The Power of the Media: the influence of the media on the stock
market performance of acquiring firms.
F.M. VAN DAALEN
University of Groningen Faculty of Economics and Business MSc Strategic Innovation Management
22 June 2015
Supervisors: K.J. McCarthy & K.R.E. Huizingh
Museumstraat 5 9711 HS Groningen f.m.van.daalen@student.rug.nl Student number: 1869264 Word count: 9639
ABSTRACT
Although most acquisitions fail, every day approximately more than 110 acquisitions are made by firms. Some of these acquisitions are widely covered in the media. The questions is, what is the effect of media coverage on the success of an acquisition? In this study the effect of the tone and volume of media coverage on the stock market performance of the acquiring firm is examined by using an event study approach. Thereby, the market to book value is expected to be a condition under which the relationship between the media and the stock market performance varies. A dataset is composed of 184 acquisitions and 2519 news articles. The results indicate that negative news has a positive influence on the stock market performance of the acquiring firms. The effect of the volume of media coverage on the stock market performance is nihil. The study did not find support for the moderating effect of the market to book value.
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1. INTRODUCTION
“Apple can't afford to miss a beat”. This heading of an article in the Wall Street Journal about
Apple’s acquisition of Beats indicates the author is a bit skeptical about the acquisition. The 3 billion dollar acquisition was widely reported in the media. For example, Google delivers 2.810.000 hits when searching on this acquisition, including neutral, negative and positive views. We are wondering whether the negative news articles are able to influence the performance of the acquiring firm. Therefore, the key question in our research is: “Does media coverage have an influence on the stock market performance of the acquiring firm?”.
This is an interesting question because acquisitions are a key part of finance (Buehlmaier, 2013). In 2014 just over 40,400 worldwide deals were announced, and the total deal value of all these acquisitions together contained 3.5 trillion US dollars (Thomson Reuters, n.d.). Remarkably, a vast majority of these acquisitions fail (King, Dalton, Daily and Govin, 2004). Although the management of the companies expect a positive financial return of the acquisition, it turns out that the stock market typically responds less positive. The stock market negatively updates the value of the firm on the expectation of future losses. Recent research showed that the acquisition performance is moderated by variables that are unspecified in existing research (King et al., 2004).
According to the institutional theory acquisitions do not exist in a vacuum. Stakeholders that are often considered to be outside the merging organization may in fact emerge as key actors in the ways in which acquisition processes take shape and are understood. In the stock market there exists an information asymmetry, there are uninformed and informed investors. The informed investor group has superior information (Tetlock, 2010). The problem of information asymmetry can be resolved by the media (Tetlock,2010; Buehlmaier, 2013). The distribution of news about a firm reduces the information asymmetry, which leads to more efficient prices of financial assets, and higher values (DellaVigna and Pollet, 2009; Fang and Peress 2009). The information released by the media can provide the investors with additional information. This additional information will influence the behavior of the investors.
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The relation between media coverage and stock market performance is expected to be negatively moderated by the market to book value (MTBV) of the acquiring firm. Following the performance extrapolation hypothesis, investors over-extrapolate the performance of the bidder when they asses the value of an acquisition (Rau and Vermaelen, 1998). The over-extrapolation of the performance is based on the past performance of the firm and their reputation. A measure of past performance of a firm is the market to book value (MTBV). Firms can be divided in “value” firms and “glamour” firms based on their MTBV. Variability in asset returns can be explained by characteristics of value versus glamour stocks (Conrad, Cooper and Kaul, 2003). Glamour firms are firms that performed well in the past and they are likely to be highly valued (Sudarsanam and Mahate, 2003). Value firms have a low MTBV and are undervalued by the market. Glamour firms are more likely to be covered by the media. Additional information does not add much, and negative information can possibly be outweighed by positive or neutral information. Consequently, the effect of media coverage is expected to be higher for value firms.
To test our hypotheses a sample of 184 acquisitions in the period between January 2012 and December 2014 is constructed. 2519 Articles about these acquisitions in one month before and one month after the announcement date are collected. The sample consist of U.S. and non-U.S. acquisitions. The acquiring firms originated from 25 different countries. Our results did not found support for the negative relationship between the negative tone of the media and the stock market performance of the acquiring firm. Instead, the results presented the opposite, the negativity of the news articles has a positive effect on the stock market performance of the acquiring firms. The volume of media coverage has a significant relationship with the stock market performance. However, the coefficient is very low, which indicates there is no economic significance. The moderating role of the MTBV was not supported by our findings.
