -1] [-45, -31] [-60, -1] [-60, -46] [-75, -1] [-75, -61] [-90, -1] [-90, -76] [-105, -1] [-105, -91] [-120, -1] [-120, -106] [-135, -1] [-135, -121] [-150, -1] [-150, -136] [-165, -1] [-165, -151] [-180, -1] [-180, -166] [-15, -1] [-15, -1] [-30, -1] [-30, -16] [-45, -1] [-45, -31] [-60, -1] [-60, -46] [-75, -1] [-75, -61] [-90, -1] [-90, -76] [-105, -1] [-105, -91] [-120, -1] [-120, -106] [-135, -1] [-135, -121] [-150, -1] [-150, -136] [-165, -1] [-165, -151] [-180, -1] [-180, -166]

45 Low Governance High Governance By Cumulative Window Table 2 (Cont.) Summary Statistics of Key Dependent Variables Panel E: Call-Put Volume Imbalance By Separate Window Event No. Standard Event No. Standard Window Obs. Mean Deviation Median Window Obs. Mean Deviation Median [-15, -1] [-15, -1] [-30, -1] [-30, -16] [-45, -1] [-45, -31] [-60, -1] [-60, -46] [-75, -1] [-75, -61] [-90, -1] [-90, -76] [-105, -1] [-105, -91] [-120, -1] [-120, -106] [-135, -1] [-135, -121] [-150, -1] [-150, -136] [-165, -1] [-165, -151] [-180, -1] [-180, -166] [-15, -1] [-15, -1] [-30, -1] [-30, -16] [-45, -1] [-45, -31] [-60, -1] [-60, -46] [-75, -1] [-75, -61] [-90, -1] [-90, -76] [-105, -1] [-105, -91] [-120, -1] [-120, -106] [-135, -1] [-135, -121] [-150, -1] [-150, -136] [-165, -1] [-165, -151] [-180, -1] [-180, -166] [-15, -1] [-15, -1] [-30, -1] [-30, -16] [-45, -1] [-45, -31] [-60, -1] [-60, -46] [-75, -1] [-75, -61] [-90, -1] [-90, -76] [-105, -1] [-105, -91] [-120, -1] [-120, -106] [-135, -1] [-135, -121] [-150, -1] [-150, -136] [-165, -1] [-165, -151] [-180, -1] [-180, -166]

46 Low Governance High Governance Table 3 Summary Statistics of Independent and Control Variables This table provides summary statistics for the independent and control variables for the full sample. Governance index refers to the Regulatory Quality (RQ) index from Worldwide Governance Indicators (WGI) constructed by the World Bank; it ranges from -2.5 to 2.5. Percentage cash measures the percentage of cash offered by the acquirer in the M&A deal. Deal size is the value of the transaction in US$ millions. Tender offer is a dummy variable which equals 1 if the acquirer makes a tender offer in the M&A deal and 0 otherwise. Hostile is a dummy variable which equals 1 if the acquirer initiates a hostile takeover in the M&A deal and 0 otherwise. Monthly stock return measures the monthly return of the target stock as at the event day. Monthly stock return volatility is the standard deviation of Monthly stock return. The results are categorised into domestic M&As, cross-border M&As with strong-governance acquirers and cross-border M&As with weak-governance acquirers. No. Standard 25th 75th Variable Obs. Mean Deviation Percentile Median Percentile Governance index Percentage cash Deal size Tender offer Hostile Monthly stock return Monthly stock return volatility Governance index Percentage cash Deal size Tender offer Hostile Monthly stock return Monthly stock return volatility Governance index Percentage cash Deal size Tender offer Hostile Monthly stock return Monthly stock return volatility

