The Short and Long Run Post-merger Stock Performance
of U.S. Firms Involved in China Inbound M&A
Master Thesis
Master in International Finance Amsterdam Business School
University of Amsterdam
Student: Qindong Wang
Supervisor: Prof. Stefan Arping September 2014
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Abstract
This research investigates the effect of China’s inbound M&A on the wealth of acquirers’ shareholders in both short run and long run. We shed light on the impact of China’s inbound M&A on U.S. acquirers. We firstly summarised the findings of existing literatures regarding post-merger stock performance. The majority of the existing researches reported an insignificant negative abnormal return in the short run; for researches studying the long run post-merger stock returns, different extents of negative abnormal returns have been found in different event windows and samples. By applying Fama-French three-factor model for the short run study and Carhart four-factor model for the long run study, we find the result of the short run average cumulative abnormal returns supports our hypothesis. The result of our analysis for the long run average cumulative abnormal returns is not in line with the hypothesis we made that as the acquirers gradually adapt to the Chinese market, complete the integrations and start creating synergies over time, the shareholders of the acquirers will have more positive or less negative cumulative abnormal returns in the second and third year.
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Table of contents
1 Introduction ………,…. 1
2 Theory, Background and Literature Review…….…….………... 5
2.1 Fama French Three-factor Model ………..……… 5
2.2 Carhart Four-factor Model ………..………... 5
2.3 Cross-border M&A---A Great and Complicated Project ………... 6
2.4 Empirical Studies ………... 7
3 Hypotheses ……..………...……….... 11
3.1 Short Run Studies Hypotheses ………. 11
3.2 Long Run Studies Hypotheses ………. 12
4 Methodology ………..……….... 14
4.1 Data Selection ...………... 14
4.2 Event Windows …….………... 15
4.3 Regression Models ...……… 16
5 Data and Descriptive Statistics ……..……… 20
6 Result and Analyses ………. 23
7 Conclusion ………. 30
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1. Introduction
Thirty years’ exponential GDP growth and large amount of surpluses on current account lead China to be an increasingly important player in Mergers and Acquisition, in both outbound and inbound investment. Due to the constraints of the policy of China’s government, the international direct investment into China commonly adopted the way of new investment. 2002 World Investment Report showed that in 2001 China's foreign direct investment is $46.9 billion, less than 5% is through the way of the transnational merger and acquisition; the rest are all through new investment. However, China’s accession to WTO at the end of 2011 became a turning point. In November 2002, the government successively promulgated "The Transfer of Shares of Listed Stated-owned Companies and Foreign Legal Person Share Purchase Announcement” and ‘Interim Provision of State-owned Enterprises Reorganisation Using Foreign Investment Capital”, both of which are big changes of China’s strategy of utilising foreign investment capital. Inbound M&A accounted for 3.90% of foreign direct investment in China in 2002. Stimulated by the two policies introduced above, this figure steeped up to 21.50% in 2005, hitting an all-time record high.
Figure 1a: China’s Inbound M&A as A Percentage of Foreign Direct Investment
Source: Thompson Financial 0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 2000 2001 2002 2003 2004 2005
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Driven by the policy of “going global” and the needs to upgrade technology and to develop globally competitive firms, China M&A deal numbers recovered from multi-year lows in the first half of 2013, increasing by more than 40% in the second half. According to the report of PwC, China outbound M&A recovered with more deals announced in the second half of 2013 than in any earlier half-year period: and on a full-year basis, outbound M&A compared well with the last few years, although the soft first half meant to new records in 2013. In the meanwhile, foreign inbound M&A was flat. Japanese investment has declined sharply over the last two years as has investment from the US. Before this slowdown period, inbound foreign investment has risen from $72bn in 2005 to $123bn in 2011, regardless of various difficulties and obstacles foreign companies face while trying to do investments in China. As China continue to open strategically important sectors to foreign investment, aiming to gain overseas expertise and accelerate its economic structural reform, the relatively cheaper assets in China will remain to be attractive to foreign investors of both upstream and downstream. According to China’s 12th Five Year Plan, seven strategic emerging industries are expected to boost domestic consumption in order to reform its export-led economy. Therefore, opening these favoured sectors is deemed as a strategy to help China meet its social goals such as accelerating urbanisation and improving public healthcare and pensions.
Given the figures and facts above, it is foreseeable that international companies will keep flowing into Chinese market. As China’s middle class population is growing rapidly, many ambitious multinational companies from developed countries are keen to acquire Chinese companies, thereby sharing the growth of this gigantic market. Given this background, our paper attempts to investigate the effect of China’s inbound M&A on the wealth of acquirers’ shareholders in both short run and long run. Furthermore, we try to shed light on two questions: is there any pattern on this issue; and did firms of some sectors obviously outperform those of other sectors?
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The existing literatures regarding China Mergers and Acquisitions mainly focus on laws and regulations or the trend of the market. Moreover, some empirical analyses have been conducted on China outbound M&A. Gu and Reed (2013) show that China’s outbound M&As have not decreased the wealth of shareholders of Chinese acquiring firms; shareholders of Chinese acquiring firms have not fared worse due to China’s “Go Global” policy of encouraging outward investment by Chinese firms. The very few researches focusing on China inbound M&A only analysed the benefits accrued to the shareholders of Chinese target firms. Chen (2012) demonstrates that mergers and acquisitions have significant effects on the performance of target State-owned Enterprises due to misconducted managerial strategies adopted by Western acquirers; acquisition management and acquisition performance are positively correlated. Song (2012) finds out that there are statistically significant and positive abnormal returns for shareholders of Chinese acquiring firms surround the announcement date, however, there generally have been balanced off over the next ten to fifteen trading days thereby leaving the shareholders of Chinese acquiring firms with no significant benefit from their M&A activities.