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2. LITERATURE REVIEW
Acquisitions
Acquisitions have become an increasingly broad-based phenomenon. Acquisitions are a fast way for companies to scale up their production, broaden their product portfolio, and enter new markets. A key driver of acquisitions is the creation and taking advantage of synergies (Andrade, Mitchell, and Stafford, 2001; Betton, Eckbo, and Thorburn, 2008). Synergies between two firms should results in efficiencies. By acquiring the target firm, the acquiring firm is able to achieve more than when both firms are operating separate from each other. However, a lot of firms are not able to create these synergies and fail to make the acquisition work. Research shows that less than 50 percent of the acquisitions succeed (Calipha,Tarba and Brock, 2010). King et al. (2004), found no evidence that acquisitions, on average, improve the financial performance of acquiring firms after the completed acquisitions are announced. They found that acquisitions either have a non-significant effect or a modest negative effect on an acquiring firm’s financial performance in the post-announcement period. In addition Tuch and O'Sullivan (2007) found that on the short term there is at best a non-significant effect of acquisitions on the shareholder wealth, and for the longer term acquisitions have a negative effect.
Stock market performance
Past research on drivers of the stock market performance mainly focused on financial drivers such as past performance, growth expectations and method of payment. King et al. (2004) conducted a meta-analysis of 93 articles about acquisition performance. Their conclusion stated that the acquisition performance is moderated by variables that are unspecified in existing research. To explain the mystery of movements in stocks prices that cannot be explained by economic information, more recent research has tried to explain the stock market performance after an acquisition by non-financial variables. For example by the mood of acquisition (Sudarsanam and Mahate, 2006); cultural differences (Stahl and Voigt, 2008) and the role of the financial media (Tetlock, 2007; Fang and Peress, 2009).
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market hypothesis was a widely accepted hypothesis, but is questioned by researchers the recent years. Following the efficient market, stock prices could not be too low or too high, because the market immediately adjust to the available information. Stock prices should reflect all information that is available in the market. In our study we question this statement because we believe there exist biases through which the price on the stock market could be undervalued or overvalued and therefore, does not reflect all information. Investors could not act fully rational. The “irrational investors approach” assumes that securities market arbitrage is imperfect. Consequently, prices can be too high or too low (Baker, Ruback and Wurgler, 2008). According to the efficient market hypothesis there should be no room for the media in explaining the stock market performance. Conversely, we suggest that the cause of these too high or too low prices on the stock market can be found in the media. Several studies in the recent years have focused on the influence of the media on the stock market.
The Influence of the Media
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tone and the volume of media coverage are able to influence the stock market performance (e.g. Tetlock, 2007; Fang and Peress, 2009).
Tone of media coverage
The tone of media coverage is measured by the ratio of negative words in news articles concerning the acquisition. One of the first who used linguistic research about the content of the media to explain the firm performance after an acquisition is Paul Tetlock. In his first study about the role of the media in the stock market, he measured the relationship between the media and the stock market by focusing on the influence of the column on U.S. stock market returns “Abreast of the Market” in the Wall Street Journal. The empirical results show that a high level of media pessimism predicts a downward pressure on market prices (Tetlock, 2007). Carcia (2013) confirmed these findings with his study based on financial news from the New York Times.
Investors are not able to observe all the actions of firms in the stock market directly. Therefore, they rely on information they obtain from secondhand, for example information provided by the media (Tetlock, Saar‐Tsechansky and Macskassy, 2008). The amount of negative words in the news about the firm significantly contributes to a useful measure of firms’ fundamentals. Investors include the information that is captured in the content of the media into stock prices (Tetlock et al.,2008). Otherwise hard to quantify information about a firm’s asset prices is reflected in the tone and volume of firm-specific news (Ferguson et al., 2015). Negative media coverage before an earnings announcement, results in large negative shocks to a firms earnings (Tetlock et al. 2008).
Tetlock (2010) further examines how the information asymmetry can be resolved by the media. He determines that a public new story is able to eliminate the information asymmetry. The results assume that the news in the media reveals new information to the uninformed investor and suggest that this news resolves the information asymmetry (Tetlock, 2010). Based on the above considerations we can assume that the negative tone of the media will influence investors’ reactions and thereby influence firm performance. Leading to hypothesis 1 concerning the tone of media coverage and firm performance:
H1: The negative tone of media coverage will negatively influence the stock market performance of the acquiring firm.