47 Table 4 Difference in Means Tests by Cumulative Window This table presents results of the difference-in- tests for the five informed trading measures for the full sample. The results for the five measures are presented in Panels A to E respectively. CAR measures the cumulative abnormal return for the target stock during the event window. Informed option volume represents the daily volume of the suspicious informed trades on the target s options. Scaled informed option volume equals Informed option volume divided by total daily option volume. IV spread measures the deviation from put-call parity of the target s options. Call-put volume imbalance measures the imbalance between the target s call and put options. The results are categorised into 1) domestic M&As compared to cross-border M&As, 2) domestic M&As compared to cross-border M&As with weak-governance acquirers, 3) domestic M&As compared to cross-border M&As with weak-governance acquirers, and 4) cross-border M&As with strong-governance acquirers compared to cross-border M&As with weak-governance acquirers. The numbers in the event windows represent the number of calendar days before the initial M&A announcements. Statistical significance is indicated at the 10% (*), 5% (**) and 1% levels (***). Event Window Panel A: CAR Low Governance High Governance : High Governance Low Governance [-15, -1] -2.81% -3.74*** -4.57% -3.27*** -2.16% -2.50** -2.41% [-30, -1] -6.32% -6.09*** -8.90% -4.61*** -5.36% -4.50*** -3.54% [-45, -1] -6.63% -4.78*** -8.69% -3.33*** -5.87% -3.68*** -2.82% [-60, -1] -7.71% -4.89*** -9.43% -3.19*** -7.08% -3.90*** -2.35% [-75, -1] -7.94% -4.54*** -8.65% -2.66*** -7.67% -3.80*** -0.98% [-90, -1] -7.55% -3.93*** -7.61% -2.13** -7.52% -3.40*** -0.08% [-105, -1] -7.30% -3.44*** -6.41% % -3.13*** 1.21% 0.24 [-120, -1] -7.59% -3.30*** -8.35% -1.95* -7.31% -2.76*** -1.04% [-135, -1] -7.58% -3.08*** -8.25% -1.80* -7.34% -2.59*** -0.92% [-150, -1] -7.14% -2.71*** -6.70% % -2.40** 0.61% 0.10 [-165, -1] -6.24% -2.21** -6.51% % -1.89* -0.36% [-180, -1] -7.35% -2.45** -9.93% -1.78* -6.40% -1.85* -3.53% Event Window Panel B: Informed Option Volume Low Governance High Governance : High Governance Low Governance [-15, -1] *** *** *** [-30, -1] *** *** *** [-45, -1] *** *** ** *** [-60, -1] *** *** ** *** [-75, -1] *** *** ** *** [-90, -1] *** *** ** *** [-105, -1] *** *** ** *** [-120, -1] *** *** ** *** [-135, -1] *** *** ** *** [-150, -1] *** *** ** *** [-165, -1] *** *** ** *** [-180, -1] *** *** ** *** 47

48 Table 4 (Cont.) Difference in Means Tests by Cumulative Window Panel C: Scaled Informed Option Volume Low Governance High Governance : High Governance Low Governance Event Window [-15, -1] *** *** *** ** [-30, -1] *** *** ** *** [-45, -1] *** *** ** *** [-60, -1] *** *** *** [-75, -1] *** *** *** [-90, -1] *** *** *** [-105, -1] *** *** *** [-120, -1] *** *** ** *** [-135, -1] *** *** ** *** [-150, -1] *** *** ** *** [-165, -1] *** *** ** *** [-180, -1] *** *** ** *** Event Window Panel D: IV Spread Low Governance High Governance : High Governance Low Governance [-15, -1] ** ** [-30, -1] *** *** * ** [-45, -1] *** *** * ** [-60, -1] *** *** ** [-75, -1] *** *** * *** [-90, -1] *** *** * ** [-105, -1] *** *** ** ** [-120, -1] *** *** ** *** [-135, -1] *** *** ** *** [-150, -1] *** *** ** *** [-165, -1] *** *** ** *** [-180, -1] *** *** ** *** 48

49 Table 4 (Cont.) Difference in Means Tests by Cumulative Window Panel E: Call-Put Volume Imbalance Low Governance High Governance : High Governance Low Governance Event Window [-15, -1] *** *** *** [-30, -1] *** *** *** [-45, -1] *** *** *** [-60, -1] *** *** *** [-75, -1] *** *** *** [-90, -1] *** *** *** [-105, -1] *** *** *** [-120, -1] *** *** *** [-135, -1] *** *** *** [-150, -1] *** *** * *** [-165, -1] *** *** *** [-180, -1] *** *** * *** Table 5 Difference in Means Tests by Segmented Window This table presents results of the difference-in- tests for the five informed trading measures for the full sample. The results for the five measures are presented in Panels A to E respectively. CAR measures the cumulative abnormal return for the target stock during the event window. Informed option volume represents the daily volume of the suspicious informed trades on the target s options. Scaled informed option volume equals Informed option volume divided by total daily option volume. IV spread measures the deviation from put-call parity of the target s options. Call-put volume imbalance measures the imbalance between the target s call and put options. The results are categorised into 1) domestic M&As compared to cross-border M&As, 2) domestic M&As compared to cross-border M&As with weak-governance acquirers, 3) domestic M&As compared to cross-border M&As with weak-governance acquirers, and 4) cross-border M&As with strong-governance acquirers compared to cross-border M&As with weak-governance acquirers. The numbers in the event windows represent the number of calendar days before the initial M&A announcements. Statistical significance is indicated at the 10% (*), 5% (**) and 1% levels (***). Event Window Panel A: CAR Low Governance High Governance : High Governance Low Governance [-15, -1] -2.81% -3.74*** -4.57% -3.27*** -2.16% -2.50** -2.41% [-30, -16] -3.51% -5.06*** -4.34% -3.36*** -3.20% -4.04*** -1.14% [-45, -31] -0.31% % % % 0.48 [-60, -46] -1.09% -1.79* -0.74% % -1.74* 0.48% 0.30 [-75, -61] -0.22% % % % 1.06 [-90, -76] 0.39% % % % 0.66 [-105, -91] 0.25% % % % 0.82 [-120, -106] -0.29% % -1.76* 0.32% % -1.72* [-135, -121] 0.01% % % % 0.08 [-150, -136] 0.45% % % % 1.07 [-165, -151] 0.89% % % % [-180, -166] -1.11% -1.97** -3.45% -3.27*** -0.25% % -2.63*** 49