Mergers and acquisitions are regarded as an important and effective strategy to enter into new market, acquire new channels and eliminate current or potential competitors. A prevailing belief is that mergers and acquisitions can enhance business by creating post-merger synergies. The leaks and/or announcements of mergers and acquisitions will usually have immediate impact on the stock prices of target companies, as a consequence in the stock market which will cause investors to reconsider companies’ expected profitability (Panayides and Gong, 2002). According to the Efficient Markets Hypothesis of Fama (1970), in an efficient market, prices reflect all the publicly available information on an underlying asset. The Synergy Trap Hypothesis of Sirower (1997) argues that during the short period surround the announced date of mergers and acquisitions, the bidder firm’s stock price is negatively influenced and the
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target firm’s stock is positively influenced. Therefore, the change of the stock’s price can be considered as the revision of the investors’ expectation pertaining to the companies’ future profitability.
Nevertheless, there is no empirical research study the benefits accrued to the shareholders of acquiring firms involving in China inbound M&A. This research aims to examine the effect of acquiring Chinese firms on long-run financial performance of listed companies in US. Although the volume and deal value of China inbound M&A have been increasing all the time, whether these deals have imposed positive impact on the acquiring firms in long run remain to be seen.
The motivation of our research is to study the short and long run stock performances of the acquiring companies involved in China inbound M&A. Historically, the companies from Japan and the U.S. contributed the most capital of foreign direct investment in China. In order to obtain a standardised benchmark, we decide to only study the acquirers from one country, Moreover, because of the convenience to gather the data and read the documents written in English, our research targets are only the acquiring firms in the U.S. The mergers and acquisitions deal information are collected from Thompson One and ZEPHYR database.
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2. Theory, Background and Literature Review
2.1 Fama French Three-factor Model
The traditional capital asset pricing model (CAPM) includes only one variable to illustrate the returns of a portfolio or stock with returns of the market as a whole. Fama and French observed that two classes of stocks had outperformed the market as a whole: small caps and high book-to-market ratio stocks. Therefore, they constructed a new pricing model taking into account the stock capitalisation and book-to-market ratio to measure the historical excess
returns of small caps over big caps and of value stocks over growth stocks. However, a number of empirical studies have argued that Fama and French model’s market value of
equity factor performs poorly. Many argue that the additional two factors of the Fama-French three-factor model are purely empirical. Unlike he CAPM, there is no underlying theory for Fama-French three-factor model. Although the three factor model needs additional date compared to the CAPM (the SMB factor and the HML factor), the higher costs in using the three factor model compared to the CAPM is not justified according to Bartholdy (2002), because the three factor model doesn’t seem to outperform the CAPM significantly on individual stock returns estimation.
2.2 Carhart Four-factor Model
Carhart (1997) constructed a 4-factor model using Fama and French’s (1993) 3-factor model plus an additional factor capturing Jegadeesh and Titman’s (1993) one-year anomaly. This
4-factor model is consistent with a model of market equilibrium with four risk 4-factors. It can also be interpreted as a performance attribution model, where coefficients and premium on the factor-mimicking portfolios indicate the proportion of mean return attributable to four
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elementary strategies: high versus low beta stocks, large versus small market capitalisation stiocks, value versus growth stocks, and one-year return momentum versus contrarian stocks. This model further improved Fama and French’s model, thus it will be applied in this thesis
research.
2.3 Cross-border M&A---A Great and Complicated Project
If a correct merger and acquisition strategy can be perfectly implemented, it will undoubtedly bring a qualitative leap to the company. But like setting up a company, mergers and acquisitions, especially cross-border m&a is a very complicated project, it has been involved in enterprise strategy, management, finance, law and even culture and custom of the host countries. Enterprises' management and policy makers must learn through professional training and long-term M&A practice to obtain the skills required. In addition, the enterprises must have the assistance of an investment bank, law firm, accounting firm and many other specialized agencies to close the deal at the lowest possible cost with highest efficiency. Roughly speaking, inbound M&A in China consists of the following three steps:
Comprehensive assessment of M&A---before the formal start of the deal with the seller, the enterprise must fully assess the profitability of the target company, advantages and disadvantages, development prospects, current situation and future of the industry, especially the development of the industry in China in the future prospects, as well as whether the target company has the resources to help the acquirer expand business in the existing market and Chinese market.
Bargaining---if the valuation results show that this M&A deal is feasible, the enterprise negotiates with the target company, trying to close the deal with right price and reasonable terms. Because the sensitivity of the mergers and acquisition deals, this
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step at the early stage is usually conducted by investment banks, law firms and accounting firms of both parties.
Integration---The enterprise needs to implement the integration plan as soon as possible after closing the deal, reasonably use the resource to develop after the merger, and use the Earn-out agreement to ensure seller is still doing its best to help the enterprise achieve promised earning level pre-merger and accomplish the transition smoothly.
2.4 Empirical Studies
There are many previous researches studied about the effect of mergers and acquisitions on stock returns, but mostly only include a short period before and after the announcement date. Malatesta (1983) reported that most acquiring firms have gained no or even negative returns due to M&A transactions. In general, the shareholders of acquiring firms hold a neutral or negative attitude towards the M&A transactions. They hardly believe that the premium paid to the target company can be compensated for the synergies in the near future. Halpern(1973), Mandelker (1974) and Franks, Broyles and Hecht (1977) all found that the target firms have benefited returns above the average in the short run post-merger. Morck et al. (1988) analysed 57 transactions between 1980 and 1987 and found that the acquiring firms earned a positive return of 2.88% during one day before and two days after the announcement date. They also used 115 transactions and found a loss of -4.09% in the same time window of three days before and after the announcement date. These results did not support the prevailing positive comments on the merging wave of conglomerates. Franks et al (1991) analysed 399 transactions from 1975 to 1984 and found a significant positive return of 28.04% for the target companies and a slight negative return of -1.02% for the acquiring firms 5 days before and after the announcement date.