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Most of the research concerning the effect of media coverage on the stock market is focused on the content of the media, how positive of negative the news is. Only a few scholars examined the effect of the volume of media coverage on the stock market performance. The volume of media coverage can be seen as the amount of news articles concerning the acquisition. Fang and Peress (2009) distinguish in their research on media coverage and stock returns between firms that obtained high media attention, low media attention or no media attention. On these three levels of media coverage they found a positive relation to stock market performance. However, they also found that no media coverage had a significantly increasing positive effect. Firms with no or less media coverage obtain a significant higher return compared with firms that attain massive media coverage (Fang and Peress, 2009). Peress (2008) found that media coverage is positively related with the price and trading volume reaction to earnings announcements. Announcements with a higher volume of media coverage generate a stronger price and trading volume reaction and a less subsequent drift. Based on the previous described information asymmetry we suggest that with no media coverage there is more information asymmetry in the market. This means that the prices of firms can be more easily overvalued. Therefore, firms are able to obtain a higher performance on the stock market. On the other side, more media coverage resolves the information asymmetry which makes it less riskier for investors to invest. Resulting in more demand for the stock and higher trade volumes but a lower return.
In addition, Barber and Odean (2008) found that investors buy stocks that grabbed their attention, for example stocks that appeared in the news. Which can cause a temporary increase in the stock prices and lead to disappointing returns. This is related with Peress (2008), who argued that an important source of friction in financial markets is limited attention. Inattention causes investors to underreact to the market.
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shows that media coverage is an important factor that can influence the trading of a stock. Hence, hypothesis 2 states:
H2: The volume of media coverage will have a positive influence on the stock market performance of the acquiring firm.
The moderating effect of the market to book value
As mentioned before the variability in asset returns can be explained by characteristics of value versus glamour stocks (Conrad et al. 2003).The return on assets is frequently used as a measure of firm performance. Thus, variability in the performance of firms can be explained by characteristics of value versus glamour stocks. Firms can be divided in value and glamour firms based on their MTBV. Past research on the stock market performance often found a significant relationship between the MTBV and the stock market performance of the acquiring firm. The MTBV links the stock price of a firm with the book or accounting value of shareholders’ equity per share. The MTBV is calculated by dividing the market value of a firm by the book value of the firm. It is usually used to proxy for a firm’s future growth opportunity. It reflects how many times the book value investors are ready to pay for a share. A MTBV greater than one means that a company’s market value is worth more than its book value. “Glamour acquirers are those firms that are highly valued as a result of their prior stock market performance” (Sudarsanam and Mahate, 2003, p. 301). Subsequently, glamour firms are firms with a high MTBV, while value firms are the firms with a lower MTBV. Another commonly used ratio is the book to market ratio. This ratio is can be seen as the reversed MTBV. The calculation of book to market ratio is based on the same numbers as the MTBV, only the numerator and denominator are reversed. Which results in exactly the opposing ratio’s for glamour and value firms. Firms with a high book to market ratio will be referred as value firms, while a low book to market ratio is linked with glamour firms. We will use the MTBV and translate findings of other research on the book to market ratio to the MTBV to avoid confusion.
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Accordingly, glamour stocks receive premium ratings in the form of MTBVs (Sudarsanam and Mahate, 2003).
According to the performance extrapolation hypothesis, the market over-extrapolates the past performance of the bidder when it assesses the value of an acquisition (Rau and Vermaelen, 1998, p.225). Research on financial media shows that investors’ overreaction to news is more pronounced for glamour stocks. High MTBVs persuade investors to assign high reputations to firms over and beyond the effects of accounting profitability, advertising intensity, size, and risk (Fombrum and Shanly, 1990). These good reputations could enable glamour firms to attract more investors. Additionally, Barber and Odean (2008) argued that investors face difficulties in choosing which stock to invest in because of the large amount of choices. They found that investors are more likely to buy attention-grabbing stocks. For example, stocks that appear in the news. Azuma, Okada and Hamuro (2014) add to this argument that the direction of the investment decisions of investors is affected by the tone of the news. Variations in media coverage exaggerate the differences in attention to glamour firms. Because of growth and performance in recent years glamour firms are likely to be repeatedly in the investors’ minds. Peress (2008) argues that the effect of media coverage will be weaker for glamour firms, because these firms are already constantly on investors’ minds. Therefore, the attention is not really reflected by media coverage.