50 Table 5 (Cont.) Difference in Means Tests by Segmented Window Panel B: Informed Option Volume Low Governance High Governance : High Governance Low Governance Event Window [-15, -1] *** *** *** [-30, -16] *** *** ** *** [-45, -31] * *** ** *** [-60, -46] *** ** *** [-75, -61] * *** *** [-90, -76] ** *** *** [-105, -91] *** [-120, -106] *** *** [-135, -121] ** [-150, -136] *** *** [-165, -151] [-180, -166] *** ** Event Window Panel C: Scaled Informed Option Volume Low Governance High Governance : High Governance Low Governance [-15, -1] *** *** *** ** [-30, -16] *** *** *** [-45, -31] *** *** *** [-60, -46] ** ** [-75, -61] ** *** ** [-90, -76] *** *** ** [-105, -91] * *** ** [-120, -106] *** ** ** [-135, -121] *** ** ** [-150, -136] *** [-165, -151] [-180, -166]

51 Table 5 (Cont.) Difference in Means Tests by Segmented Window Panel D: IV Spread Low Governance High Governance : High Governance Low Governance Event Window [-15, -1] ** ** [-30, -16] *** *** ** [-45, -31] [-60, -46] [-75, -61] ** *** * [-90, -76] [-105, -91] [-120, -106] ** *** ** [-135, -121] * ** [-150, -136] ** ** * [-165, -151] [-180, -166] Event Window Panel E: Call-Put Volume Imbalance Low Governance High Governance : High Governance Low Governance [-15, -1] *** *** *** [-30, -16] *** *** *** [-45, -31] ** *** ** [-60, -46] [-75, -61] * *** * [-90, -76] [-105, -91] ** [-120, -106] *** *** [-135, -121] ** [-150, -136] ** [-165, -151] [-180, -166]