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Currently, there are very few researches studied about M&A in China due to various reasons, such as small sample and limited data source. Agyenim et al. (2008) analysed 27 cross-border M&A deals in China took place in the stock exchanges of Shanghai and Shenzhen between 2000 and 2004. The study finds that cross-border M&A in China are primarily motivated by market development and create value for Chinese acquiring firms. Tuan et al. (2007) used a sample of 22 tender offer bids between 2002 and 2006 to examine the profitability of merger arbitrage strategies. They found out the average cumulative abnormal return of target firms for voluntary tender offers is significantly positive from 30 days before the announcement date to the announcement date. Gu and Reed (2013) applied an event window methodology to study 135 deals of China’s outbound M&A and argued that overseas M&A (OMA) have not decreased the wealth of shareholders of Chinese acquiring firms; shareholders of Chinese acquiring firms have not fared worse due to China’s “Go Global” policy of encouraging outward investment by Chinese firms. Chen (2012) demonstrates that mergers and acquisitions have significant effects on the performance of target State-owned Enterprises due to misconducted managerial strategies adopted by Western acquirers; acquisition management and acquisition performance are positively correlated. Song (2012) finds out that there are statistically significant and positive abnormal returns for shareholders of Chinese acquiring firms surround the announcement date, however, there generally have been balanced off over the next ten to fifteen trading days thereby leaving the shareholders of Chinese acquiring firms with no significant benefit from their M&A activities.
There are also some long run post-merger stock return studies. It is harder to conduct long run studies because there might be various other factors affecting the stock price. There is no very effective methodology to isolate the influence of merger and acquisitions from other factors such as management strategy, industry specific situation, corporate debt structure, etc. Moreover, the synergies might also be caused by macro-economic trend. In general, the
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results of long run stock return studies highly depend on the benchmark used. The majority of the existing studies adopted benchmark models such as CAPM, Fama-French three-factor model, market risk-adjusted model, etc. In addition, an event study has been employed by most literatures. Currently, there is no empirical research studies the benefits accrued to the shareholders of acquiring firms involving in China inbound M&A. This research posits to investigate the effect of acquiring Chinese firms on long run financial performance of listed companies in US. Although the volume and deal value of China inbound M&A have been increasing all the time, whether acquiring cheap assets will impose positively affect the wealth of the shareholders of acquirers is still inconclusive.
Frank et al. (1999) constructed an eight-factor model as benchmark to analyse 399 transactions and find a positive average monthly return of 0.05%. They also reported that hostile takeovers outperform friendly takeovers by 0.46%. Bruner (2002) applied an event window between 1978 and 2001 for 44 acquiring firms, concluding that on average acquiring firms earned no abnormal share returns post mergers and acquisitions. Rau and Vermaelen (1998) found the smallest statistically significant negative ACAR of -4% of 3968 transactions with an event window of 36 month between 1980 and 1991. By contrast, Loughran and Vijh (1997) studied 434 transactions between 1970 and 1989 with an event window of 1250 days and report the largest statistically significant negative ACAR of -14.3%.
10 Researcher Country /Region Period (years) Sample Size Event Window (days) ACARs of Acquirer Franks et al. US 1975-1984 399 (-5,+5) -1.02% Morck et al. US 1975-1987 326 (-2,+1) -0.70% 1975-1979 120 0.23% 1980-1987 115 -4.09%
Kaplan and Weischbach US 1971-1982 271 (-5,+5) -1.49% Smith and Kim US 1980-1986 177 (-5,+5) 0.50% Marquiera et al. US 1977-1996 47 (-40,+40) -4.79% Mulherm and Boone US 1990-1999 281 (-1,+1) -0.37% Campa and Hernando EU 1998-2000 181 (-1,+1) 0.61%
Holmen and Knof Sweden 1985-1995 121 (-5,+5) 0.32% Agyeim et el. China 2000-2007 27 (-20,+20) 4.43% Tuan et el. China 2002-2006 22 (-30,30) 3.87% Gu and Reed China 1994-2009 135 (-1,+1) 0.98% Song China 1990-2008 279 (-15,+15) 0.12%
Table2b: Empirical Results of Short Run Post-merger Stock Return Studies
Researcher Country /Region Period (years) Sample Size Event Window (Months) ACARs of Acquirer Loughran & Vijh US 1970-1989 434 (0, +1250) days -14.20%
Franks et al. US 1975-1984 399 (0, +36) 0.05% Limmack UK 1977-1986 448 (0, +24) -4.67% Rau & Vermaelen US 1980-1991 3968 (0, +36) -4.00% Gregory US 1984-1992 452 (0, +500) days -18.00% Datta et al. US 1993-1998 437 (0, +36) -10.67%
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3. Hypotheses
3.1 Short Run Studies Hypotheses
As it can be seen in Table 2a, the previous researches mostly report an insignificant negative abnormal return in the short run around the announcement date of the mergers and acquisitions in the U.S. By contrast, all of the studies we are aware of regarding the short run post-merger stock return in China show positive abnormal returns. The empirical results prove that M&A transactions generally favoured the shareholders of acquiring firms in the short run in China; however, foreign investors seeking for target companies in China will face more unprecedented competition. It is particularly time-consuming and might also be costly to pass through three hurdles of acquiring Chinese firms, namely, national security review, anti-trust review and industry access restrictions.