Another argument for the difference between value and glamour firms is that managers of glamour firms overestimate their abilities to manage an acquisition (Rau and Vermaelen,1998) They are infected by hubris (Roll, 1986). “Hubris infects extremely confident managers who highly estimate their ability to extract acquisition benefits and consequently pay large premiums” (Hayward and Hambrick, 1997, p. 106). This hubris will cause managers to be overconfident of their own valuation analysis and will lead to excessive acquisition activity (Barberis and Thaler, 2005). In contrast, value firms tend to be more cautious with their acquisitions and are less likely to be driven by hubris. Consequently, value firms are likely to outperform glamour firms in three years after the acquisition (Rau and Vermaelen, 1998). The expectations of glamour are set quite high and difficult to attain, while there are low expectations for the value firms. The market seems to be too pessimistic about the capabilities of value firms (Rau and Vermaelen, 1998).
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firm a negative moderation by the MTBV is expected. We suggest that the effect of the tone of the media will be greater for value firms, firms with a low MTBV. A negative moderation of the MTBV is expected between the volume of media coverage and the stock market performance of the acquiring firm as well. Since firms with a lower MTBV are likely to be covered less in the media, the positive effect of more media coverage will be greater for firms with a lower MTBV.
Hypothesis 3a: The relation between the tone of the media and the stock market performance of the acquiring firm is negatively moderated by the market to book value of the acquiring firm.
Hypothesis 3b: The relation between the volume of the media and the stock market performance of the acquiring firm is negatively moderated by the market to book value of the acquiring firm.
3. METHODOLOGY
In this section, first, the sample selection will be described. Subsequently, the measurement of the dependent, independent, moderator and control variables will be discussed. Appendix 5 provides a table including all the variables with their definitions and constructions. Last, the analytic approach used in this study will be explained.
Sample selection
To test our hypotheses a sample was composed of acquisitions from companies across various industries worldwide. News articles concerning these acquisitions are derived from English-language newspapers.
Acquisitions. The acquisitions and information about these acquisitions are obtained
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excluded. Within firm acquisition were deleted from our sample as well. This leaves a sample of 278 acquisitions.
Media. The media data is collected from LexisNexis. LexisNexis aggregates
information from over 36,000 international news and business sources, as well as thousands of business-relevant web sites, blogs and forums (LexisNexis, n.d.). News articles that referred to one of the acquisitions of our sample are collected during the period one month before the announcement date and one month after the announcement date. There was no specific selection on newspapers, all English-language newspapers were included. From the original 278 acquisitions, 184 acquisitions were covered in the media by news articles. Acquisitions without media coverage are excluded from our sample. Therefore, the final sample of acquisitions contained 184 acquisitions. These 184 acquisitions are made by a 69 different firms from 25 countries. Appendix 2 displays the distribution of acquisitions per country. The majority of our acquisitions are made by firms based in the United States.
Unfortunately, there was some noise in the articles that were initially collected. For example, next to relevant information, searching on “Johnson & Johnson” delivered some sport results showing that Mr. Johnson scored. To avoid this noise in the articles, the results are filtered on for example at least two times occurrence of the acquiring firm. The exact steps and selection criteria are described in appendix 2. After the first steps to delete the noise in the news articles, our sample consisted of 2975 articles. However, examining these articles we concluded that there was still some noise in the articles. For instance, articles that reported the most important events happened that week, including only one sentence about the acquisition. To avoid the noise a scan is made through all the articles and the following articles are removed: (1) articles that did not concern the acquisition; (2) articles that only mentioned the acquisition as a reference; (3) articles that concerned a lot of acquisitions or other news and only briefly mention the acquisition. Duplicates were also removed, except for articles that appeared in other editions of the newspaper. With scanning the articles 15,3 percent of the articles are removed, leaving a final sample of 2519 news articles. 244 Articles for one month before the acquisitions and 2275 articles for one month after the acquisitions. The articles are derived from 322 different newspapers from 18 different countries.