52 Table 6 Comparisons of Levels of Pre-announcement Informed Trading by Cumulative Window This table presents the OLS regression outputs of regressing the five informed trading measures on dummy (for Panel A, B & C) or Weak-gov dummy (for Panel D). Year-fixed effect, industry-fixed effect and clustering by deal are used. For display simplicity, only the results of the key independent variables are presented. CAR measures the cumulative abnormal return for the target stock during the event window. Informed option volume represents the daily volume of the suspicious informed trades on the target s options. Scaled informed option volume equals Informed option volume divided by total daily option volume. IV spread measures the deviation from put-call parity of the target s options. Call-put volume imbalance measures the imbalance between the target s call and put options. Independent variables include: governance index, percentage cash, deal size, tender offer, hostile, monthly stock return and monthly stock return volatility. is a dummy which equals 1 for cross-border transactions and 0 otherwise. Weak-gov is a dummy which equals one if Governance index of the acquirer is below Governance index refers to the Regulatory Quality (RQ) index from Worldwide Governance Indicators (WGI) constructed by the World Bank; it ranges from -2.5 to 2.5. Percentage cash measures the percentage of cash offered by the acquirer in the M&A deal. Deal size is the value of the transaction in US$ millions. Tender offer is a dummy variable which equals 1 if the acquirer makes a tender offer in the M&A deal and 0 otherwise. Hostile is a dummy variable which equals 1 if the acquirer initiates a hostile takeover in the M&A deal and 0 otherwise. Monthly stock return measures the monthly return of the target stock as at the event day. Monthly stock return volatility is the standard deviation of Monthly stock return. The numbers in the event windows represent the number of calendar days before the initial M&A announcements. The numbers in the event windows represent the number of calendar days before the initial M&A announcements. Statistical significance is indicated at the 10% (*), 5% (**) and 1% levels (***). Panel A: [-15, -1] [-30, -1] [-45, -1] [-60, -1] [-75, -1] [-90, -1] [-105, -1] [-120, -1] [-135, -1] [-150, -1] [-165, -1] [-180, -1] CAR 0.019** 0.046*** 0.051*** 0.062*** 0.061*** 0.057*** 0.053** 0.054** 0.048* (2.45) (4.37) (3.62) (3.82) (3.39) (2.88) (2.42) (2.27) (1.90) (1.54) (0.92) (1.16) Inf vol * ** * * * * * * * * * * (1.95) (1.99) (1.87) (1.82) (1.85) (1.86) (1.81) (1.76) (1.73) (1.72) (1.73) (1.76) Inf vol scaled (1.32) (1.16) (1.26) (0.68) (0.65) (0.71) (0.70) (0.71) (0.75) (0.76) (0.70) (0.69) IV Spd 0.007* 0.008** 0.006* 0.005* 0.005* (1.76) (2.19) (1.85) (1.65) (1.76) (1.58) (1.38) (1.30) (1.27) (1.32) (1.19) (1.20) C-P Imb ** ** * 9.157** 8.666** 7.589** 6.808** 6.247** 5.728** 5.388** 5.096** 4.894** (2.00) (1.99) (1.94) (2.00) (2.13) (2.10) (2.09) (2.09) (2.04) (2.02) (2.03) (2.05) Panel B: Low Governance [-15, -1] [-30, -1] [-45, -1] [-60, -1] [-75, -1] [-90, -1] [-105, -1] [-120, -1] [-135, -1] [-150, -1] [-165, -1] [-180, -1] CAR 0.040*** 0.071*** 0.071*** 0.081*** 0.071** 0.064* (2.83) (3.60) (2.68) (2.66) (2.13) (1.73) (1.25) (1.62) (1.31) (0.92) (0.61) (1.08) Inf vol * * ** ** ** ** ** ** ** ** ** ** (1.80) (1.91) (1.98) (2.07) (2.12) (2.15) (2.11) (2.08) (2.05) (2.04) (2.05) (2.06) Inf vol scaled 0.039* 0.035** 0.033** 0.026** 0.025** 0.024** 0.023** 0.021** 0.020** 0.021** 0.020** 0.019* (1.92) (2.11) (2.45) (2.09) (2.20) (2.21) (2.14) (2.06) (2.05) (2.10) (1.98) (1.92) IV Spd 0.015* 0.015** 0.013** 0.010** 0.010** 0.008* (1.83) (2.41) (2.13) (1.99) (2.08) (1.83) (1.61) (1.56) (1.58) (1.60) (1.54) (1.56) C-P Imb ** ** ** ** ** ** ** ** ** ** ** ** (2.20) (2.44) (2.39) (2.39) (2.50) (2.48) (2.47) (2.48) (2.44) (2.43) (2.42) (2.39) 52

53 Table 6 (Cont.) Comparisons of Levels of Pre-announcement Informed Trading by Cumulative Window Panel C: High Governance [-15, -1] [-30, -1] [-45, -1] [-60, -1] [-75, -1] [-90, -1] [-105, -1] [-120, -1] [-135, -1] [-150, -1] [-165, -1] [-180, -1] CAR *** 0.044*** 0.056*** 0.058*** 0.055** 0.054** 0.047* (1.31) (3.19) (2.72) (3.03) (2.83) (2.42) (2.16) (1.75) (1.48) (1.30) (0.68) (0.70) Inf vol (1.03) (0.97) (0.57) (0.35) (0.36) (0.35) (0.32) (0.28) (0.28) (0.29) (0.33) (0.39) Inf vol scaled (0.51) (0.13) (0.04) (-0.52) (-0.71) (-0.73) (-0.71) (-0.64) (-0.55) (-0.63) (-0.66) (-0.62) IV Spd (0.95) (1.19) (0.92) (0.73) (0.82) (0.80) (0.75) (0.70) (0.71) (0.79) (0.69) (0.70) C-P Imb (-0.08) (-0.56) (-0.58) (-0.47) (-0.45) (-0.51) (-0.50) (-0.53) (-0.62) (-0.61) (-0.51) (-0.41) Panel D: : High Governance Low Governance [-15, -1] [-30, -1] [-45, -1] [-60, -1] [-75, -1] [-90, -1] [-105, -1] [-120, -1] [-135, -1] [-150, -1] [-165, -1] [-180, -1] CAR (0.74) (0.64) (0.38) (-0.08) (-0.40) (-0.18) (-0.22) (0.06) (-0.13) (-0.29) (-0.15) (0.33) Inf vol (0.12) (0.25) (0.56) (0.85) (0.94) (0.98) (0.95) (0.97) (0.96) (0.91) (0.80) (0.71) Inf vol scaled * 0.029** 0.028** 0.026** 0.024* 0.023* 0.023* 0.023* 0.022* (0.74) (1.27) (1.47) (1.68) (2.04) (2.10) (2.08) (1.94) (1.87) (1.92) (1.92) (1.90) IV Spd (0.95) (1.19) (0.92) (0.73) (0.82) (0.80) (0.75) (0.70) (0.71) (0.79) (0.69) (0.70) C-P Imb * ** ** ** ** * * * * * * * (1.69) (2.03) (2.10) (2.01) (2.04) (1.96) (1.93) (1.94) (1.93) (1.89) (1.81) (1.76) 53