A recently published U.S.-China Business Council (USCBC) study reflects these policy-related concerns of direct investment in China among leading American companies. In its “2010 Member Priorities Survey Results” published on 17 November, U.S.-China Business Council concluded that while most U.S. companies still hold strong commitments to the Chinese market and stayed profitable in China over the past year, the market is generally less FDI friendly compared to three years ago.
Therefore, we expect to observe a positive average cumulative abnormal return around the announcement date for the shareholders of U.S companies acquiring Chinese companies.
Hypothesis 1:
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3.2 Long Run Studies Hypotheses
A substantial body of evidence indicates that M&A premium is on average 20 to 30 percent above a target's pre-acquisition share price. Such loses on the wealth of shareholders of acquiring firms cannot be easily compensated by the synergies created within two or three years post-merger. The empirical results of long run post-merger stock performance of acquirers in Table 2b also support this commonly accepted belief, only one study reports positive average abnormal cumulative returns (ACARs), the rest all show negative ACARs. Considering more complexities involving in cross-border M&A, it is prudent to make a hypothesis that the shareholders of U.S. companies acquired Chinese companies have also gained negative abnormal return in 3 years after the announcement date.
Hypothesis 2:
Even if it is relatively cheaper to acquire the assets in China, it will cost some time to absorb the benefits and synergies brought by Chinese target companies. For those companies who want to expand business in China, it will also take them some time to get accustomed to the habit and culture of local consumers and face the competition of the existing local companies or joint ventures. In total, China's inbound and outbound M&A deals in 2010 amounted to $236 billion out of a global total of $2.8 trillion, or a little more than 8 percent. The consolidation in consumer retail, real estate, healthcare, technology and industrial sectors not only powered domestic M&A but also catalysed inbound M&A. Thus, we expect to observe that the U.S. companies acquired Chinese companies of booming sectors outperform those acquired Chinese companies of less booming sectors, i.e., some companies in specific sectors have more positive or less negative cumulative abnormal returns than others. Moreover, as the acquirers gradually adapt to the Chinese market, complete the integrations and start creating
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synergies over time, we expect that the shareholders of the acquirers will have more positive or less negative cumulative abnormal returns in the second and third year.
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4. Methodology
4.1 Data Selection
Our research aims to study the short and long run stock performances of the acquiring companies of China inbound M&A. The most active participants of China inbound M&A are Japanese and the U.S. firms. To maintain a standardised benchmark, we decide to only study the acquirers in one country, Moreover, because of the convenience to gather the data and read the documents written in English, our research targets are only the acquiring firms in the U.S. The mergers and acquisitions deal information are collected from Thompson One and ZEPHYR database.
Our search criteria are set as listed companies in the U.S. acquired companies in China from 1 January 2003 to 31 December 2010. We extract those only traded on OTC, retaining all the U.S. companies which are listed in NYSE and NASDAQ, We also eliminate those companies which have been delisted or acquired during 3 years after the deal announcement date. To ensure the transactions will have certain extent of influence to the wealth of the shareholders of acquiring firms, we only select the transactions with deal value over $10 million.
The reason we select the deals between 2003 and 2010 is that China’s inbound M&A entered into a new era since the end of 2012. As we illustrated in section 1, China’s accession to WTO at the end of 2011 became a turning point. The implementation of "The Transfer of Shares of Listed Stated-owned Companies and Foreign Legal Person Share Purchase Announcement” and ‘Interim Provision on State-owned Enterprises Reorganisation Using Foreign Investment Capital” since November 2002 increased the utilisation of foreign investment capital. The inbound M&A as a percentage of foreign direct investment (FDI) soared from 3.90% in 2002 to 21.50% in 2005, hitting an all-time record high. By choosing
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this period, we will be able to acquire more samples which are more representative at the same time. Eventually, we obtain 58 deals as our sample.
All the monthly and daily stock prices are downloaded from Thompson Datastream and Yahhoo! Finance. The monthly and daily stock prices of the 58 stocks are the adjusted closing prices at the end of each day or month in different event windows. Here the adjusted price is defined as the closing price, which has been historically adjusted for dividends and rights issues. We also categorise the 58 companies into different sectors according to the information gathered from Bloomberg.
4.2 Event Window
Event windows are constructed to calculate the cumulative abnormal returns in different period. The short run study is designed for a maximum pre-merge event window of five days and a maximum post-merger event window of five days. The long run study is designed for a maximum post-merger event window of three years. Different event windows are constructed for the purposes of comparing the cumulative abnormal returns of different periods.
Short run event window are defined as:
[-5;+5] = the event window representing 5 trading days prior to the announcement date and 5 trading days post to the announcement date.
[-3;+3] = the event window representing 3 trading days prior to the announcement date and 3 trading days post to the announcement date.
Long run event window are defined as:
[0;+3] = the event window representing 3 financial years, or 756 trading days, or 36 months post to the announcement date.
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[0;+1] = the event window representing 1 financial year, or 252 trading days, or 12 months of one year post to the announcement date.
[0;+2] = the event window representing 2 financial years, or 504 trading days, or 24 months of two years post to the announcement date.
[0;+3] = the event window representing 3 financial years, or 756 trading days, or 36 months of the third year post to the announcement date.
4.2 Regression Model
As introduced in section 2, we will apply the Fama-French three-factor model to study the short run abnormal returns. Fama and French (1992) studied the determinant factors of differences of stock returns in U.S. stock market and found that the beta value of the stock market cannot explain the differences of the stock returns, but the market capitalization, book-to-market ratio and price-to-earnings ratio of listed companies can explain the difference between stock returns. Fama and French argued that the abnormal returns illustrated above compensate for the risk factors which beta of CAPM could not reflect.