Dependent variable
Firm performance. The focus in our study is on the stock market performance of the acquiring
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defined as the short term market response to acquisition announcements because the a stock’s upward or downward movement is measured over a short time frame. CARs around acquisition announcement dates reflect investors’ responses to the announcement of an acquisition, based on present expectations about the future cash flows of a combined firm (Haleblian et al. 2009). The CARs are measured with an event study approach. This procedure is further described in the analytic approach.
Independent variable
The independent variable media coverage was divided into two measures. A measure for the tone of media coverage and a measure for the volume of media coverage.
Tone. The tone of the media is measured following the work of Tetlock (2007) and
Tetlock et al. (2008), by using the ratio negative words to the total number of words. To calculate the amount of negative words in the articles the Harvard IV-4 Psychological Dictionary is used. The word classification labeled NEGATIV consist of 4783 negative words. Examples of the negative words are abrupt, meaningless, neglect and over-priced. With a script running through all the articles of our sample, the amount of negative words per article was calculated. The ratio negative is calculated by dividing the amount of negative words in the article by the total amount of words in the article:
𝑅𝑎𝑡𝑖𝑜 𝑛𝑒𝑔𝑎𝑡𝑖𝑣𝑒 𝑎𝑟𝑡𝑖𝑐𝑙𝑒 𝑥 =𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑛𝑒𝑔𝑎𝑡𝑖𝑣𝑒 𝑤𝑜𝑟𝑑𝑠 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑡𝑜𝑡𝑎𝑙 𝑤𝑜𝑟𝑑𝑠
Afterwards, we took the average of all news articles concerning the acquisition to construct the ratio negative per acquisition. The face validity of the ratio negative is checked by using 2 independent students. Both students rated 15 randomly selected articles on a scale from 1 to 10 how negative they thought the articles were, with 10 indicating that the article is very negative. The correlation test between the students ratings and the calculated ratio negative shows a strong relationship. The results confirm the use of our ratio negative as a proxy for the negative tone of the media. The correlation matrix is displayed in appendix 4.
Volume. Following Fang and Peress (2009) the volume of media coverage was
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Moderator variable
Market to book value (MTBV): The MTBV is derived from Datastream for the end of the
previous fiscal year. Datastream is a financial database providing macro-economic data as well as global financial data. Unfortunately the MTBV was not available for 5 acquisitions.
Control variables
Media related control variables. First, media related control variables are included. The first
media related control variable is the circulation rate. We controlled for the different circulation rates belonging to the newspapers in which the articles were published. From almost all the articles the circulation rates are retrieved, for example from the Audit Bureau of Circulations (ABC). The average of all circulations rates belonging to one acquisition is taken as the circulation measure for the acquisition. The second control variable was whether the country of the newspaper matched the home country of the acquiring firm. Carroll and McCombs (2003) found that the proximity of a firm to a particular news source can influence its news coverage by that medium. A dummy variable is created, indicating 1 when the country of the firms matches the country of the newspaper and 0 when there is no match.
Deal specific control variables. Second, data on the deal specific control variables was
employed. The deal value is retrieved from the Thomson SDC database to control for differences in the stock market performance of acquiring firms caused by differences in the deal values of the acquisitions. The deal value is divided by the market value of the acquiring firm in order to get the relative deal value. Previous research also showed that national and international acquisition have different effects. International acquisitions are expected to outperform national acquisition, for example because they expand their businesses into new markets (Martynova, Oosting, and Renneboog, 2006). To control for this effect a dummy variable international was created, with 0 referring to national acquisitions and 1 referring to international acquisitions.
Firm specific control variables. Finally, firm specific controls to account for
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necessary. A variable firm size reflecting the number of employees per firm is included. The second firm specific control variables that was added is the net cash flow from operating activities of the acquiring firm. We control for the net operating cash flow because companies that are performing well are likely to generate significant cash flows. In addition, cash-rich firms are more likely to make acquisition (Harford, 1999).
Analytic approach
To measure the firm performance an event-study approach is used following MacKinlay (1997). The event study measures the impact the acquisition announcement on the value of the firm (MacKinlay, 1997). In our study a short window of 41 days is used. The event-window is comprised of 20 pre-event working days, the event and 20 post-event working days. The advantage of a short event-window is that changes in the stock prices can be attributed to the acquisition announcement with minimizing noise from other potential variables (Haleblian et al. 2009). The time line for the event study is presented in figure 1.