54 Table 7 Comparisons of Levels of Pre-announcement Informed Trading by Segmented Window This table presents the OLS regression outputs of regressing the five informed trading measures on dummy (for Panel A, B & C) or Weak-gov dummy (for Panel D). Year-fixed effect, industry-fixed effect and clustering by deal are used. For display simplicity, only the results of the key independent variables are presented. CAR measures the cumulative abnormal return for the target stock during the event window. Informed option volume represents the daily volume of the suspicious informed trades on the target s options. Scaled informed option volume equals Informed option volume divided by total daily option volume. IV spread measures the deviation from put-call parity of the target s options. Call-put volume imbalance measures the imbalance between the target s call and put options. Independent variables include: governance index, percentage cash, deal size, tender offer, hostile, monthly stock return and monthly stock return volatility. is a dummy which equals 1 for cross-border transactions and 0 otherwise. Weak-gov is a dummy which equals one if Governance index of the acquirer is below Governance index refers to the Regulatory Quality (RQ) index from Worldwide Governance Indicators (WGI) constructed by the World Bank; it ranges from -2.5 to 2.5. Percentage cash measures the percentage of cash offered by the acquirer in the M&A deal. Deal size is the value of the transaction in US$ millions. Tender offer is a dummy variable which equals 1 if the acquirer makes a tender offer in the M&A deal and 0 otherwise. Hostile is a dummy variable which equals 1 if the acquirer initiates a hostile takeover in the M&A deal and 0 otherwise. Monthly stock return measures the monthly return of the target stock as at the event day. Monthly stock return volatility is the standard deviation of Monthly stock return. The numbers in the event windows represent the number of calendar days before the initial M&A announcements. The numbers in the event windows represent the number of calendar days before the initial M&A announcements. Statistical significance is indicated at the 10% (*), 5% (**) and 1% levels (***). Panel A: [-15, -1] [-30, -16] [-45, -31] [-60, -46] [-75, -61] [-90, -76] [-105, -91] [-120, -106] [-135, -121] [-150, -136] [-165, -151] [-180, -166] CAR 0.019** 0.028*** * ** (2.45) (3.84) (0.63) (1.72) (-0.18) (-0.65) (-0.62) (0.12) (-0.97) (-0.98) (-2.28) (1.56) Inf vol * * (1.95) (1.74) (0.68) (0.32) (1.21) (1.27) (-0.10) (0.27) (1.41) (1.15) (0.30) (-1.18) Infvol scaled (1.32) (0.70) (0.77) (-1.35) (0.55) (0.75) (0.49) (0.48) (0.92) (0.64) (-0.09) (-0.09) IV Spd 0.007* 0.009** (1.76) (2.14) (0.83) (-0.50) (0.46) (-0.41) (-0.22) (-0.38) (0.49) (0.70) (-0.31) (1.01) C-P Imb ** ** (2.00) (1.50) (0.52) (0.70) (2.23) (-1.50) (-0.04) (0.54) (-0.52) (1.37) (0.64) (-0.11) Panel B: Low Governance [-15, -1] [-30, -16] [-45, -31] [-60, -46] [-75, -61] [-90, -76] [-105, -91] [-120, -106] [-135, -121] [-150, -136] [-165, -151] [-180, -166] CAR 0.040*** 0.031** * *** (2.83) (2.29) (0.04) (0.79) (-0.77) (-0.63) (-1.16) (1.80) (-0.90) (-1.26) (-1.09) (2.72) Inf vol * * * * (1.80) (1.87) (1.82) (1.19) (1.16) (1.92) (-0.15) (0.64) (1.36) (0.31) (-0.42) (-0.87) Infvol scaled 0.039* 0.031* 0.030* * (1.92) (1.70) (1.81) (0.39) (1.47) (1.41) (1.04) (0.89) (1.17) (1.85) (0.43) (0.02) IV Spd 0.015* 0.017** (1.83) (2.46) (1.16) (-0.20) (-0.09) (-0.70) (-0.48) (-0.15) (0.45) (1.33) (0.61) (1.11) C-P Imb ** ** ** (2.20) (2.04) (1.34) (1.02) (2.34) (-0.82) (0.94) (1.00) (-0.23) (1.63) (0.87) (-1.16) 54