In the capital asset pricing model (CAPM) and other traditional theory, all the risk premium of a portfolio reflected by β. But this model had met many challenges of explaining the present situation of the stock market returns, such as January effect. Fama and French (1992) observed the variations of market value and found that companies with smaller capitalization and lower price-to-book are more likely to achieve returns better than the average of the market. Thus the three-factor model introduces two new explanatory variables: (i) stock capitalization and (ii) price-to-book value together with the market index in the CAPM to estimate stock returns, namely:
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Where:
Rit = the expected return of stock i
Rft = the risk-free rate
βi = the market beta
Si = the coefficient of factor sensitivity towards small company shares
SMBt = small minus big, the difference between the expected return on a portfolio of small
firms’ shares and the expected return on a portfolio of big firms’ shares
Hi = the coefficient of factor sensitivity towards high book-to-market ratio firms’ shares
HMIt = high minus low, the difference between the expected return on a portfolio of high
market ratio firms’ shares and the expected return on a portfolio of low book-to-market ratio firms’ shares
εit = the error terms
The study of Griffin (2002) shows that Fama French three-factor model is country specific and argues global factors have less influence on time-series variations in stock returns than local factors. Fama and French (1996) admitted that the model will have complete influence only if it explains the preference of investors and the structure of an economy.
To better assess the long run abnormal return, we apply the Carhart four-factor model which is an improvement of the Fama-French three-factor model. Carhard included a momentum factor reflecting the tendency of a stock price to continue increasing if it is rising and to continue declining if it is declining. Carhart constructed the 4-factor model by using Fama-French three-factor model plus an additional factor an additional factor capturing Jegadeesh and Titman’s (1993) one-year momentum anomaly:
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t = 1, 2, · · ·, T
Where:
= the return on a portfolio in excess of the one-month T-bill return = the excess return on a value-weighted aggregate market proxy
SMBt = small minus big, the difference between the expected return on a portfolio of small
firms’ shares and the expected return on a portfolio of big firms’ shares
HMIt = high minus low, the difference between the expected return on a portfolio of high
market ratio firms’ shares and the expected return on a portfolio of low book-to-market ratio firms’ shares
= one year momentum in stock returns
Carhart added the one-year momentum return factor (PR1YR) to the equation, supplementing the explanation of the model compared to the Fama-French three-factor model. According to Carhart (1997), the fourth factor significantly improves the accuracy of three-factor model because the three-factor model did not concern the errors of last year’s stock portfolios. Carhart attempted to significantly eliminate the patterns in pricing errors. This provides a well performing model on describing cross-sectional variation in average stock returns.
Finally, we summarise the to get average cumulative abnormal return (ACAR):
Where:
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= the actual return for security i for day t
∑
Where:
= daily cumulative average abnormal return for the sample for the day t=K to t=L
∑
Where:
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5. Data and Descriptive Statistics
As mentioned in Section 4.1, we eventually obtained 58 companies in our sample. According to the information provided on Bloomberg, we categorise the samples into eight different sectors, namely, communications, consumer discretionary, consumer staples, financials, health care, industrials, materials and technology. There are only two acquiring companies acquired target companies in a different sector. Both of the irrelevant M&A are done by big financial institutions (Goldman Sachs and AIG). The distribution of the sectors of the 58 acquiring companies is present in Figure 5a below.
Figure 5a. Sector Distribution of the Acquiring Firms
It is rather evident that the targets in industrials, materials and technology are much more favoured than other sectors, accounting for 56.90% in total. The remaining five sectors only account for 43.10% of the whole sample. In terms of the deal value, the highest is $2 billion and the lowest is $10.3 million. The average deal value of the sample is $130.77 million.
Communications 5.17% Consumer Discretionary 12.07% Consumer Staples 6.90% Financials 6.90% Health Care 10.34% Industrials 24.14% Materials 13.79% Technology 20.69%
Sector Distribution
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Table 5a. Short Run ACAR
ACAR SD Max Min Skew Kurt (-3;+3) 0.002358 0.024454 0.117048 -0.032658 3.022362 11.827057
(0.0359)
(-5;+5) 0.000247 0.008623 0.042396 -0.013542 2.447205 9.891166
(0.0410)
*The p-values of t-statistics under significance level of 5% are reported in the parentheses
For the short run study, we observe a positive average cumulative abnormal return for the two event windows. The ACAR of 3 days and 5 days before and after the announced date are 0.24% and 0.025%, respectively. The wide range between maximum and minimum ACARs and the standard deviation presented in Table 5a indicate that although on average there is a positive cumulative abnormal return in the short run, the individual return is specific to each acquiring firm. The positive skewness indicates a longer tail on the right side. The excess K of both event windows are larger than 3, which means a more flat distribution than normal distribution, with frequent medium to large changes and less frequent very large changes.
Table 5b. Long Run ACAR
ACAR SD Max Min Skew Kurt
(0;+1) -0.001464 0.034314 0.073142 -0.093585 -0.218841 0.439470 (0.0041) (0;+2) -0.007653 0.027142 0.075433 -0.122290 -1.297425 6.237568 (0.0038) (0;+3) -0.009138 0.024158 0.037473 -0.132891 -2.643426 12.350838 (0.0002)
*The p-values of t-statistics under significance level of 5% are reported in the parentheses
The average cumulative abnormal return of the event windows of one, two and three years after the announced date are -0.15%, -0.77% and -0.91, respectively. The ACAR (0;+3) has a longer tail on the left side than the ACAR (0;+2) and ACAR (0;+1). The ACAR (0;+1) has an excess K less than 0, which means a flatter distribution with very frequent small changes
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and less frequent very large changes. By contrast, the distribution of the ACAR (0;+2) and ACAR (0;+3) have more peakedness, with a kurtosis of 6.24 and 12.35, respectively. According to Table 5b, it is evident that the average cumulative abnormal returns of the sample we observed became more negative over the three years after the announced date. In the meanwhile, we observe a big gap between the maximum ACAR and the minimum ACAR in each event window. This result might be in line with our hypothesis that the acquirers in some sectors outperformed the others. We will analyse and discuss further regarding this observation in section 6.