Figure 1. Time line the event study 1
To evaluate the impact of the acquisition announcement, a measure for the abnormal return is required. The abnormal return is “the actual ex post return of the security over the event-window minus the normal return of the firm over the event event-window” (MacKinlay, 1997, p.15). The formula for firm 𝑖 and event date 𝜏 is:
𝐴𝑅𝑖𝜏 = 𝑅𝑖𝜏− 𝐸(𝑅𝑖𝜏|𝑋𝜏)
Where 𝐴𝑅𝑖𝜏 is the abnormal return, 𝑅𝑖𝜏 the actual return and 𝐸(𝑅𝑖𝜏|𝑋𝜏) the normal return for
time period 𝜏. In order to draw overall inferences for the acquisition, the abnormal return observations must be aggregated (MacKinlay, 1997). The sum of these abnormal returns is called the cumulative abnormal return (CAR). The CAR from 𝜏1to , 𝜏2 is,
𝐶𝐴𝑅𝑖(𝜏1, 𝜏2) = ∑ 𝐴𝑅𝑖𝜏
𝜏2
𝜏=𝜏1
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4. RESULTS
Summary statistics
For the 184 acquisitions, a total of 2519 news articles were collected and analyzed. In order to get one measure for each of the characteristics of the news articles per acquisition, the averages of the total are taken. Table 1 presents the descriptive statistics of these averages per acquisition. As showed in table 1 there is a big difference between the mean and the median of the circulation rates. To control for outliers, a log variable is created and used in the regression models. Table 2 displays the descriptive statistics of the acquiring firm and deal specific variables per acquisition. The acquiring firms characteristic show big difference between the minimum and maximum values. For these variables a log is created as well, to control for outliers.
Table 1: Descriptive statistics news articles
Variables N Mean Median SD Min. Max.
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Table 2: Descriptive statistics acquisitions
1
* 1000
Table 3 shows the correlation matrix of the key variables. The correlation matrix shows that some of the key variables are highly correlated. High correlations can indicate that multicolinearity exists. Multicolinearity reflects “high correlations among the latent exogenous constructs” (Grewal, Cote and Baumgartner, 2004, p.519). In order to check for multicolinearity the Variance Inflation Factors (VIF) are calculated for the key variables. The results show that our model does not suffer from multicolinearity (VIF <4.94). Appendix 6 shows the exact VIF per variable.
Table 3: Correlation matrix of the key variables
1 2 3 4 5 6 7 8 9 10 1. CAR(-20,+20) 1.000 2. Ratio negative1 0.193 1000 3. Total coverage1 0.107 0.192*** 1000 4. Ln(circulation) -0.107 0.160*** 0.293*** 1000 5. Match country 0.159** 0.046* -0.024 -0.068*** 1000
6. Relative deal value 0.096 0.165*** 0.273*** 0.216*** -0.164*** 1000
7. International acquisition -0.136* 0.047* 0.075*** 0.014 -0.285*** 0.063** 1000 8. Ln(size) -0.031 -0.232*** -0.104*** -0.015 -0.005 -0.109*** 0.042* 1000 9. Ln(cash flow) -0.003 0.012 -0.003 -0.022 0.001 -0.060** -0.004 0.028 1000 10. Ln(MTBV) 0.035 0.082*** 0.211*** 0.253*** -0.146*** 0.140*** 0.081*** -0.168*** -0.037 1000 *** p<0.01, ** p<0.05, * p<0.1 1 mean centered Ln(x) = log(x)
Variables N Mean Median SD Min. Max.
Deal characteristics
Deal value1 184 1468.397 525 2600.483 10.312 19119.31
International acquisition 184 0.380 0 0.487 0 1
Acquiring firm characteristics
Firm size 180 138647 98438.5 109175.9 4500 519671
Cash flow 180 35978.72 1260.637 330012.2 -74725.9 3797281
Market value1 183 2080.461 100.771 17538.25 21.576 197528.2
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Regression
The interest of this study is the effect of the media on the stock market performance of the acquiring firm. Media coverage is distinguished in the tone of media coverage and the volume of media coverage. The scatter plots below shows that both of the independent variables have positive relationship with the stock market performance. The ratio negative displays a somewhat stronger relationship with the stock market performance of the acquiring firm, than the volume of media coverage.