55 Table 7 (Cont.) Comparisons of Levels of Pre-announcement Informed Trading by Segmented Window Panel C: High Governance [-15, -1] [-30, -16] [-45, -31] [-60, -46] [-75, -61] [-90, -76] [-105, -91] [-120, -106] [-135, -121] [-150, -136] [-165, -151] [-180, -166] CAR *** * ** (1.31) (3.33) (0.62) (1.69) (0.26) (-0.48) (-0.10) (-0.96) (-0.66) (-0.37) (-2.29) (0.23) Inf vol * (1.03) (0.35) (-1.50) (-1.66) (0.41) (-0.52) (0.55) (-0.15) (0.01) (1.61) (1.02) (-0.89) Infvol scaled ** (0.51) (-0.27) (-0.33) (-2.27) (-0.85) (-0.29) (-0.14) (-0.01) (0.39) (-0.86) (-0.57) (-0.22) IV Spd (0.95) (1.15) (0.05) (-0.43) (0.78) (0.07) (0.45) (0.17) (0.32) (-0.01) (-0.62) (0.48) C-P Imb (-0.08) (-0.83) (-0.87) (0.01) (0.50) (-1.22) (-1.08) (-0.62) (-0.98) (0.36) (0.76) (0.76) Panel D: : High Governance Low Governance [-15, -1] [-30, -16] [-45, -31] [-60, -46] [-75, -61] [-90, -76] [-105, -91] [-120, -106] [-135, -121] [-150, -136] [-165, -151] [-180, -166] CAR *** (0.74) (0.16) (-0.28) (-0.90) (-1.02) (0.57) (-0.24) (1.12) (-0.62) (-0.67) (0.58) (2.73) Inf vol *** ** ** (0.12) (0.95) (1.46) (1.02) (5.15) (2.10) (1.16) (1.26) (1.20) (1.30) (0.93) (2.20) Infvol scaled * 0.035* (0.74) (1.43) (1.25) (1.66) (1.79) (1.38) (1.22) (0.52) (0.66) (1.50) (1.27) (0.84) IV Spd 0.012* *** * 0.012* 0.013** (1.67) (1.49) (-0.95) (0.80) (-3.02) (1.48) (0.20) (1.73) (1.98) (2.06) (1.44) (1.11) C-P Imb * * ** * (1.69) (1.81) (1.63) (1.21) (2.52) (1.19) (1.80) (0.60) (0.57) (0.60) (-0.95) (1.37) 55

56 Table 8 Comparisons of Changes in Pre-announcement Informed Trading by Cumulative Window This table presents the OLS regression outputs of regressing the five informed trading measures on the interaction term between dummy and Event dummy (for Panels A, B & C ) or the interaction term between Weak-gov dummy and Event dummy (for Panel D). Deal-fixed effect and clustering by deal are used. For display simplicity, only the results of the key independent variables are presented. CAR measures the cumulative abnormal return for the target stock during the event window. Informed option volume represents the daily volume of the suspicious informed trades on the target s options. Scaled informed option volume equals Informed option volume divided by total daily option volume. IV spread measures the deviation from put-call parity of the target s options. Call-put volume imbalance measures the imbalance between the target s call and put options. Independent variables include: governance index, percentage cash, deal size, tender offer, hostile, monthly stock return and monthly stock return volatility. is a dummy which equals 1 for cross-border transactions and 0 otherwise. Weak-gov is a dummy which equals one if Governance index of the acquirer is below Governance index refers to the Regulatory Quality (RQ) index from Worldwide Governance Indicators (WGI) constructed by the World Bank; it ranges from -2.5 to 2.5. Percentage cash measures the percentage of cash offered by the acquirer in the M&A deal. Deal size is the value of the transaction in US$ millions. Tender offer is a dummy variable which equals 1 if the acquirer makes a tender offer in the M&A deal and 0 otherwise. Hostile is a dummy variable which equals 1 if the acquirer initiates a hostile takeover in the M&A deal and 0 otherwise. Monthly stock return measures the monthly return of the target stock as at the event day. Monthly stock return volatility is the standard deviation of Monthly stock return. The numbers in the event windows represent the number of calendar days before the initial M&A announcements. The numbers in the event windows represent the number of calendar days before the initial M&A announcements. Statistical significance is indicated at the 10% (*), 5% (**) and 1% levels (***). Panel A: [-15, -1] [-30, -1] [-45, -1] [-60, -1] [-75, -1] [-90, -1] [-105, -1] [-120, -1] [-135, -1] [-150, -1] [-165, -1] [-180, -1] Inf vol (1.12) (1.15) (0.99) (0.89) (0.86) (0.87) (0.79) (0.71) (0.66) (0.64) (0.62) (0.61) Inf vol scaled 0.024** 0.019** 0.017** 0.012* 0.010* 0.010* 0.009* 0.009* 0.009* 0.009* 0.008* 0.007* (2.04) (2.03) (2.18) (1.72) (1.71) (1.85) (1.82) (1.87) (1.92) (1.85) (1.74) (1.73) IV Spd * 0.006* 0.006* 0.005* (0.96) (1.35) (1.13) (1.13) (1.38) (1.37) (1.60) (1.64) (1.74) (1.82) (1.85) (1.80) C-P Imb (1.13) (1.52) (1.42) (1.31) (1.32) (1.29) (1.23) (1.19) (1.12) (1.12) (1.08) (1.12) Panel B: Low Governance [-15, -1] [-30, -1] [-45, -1] [-60, -1] [-75, -1] [-90, -1] [-105, -1] [-120, -1] [-135, -1] [-150, -1] [-165, -1] [-180, -1] Inf vol (1.35) (1.42) (1.34) (1.31) (1.33) (1.35) (1.32) (1.31) (1.28) (1.27) (1.26) (1.25) Inf vol scaled 0.034* 0.034** 0.034** 0.026** 0.023** 0.022** 0.020** 0.019** 0.017* 0.017* 0.015* 0.014* (1.79) (2.14) (2.40) (2.11) (2.13) (2.15) (2.06) (1.99) (1.93) (1.90) (1.74) (1.68) IV Spd * 0.013* 0.012* 0.013** 0.012** 0.011** (1.13) (1.36) (1.28) (1.34) (1.48) (1.51) (1.75) (1.78) (1.92) (2.02) (2.09) (2.16) C-P Imb * * * * * * * * * * (1.27) (1.74) (1.64) (1.66) (1.80) (1.80) (1.83) (1.87) (1.84) (1.84) (1.80) (1.82) 56