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6. Result and Analysis
As we introduced in section 1, the deal volume of China inbound M&A keeps an increasing trend after China obtained the accession to WTO at the end of 2002. Our sample consisting of 58 listed U.S. companies acquired Chinese companies is in line with the report we quoted in section 1. There were 9 deals completed in 2005, which is three times as in 2003. Although there was a temporary drop in 2006, it immediately bounced to 9 deals in 2007. Surprisingly, we found that there were 11 deals completed in 2008 while the financial crisis was rampant in the U.S. This might because the acquirers who needed to expand their business were unconfident about the outlook of domestic economy, thus acquiring cheap assets overseas, in this case---China, became a better alternative. The deal volume decreased in the next two years due to the spread of the financial crisis.
Figure 6a. Deals Completed in Each Year from 2003 to 2010
The deal of highest value was Bank of America acquired a 9% stake in China Construction Bank Corp (CC), from Chinese state-owned China SAFE Investments Ltd, for 20.666 billion
0 2 4 6 8 10 12 2003 2004 2005 2006 2007 2008 2009 2010
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Chinese yuan ($2.5 billion US). Concurrently, BA was granted an option to raise its stake to 19.9% from 9% and planned to partially exercise this option to raise its stake to 10.75% from 8.18% by acquiring a further 2.57% stake, or 6 billion ordinary shares, in CC. The deal of lowest value was US-based plastic bottles manufacturer holding company Silgan Holdings Inc acquired Vac Vem Dongguan for $10.3 million.
The result of the short run average cumulative abnormal returns supports our hypothesis that in the short run, the China inbound M&A will bring positive abnormal returns to the shareholders of the acquiring firms. Both of the event windows we have tested report an insignificant cumulative abnormal return on average. In addition, as we have shown in Table 5a, the ACAR of 3 days before and after the announced date is larger than that of 5 days before and after the announced date. This finding is similar with the research of Song (2012). He found out that there are positive abnormal returns for shareholders of Chinese acquiring firms around the announcement date, however, there generally have been balanced off over the next ten to fifteen trading days thereby leaving the shareholders of acquiring firms with no significant benefit from their M&A activities.
The wide range between maximum and minimum ACARs presented in Table 5a indicates that although on average there is a positive cumulative abnormal return in the short run, the individual return is specific to each acquiring firm. Here we listed 10 companies with the highest and lowest average abnormal returns for both event windows in Table 6a and Table 6b. There is no pattern showing that the acquirers of some sectors outperformed the acquirers of other sectors. The distribution of the winners and losers is quite dispersed in different sectors. The gap between the highest ACAR and the lowest ACAR is lower in the event window of three days before and after the announced date. Moreover, we find that some losers in the event window (-3;+3) became winners in the event window (-5;+5). This finding further proves that the individual return is specific to each acquiring firm and there is no pattern.
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Table 6a. Companies with Highest and Lowest ACAR (-3;+3)
Panel A Panel B
Company ACAR Sector Company ACAR Sector
UNIVERSAL ELECTRONICS 11.70% Technology MTS Systems -3.27% Industrials
MONSTER WORLDWIDE 10.14% Communications YAHOO! -3.04% Communications
GENERAL STEEL 5.87% Materials LEGGETT&PLATT -2.79% Consumer Discretionary
MORGAN STANLEY 2.44% Financials Zimmer Holdings -2.68% Health Care
PERKINELMER 1.84% Health Care NeoStem -2.11% Health Care
YRC WORLDWIDE 1.28% Industrials CHINA GREEN AGRICULTURE -1.81% Materials
Scientific Games 1.26% Technology SOHU.COM -1.68% Communications
BEST BUY 1.23% Consumer Discretionary Carlisle Cos -1.62% Industrials
CNET Networks 1.07% Technology EBAY -1.38% Consumer Discretionary
CHINA AUTOMOTIVE SYSTEMS 1.03% Consumer Discretionary JOY GLOBAL -1.07% Industrials
Table 6b. Companies with Highest and Lowest ACAR (-5;+5)
Panel A Panel B
Company ACAR Sector Company ACAR Sector
UNIVERSAL ELECTRONICS 4.24% Technology ADC Telecommunication -1.35% Technology
NeoStem 2.56% Health Care Jinpan International -1.33% Materials
PERKINELMER 1.86% Health Care AIG -1.06% Financials
CHINA AUTOMOTIVE SYSTEMS 1.09% Consumer Discretionary Carlisle Cos -1.05% Industrials
Scientific Games 1.02% Technology 3Com -1.00% Technology
BALL CORPORATION 0.51% Materials LEGGETT&PLATT -0.77% Consumer Discretionary
MTS Systems 0.51% Industrials Zimmer Holdings -0.75% Health Care
MONSTER WORLDWIDE 0.50% Communications JOY GLOBAL -0.67% Consumer Discretionary
Amdocs 0.49% Technology GOLDMAN SACHS -0.67% Financials
26
The result we observed for the long run average cumulative abnormal returns is on the opposite of the hypothesis we made that as the acquirers gradually adapt to the Chinese market, complete the integrations and start creating synergies over time, the shareholders of the acquirers will have more positive or less negative cumulative abnormal returns in the second and third year. The average cumulative abnormal returns of one, two and three years after the announced date are -0.15%, -0.77% and -0.91%, respectively. Therefore, on average there is implication that the post-merger synergies and integrations can increase the wealth of the shareholders of acquiring firms.