57 Table 8 (Cont.) Comparisons of Changes in Pre-announcement Informed Trading by Cumulative Window Panel C: High Governance [-15, -1] [-30, -1] [-45, -1] [-60, -1] [-75, -1] [-90, -1] [-105, -1] [-120, -1] [-135, -1] [-150, -1] [-165, -1] [-180, -1] Inf vol * ** ** ** ** ** ** ** ** ** ** (-1.70) (-1.53) (-2.03) (-2.13) (-2.19) (-2.11) (-2.17) (-2.19) (-2.18) (-2.21) (-2.20) (-2.21) Inf vol scaled (1.39) (1.15) (1.12) (0.71) (0.65) (0.79) (0.80) (0.93) (1.05) (0.97) (0.93) (0.96) IV Spd (0.24) (0.60) (0.34) (0.22) (0.53) (0.43) (0.57) (0.69) (0.71) (0.73) (0.71) (0.60) C-P Imb * * * * (-0.57) (-0.50) (-0.51) (-1.13) (-1.31) (-1.26) (-1.45) (-1.52) (-1.74) (-1.79) (-1.94) (-1.80) Panel D: : High Governance Low Governance [-15, -1] [-30, -1] [-45, -1] [-60, -1] [-75, -1] [-90, -1] [-105, -1] [-120, -1] [-135, -1] [-150, -1] [-165, -1] [-180, -1] Inf vol (1.38) (1.41) (1.40) (1.44) (1.52) (1.54) (1.53) (1.52) (1.50) (1.52) (1.52) (1.51) Inf vol scaled (0.68) (1.13) (1.43) (1.44) (1.52) (1.48) (1.39) (1.25) (1.12) (1.16) (1.06) (0.99) IV Spd * 0.011* 0.011* 0.011* 0.010* 0.010* (0.96) (1.28) (1.26) (1.37) (1.48) (1.58) (1.71) (1.66) (1.72) (1.73) (1.75) (1.85) C-P Imb * * * * * * ** ** ** ** ** (1.32) (1.81) (1.66) (1.74) (1.88) (1.89) (1.95) (2.01) (2.04) (2.08) (2.07) (2.08) 57

58 Table 9 Comparisons of Changes in Pre-announcement Informed Trading by Segmented Window This table presents the OLS regression outputs of regressing the five informed trading measures on the interaction term between dummy and Event dummy (for Panels A, B & C ) or the interaction term between Weak-gov dummy and Event dummy (for Panel D). Deal-fixed effect and clustering by deal are used. For display simplicity, only the results of the key independent variables are presented. CAR measures the cumulative abnormal return for the target stock during the event window. Informed option volume represents the daily volume of the suspicious informed trades on the target s options. Scaled informed option volume equals Informed option volume divided by total daily option volume. IV spread measures the deviation from put-call parity of the target s options. Call-put volume imbalance measures the imbalance between the target s call and put options. Independent variables include: governance index, percentage cash, deal size, tender offer, hostile, monthly stock return and monthly stock return volatility. is a dummy which equals 1 for cross-border transactions and 0 otherwise. Weak-gov is a dummy which equals one if Governance index of the acquirer is below Governance index refers to the Regulatory Quality (RQ) index from Worldwide Governance Indicators (WGI) constructed by the World Bank; it ranges from -2.5 to 2.5. Percentage cash measures the percentage of cash offered by the acquirer in the M&A deal. Deal size is the value of the transaction in US$ millions. Tender offer is a dummy variable which equals 1 if the acquirer makes a tender offer in the M&A deal and 0 otherwise. Hostile is a dummy variable which equals 1 if the acquirer initiates a hostile takeover in the M&A deal and 0 otherwise. Monthly stock return measures the monthly return of the target stock as at the event day. Monthly stock return volatility is the standard deviation of Monthly stock return. The numbers in the event windows represent the number of calendar days before the initial M&A announcements. The numbers in the event windows represent the number of calendar days before the initial M&A announcements. Statistical significance is indicated at the 10% (*), 5% (**) and 1% levels (***). Panel A: [-15, -1] [-30, -16] [-45, -31] [-60, -46] [-75, -61] [-90, -76] [-105, -91] [-120, -106] [-135, -121] [-150, -136] [-165, -151] [-180, -166] Inf vol ** (1.12) (1.19) (0.67) (-0.45) (0.38) (1.15) (-0.51) (0.27) (-0.25) (0.38) (-0.84) (-2.17) Infvol scaled 0.024** * (2.04) (1.34) (1.73) (-0.59) (0.92) (1.49) (1.01) (1.55) (1.55) (0.38) (-0.18) (0.39) IV Spd ** ** 0.006* (0.96) (1.59) (0.04) (0.32) (1.35) (-0.28) (2.02) (1.01) (2.01) (1.68) (0.53) (0.41) C-P Imb ** (1.13) (2.09) (0.92) (0.21) (1.37) (0.48) (1.03) (1.31) (-0.13) (0.57) (-0.98) (0.96) Panel B: Low Governance [-15, -1] [-30, -16] [-45, -31] [-60, -46] [-75, -61] [-90, -76] [-105, -91] [-120, -106] [-135, -121] [-150, -136] [-165, -151] [-180, -166] Inf vol * * (1.35) (1.47) (1.16) (0.45) (1.16) (1.37) (0.08) (0.68) (0.36) (1.12) (-1.69) (-1.86) Infvol scaled 0.034* 0.032* 0.034** (1.79) (1.81) (2.05) (0.45) (1.05) (1.17) (0.89) (0.86) (0.69) (0.95) (-0.19) (-0.31) IV Spd * ** * (1.13) (1.52) (0.46) (1.06) (1.71) (0.82) (2.35) (0.81) (1.97) (1.59) (0.83) (1.39) C-P Imb ** ** 0.006* (0.96) (1.59) (0.04) (0.32) (1.35) (-0.28) (2.02) (1.01) (2.01) (1.68) (0.53) (0.41) 58

59 Table 9 (Cont.) Comparisons of Changes in Pre-announcement Informed Trading by Segmented Window Panel C: High Governance [-15, -1] [-30, -16] [-45, -31] [-60, -46] [-75, -61] [-90, -76] [-105, -91] [-120, -106] [-135, -121] [-150, -136] [-165, -151] [-180, -166] Inf vol * ** * (-1.70) (-1.16) (-2.26) (-1.23) (-1.25) (-0.22) (-0.84) (-0.24) (-0.81) (-0.12) (-0.45) (-1.75) Infvol scaled (1.39) (0.47) (0.63) (-1.13) (0.33) (1.00) (0.66) (1.34) (1.45) (-0.28) (-0.10) (0.60) IV Spd (0.24) (0.88) (-0.18) (-0.29) (0.68) (-0.79) (1.30) (1.05) (1.24) (0.98) (0.14) (-0.37) C-P Imb (-0.57) (-0.13) (0.03) (-1.39) (-0.38) (0.26) (-0.13) (0.31) (-0.80) (-0.33) (-0.89) (1.12) Panel D: : High Governance Low Governance [-15, -1] [-30, -16] [-45, -31] [-60, -46] [-75, -61] [-90, -76] [-105, -91] [-120, -106] [-135, -121] [-150, -136] [-165, -151] [-180, -166] Inf vol (1.38) (1.60) (1.38) (1.32) (1.61) (1.48) (0.78) (0.81) (0.77) (1.03) (-0.34) (0.28) Infvol scaled (0.68) (1.28) (1.55) (1.00) (0.81) (0.61) (0.42) (-0.07) (-0.39) (0.99) (-0.11) (-0.67) IV Spd * ** (0.96) (1.77) (0.73) (1.13) (1.29) (0.81) (1.46) (0.20) (0.97) (1.37) (1.37) (2.66) C-P Imb ** * ** * (1.32) (2.49) (1.08) (1.78) (2.35) (1.03) (1.80) (1.65) (1.07) (1.65) (-0.07) (-0.95) 59