Table 6c. The Long Run ACARs of Different Sectors
Sector (0;+1) (0;+2) (0;+3) Communications -1.12% -2.00% -1.19% Consumer Discretionary 1.42% 0.38% -0.45% Consumer Staples 0.87% -0.03% 0.30% Financials 2.03% -2.07% -2.72% Healthcare -1.44% 0.24% -0.95% Industrials 0.58% -0.63% -1.12% Materials -2.40% -1.06% -0.71% Technology -0.59% -1.40% -0.80%
*The results of t-statistics are missing due to small sample size
Among the eight sectors, only consumer staples has a positive average cumulate abnormal return of three years after the merger, the rest all have a negative average cumulative abnormal return of different levels. Communications, financials and industrials performed poorly compared with other sectors in the long run, although financials has the highest ACAR in the first year. As we introduced in section 1, consumer discretionary, healthcare, industrials and technology are more favoured by the Chinese government to bring in foreign investment, accelerating the reform of the Chinese economy and boosting the domestic demands. However, according to the result of our research, acquiring those cheap assets in China cannot
27
bring excess wealth to the shareholders of acquiring firms in the U.S. The long run ACARs of each firm in different event windows are listed in Table 6d.
28
Table 6d. Long Run ACARs C onsume r Di scre ti onary AC AR Industri al s AC AR
C ommuni cati ons AC AR Company (0;+1) (0;+2) (0;+3) Company (0;+1) (0;+2) (0;+3)
Company (0;+1) (0;+2) (0;+3) BEST BUY -3.64% -3.79% -3.39% YRC WORLDWIDE 2.85% -12.23% -13.29%
MONST ER WORLDWIDE -3.10% -3.82% -5.21% (0.2625) (0.0346) (0.0020) (0.5989) (0.6694) (0.0922)
(0.0016) (0.0000) (0.0000) EBAY 5.27% 0.03% -0.35% HONEYWELL 0.87% -1.31% -0.79%
YAHOO! 7.31% 3.34% 3.75% (0.0000) (0.0006) (0.0442) (0.0008) (0.0000) (0.0000)
(0.0023) (0.0267) (0.0028) HOME DEPOT -1.30% -0.67% -1.23% BOEING -3.06% 0.36% -0.07%
SOHU.COM -7.56% -5.52% -2.11% (0.1385) (0.0045) (0.0051) (0.0869) (0.0006) (0.0000)
(0.2043) (0.0748) (0.0110) AMAZON.COM 1.34% -0.91% 0.59% JOY GLOBAL 0.93% 1.84% -0.27%
(0.3985) (0.0868) (0.0066) (0.0440) (0.0000) (0.0000)
C onsume r Stapl e s AC AR CHINA AUT OMOT IVE 3.60% 7.54% 0.84% KADANT 2.40% 1.88% -0.13%
Company (0;+1) (0;+2) (0;+3) (0.0871) (0.0003) (0.0003) (0.4206) (0.0234) (0.0002)
PROCT ER & GAMBLE -0.85% -0.97% -0.55% LEGGET T &PLAT T 2.61% -0.21% -0.67% AO SMIT H 3.87% 0.75% 0.39%
(0.6280) (0.0198) (0.0427) (0.0039) (0.0003) (0.0000) (0.0528) (0.1754) (0.0534)
AVON PRODUCT S 2.39% 0.12% 0.65% Yum! Brands 2.09% 0.69% 1.05% Johnson Cont rols 2.71% 2.12% 1.21%
(0.6102) (0.7958) (0.7727) (0.1180) (0.0027) (0.0038) (0.0895) (0.1253) (0.1824)
PEPSICO 0.26% 0.74% 0.38% UPS -1.57% -0.71% -0.58%
(0.0378) (0.0163) (0.0007) He al thcare AC AR (0.1099) (0.0055) (0.0000)
HJ Heinz 1.67% -0.03% 0.72% Company (0;+1) (0;+2) (0;+3) Schlumberger 1.81% -0.86% -1.65%
(0.7031) (0.2443) (0.3752) CARDINAL HEALT H 0.55% 0.06% 0.96% (0.0513) (0.0097) (0.0000) (0.0452) (0.2743) (0.1316) Lincoln Elect ric -3.99% -1.01% -0.27%
Fi nanci al s AC AR PERKINELMER 0.12% 0.48% -0.26% (0.0713) (0.0001) (0.0000)
Company (0;+1) (0;+2) (0;+3) (0.0080) (0.0348) (0.0005) MT S Syst ems -5.40% -1.17% -0.30%
GOLDMAN SACHS GP. 0.65% -1.42% -2.42% Zimmer Holdings 0.17% 1.24% 0.33% (0.1779) (0.0058) (0.0005)
(0.0096) (0.0000) (0.0000) (0.2320) (0.0158) (0.0008) Regal Beloit 5.51% 1.13% 0.45%
MORGAN ST ANLEY 0.31% 0.19% -1.28% Johnson & Johnson 0.47% 0.22% -0.48% (0.0144) (0.0001) (0.0000)
(0.0745) (0.0031) (0.0000) (0.0120) (0.0000) (0.0000) Cooper Tire & Rubber -1.51% -1.17% -0.77% AIG 6.62% -6.51% -6.26% NeoStem -6.76% -0.59% -5.15% (0.5928) (0.0664) (0.0041)
(0.1247) (0.0398) (0.0099) (0.2377) (0.5648) (0.3652) Carlisle Cos 2.77% 1.62% 0.41% Bank of America 0.52% -0.52% -0.92% M edtronic -3.17% 0.01% -1.09% (0.1332) (0.0887) (0.1960)
29 Table 6d (Continued)
Mate ri al s AC AR Te chnol ogy AC AR
Company (0;+1) (0;+2) (0;+3) Company (0;+1) (0;+2) (0;+3)
ALCOA -3.96% -2.19% -1.32% UNIVERSAL ELECT RONICS -0.0258884 -0.0211159 -0.008002
(0.0463) (0.0968) (0.0260) (0.0009) (0.0002) (0.0000)
BALL CORPORAT ION 0.84% -0.55% -0.25% CISCO SYST EMS -0.019106 -0.0143439 -0.0160362
(0.1759) (0.0000) (0.0000) (0.0252) (0.0025) (0.0000)
GENERAL ST EEL -9.36% -7.17% -5.21% DUN&BRADST REET -0.015608 -0.0153519 -0.0094628
(0.0689) (0.0382) (0.0582) (0.4233) (0.0059) (0.0001)
SILGAN HOLDINGS 3.81% 1.65% 1.13% CIRRUS LOGIC -0.034472 -0.0390065 -0.0069172
(0.1944) (0.0048) (0.0029) (0.3811) (0.3473) (0.3828)
CHINA GREEN AGRICULT URE -7.57% 0.63% -2.60% IAC Int erAct iveCorp -0.0083481 -0.00822 -0.0069243
(0.2628) (0.1321) (0.2594) (0.1146) (0.0022) (0.0000)
Int ernat ional Paper -1.51% -1.16% -0.22% ADC T elecommunicat ion 0.0283625 -0.0346844 0.0016641
(0.1529) (0.0000) (0.0000) (0.2080) (0.0462) (0.0057)
Jinpan Int ernat ional -0.66% 1.12% 3.17% Scient ific Games 0.0006383 -0.0042562 -0.0313459
(0.0567) (0.0567) (0.0000) (0.0300) (0.0000) (0.0000) Valspar -0.77% -1.34% -0.35% Symant ec 0.054096 -0.0040268 -0.0120145 (0.1383) (0.0094) (0.0006) (0.0916) (0.0039) (0.0005) 3Com -0.0360283 -0.0198626 0.0116717 (0.1506) (0.5899) (0.0997) Amdocs 0.0057561 0.0039601 0.0018216 (0.0019) (0.0568) (0.0019) Microsoft -0.0040463 -0.0025462 -0.0019311 (0.2287) (0.0502) (0.0077) CNET Net works -0.016029 -0.0090988 -0.0183247
(0.1907) (0.1858) (0.0113)
30
7. Conclusion
This research studies the effect of China’s inbound M&A on the wealth of acquirers’ shareholders in both short run and long run. We attempted to figure out the impact of China’s inbound M&A on the U.S. acquirers. We firstly summarised the findings of existing literatures regarding post-merger stock performance. The majority of the existing researches reported an insignificant negative abnormal return in the short run; for researches studying the long run post-merger stock returns, different extents of negative abnormal returns have been found in different event windows and samples.
We assume that we will observe a positive average cumulative abnormal return around the announcement date for the shareholders of U.S companies acquiring Chinese companies and that the shareholders of U.S. companies acquired Chinese companies have gained negative abnormal return in 3 years after the announcement date. Moreover, as the acquirers gradually adapt to the Chinese market, complete the integrations and start creating synergies over time, we expect that the shareholders of the acquirers will have more positive or less negative cumulative abnormal returns in the second and third year. We applied Fama-French three-factor model for the short run study and Carhart four-three-factor model for the long run study. The result of the short run average cumulative abnormal returns supports our hypothesis that in the short run, the China inbound M&A will bring positive abnormal returns to the shareholders of the acquiring firms. Both of the event windows we have tested report an insignificant cumulative abnormal return on average. The ACAR of 3 days and 5 days before and after the announced date are 0.24% and 0.025%, respectively. The gap between the highest ACAR and the lowest ACAR is lower in the event window of three days before and after the announced date. In addition, we find that some losers in the event window (-3;+3) became winners in the
31
event window (-5;+5). This finding further proves that the individual return is specific to each acquiring firm.
The result we observed for the long run average cumulative abnormal returns is not in line with the hypothesis we made that as the acquirers gradually adapt to the Chinese market, complete the integrations and start creating synergies over time, the shareholders of the acquirers will have more positive or less negative cumulative abnormal returns in the second and third year. The average cumulative abnormal returns of one, two and three years after the announced date are -0.15%, -0.77% and -0.91%, respectively. Therefore, on average there the post-merger synergies and integrations cannot increase the wealth of the shareholders of acquiring firms.
We categorised the sample of 58 companies into eight sectors and found that only consumer staples has a positive average cumulate abnormal return of three years after the merger, the rest all have a negative average cumulative abnormal return to different extents. According to our introduction in section 1, consumer discretionary, healthcare, industrials and technology are more favoured by the Chinese government to bring in foreign investment, thereby accelerating the reform of the Chinese economy and boosting the domestic demands. However, based on the result of our research, acquiring those cheap assets in China cannot bring excess wealth to the shareholders of acquiring firms in the U.S.
In conclusion, for those investors of U.S. companies who want to expand their business by acquiring target companies in China, it is possible to exploit the profits in the short period around the announced date. However, if they buy and hold the stocks for a longer period of at least one year, there is no evidence showing that they will earn more abnormal return than investing in other stocks.
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Due to our various selecting criteria, we could only obtain a sample of 58 companies, which might not be representative enough quantitatively. In addition, due to time limitation, we could not apply models which are more sophisticated than Fama-French three-factor model and Carhart four-factor model, Therefore, a future research applying more recently and sophisticatedly constructed model taking into account more risk factors might be able to provide more robust results for the long run stock abnormal return studies.
33
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