Figure 2: Scatterplot ratio negative figure 3: Scatterplot total coverage
The regression results for the stock market performance of the acquiring firm, measured by CAR(-20,+20), are presented in table 4. Acquisition activity clusters through time by industry (Andrade and Stafford, 2004). Therefore, we run our regressions clustered by industry. The acquisitions are classified in 10 different industries by the industry code of the ICB. Additional information about the industry classification can be found in appendix 7. Model 1 in table 4 shows the base line model with only our control variables. The table displays the unstandardized correlation coefficients (B) and between parentheses the significance level (p-value). The control variable relative deal value (B=0.571, p<0.10) contributes significantly to the stock market performance. Indicating that a higher relative deal value would result in a higher stock market performance of the acquiring firm. The significance of the relative deal value disappears when adding our variables of interest.
Our first assumption was that the negative tone of the news articles will have a negative impact on the stock market performance of the acquiring firm. The results presented in model 2 do not support this assumption. Moreover, they show the opposite of what was expected. The ratio negative appears to have a positive and significant effect (B=1.821, p<0.01) on the stock market performance of the acquiring firm. Subsequently, hypothesis 1 can be rejected. Our results indicate that the more negative the news is about the acquisition,
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the better the stock market performance of the acquiring firm will be. The stock market performance of the acquiring firm is expected to increase with 1.821 percent when the ratio negative increases by one, holding the other factors constant. The adjusted R-square raises from 0.035 to 0.072, indicating that model 2 adds 3.7 percent in explaining the variance in the stock market performance of the acquiring firm.
Table 4: Regression results on CAR(-20,+20) clustered by industry
(1) (2) (3) (4) (5) Ratio negative1 1.821*** 1.939** (0.001) (0.020) Total coverage1 0.001* 0.000 (0.079) (0.595) Ln(circulation) -0.011 -0.014 -0.015 -0.015 -0.016 (0.329) (0.244) (0.151) (0.236) (0.130) Match country 0.042 0.031 0.039 0.028 0.038 (0.126) (0.213) (0.150) (0.246) (0.181)
Relative deal value 0.571* 0.441 0.488 0.427 0.485
(0.062) (0.166) (0.141) (0.192) (0.139) International acquisition -0.017 -0.021 -0.019 -0.021 -0.017 (0.381) (0.185) (0.325) (0.273) (0.437) Ln(size) -0.003 0.003 -0.001 0.003 -0.003 (0.760) (0.678) (0.884) (0.759) (0.764) Ln(cash flow) 0.011 0.009 0.010 0.010 0.010 (0.187) (0.174) (0.244) (0.165) (0.228) Ln(MTBV) 0.009 0.003 (0.559) (0.839) Ratio negative * Ln(MTBV) -0.228 (0.778) Total coverage * Ln(MTBV) 0.000 (0.647) Constant 0.072 0.058 0.117 0.073 0.130 (0.630) (0.679) (0.385) (0.594) (0.323) Observations 165 165 165 162 162 Adjusted R-squared 0.035 0.072 0.043 0.055 0.025 *** p<0.01, ** p<0.05, * p<0.1 1 Mean centered Ln(x) = log(x)
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variable volume of media coverage to the control variables increased the adjusted R-square from 0.035 to 0.043. Indicating that more variance is explained by model 3 compared with model 1. The results indicate a positive and significant (B=0.001, p<0.1) relationship, accordingly hypothesis 2 is supported. However, the coefficient is 0.001, indicating that the effect is nihil. Adding one additional article, the stock market performance of the acquiring firm is expected to increase with only 0.001 percent, holding the other factors constant.
Model 4 and 5 in table 4 present the regression results with the moderating variable, MTBV. The MTBV was expected to influence the relationship between media coverage and the stock market performance. Model 4 shows the regression results with the ratio negative as independent variable. The positive effect of the ratio negative found in model 2 remains significant and strong when adding the moderating variable (B=1.825, p<0.01). The effect of the moderator MTBV on the relation between the tone of the media and the stock market performance is negative as expected, although not significant (B=-0.023, p>0.1). Thereby, the model shows that adding the moderator variable does not contribute in explaining the variance. The adjusted R-square decreases from 0.072 to 0.055. Consequently, hypothesis 3a can be rejected.
Finally, model 5 shows the results for the moderating effect of the MTBV on the relationship between the volume of the media and the stock market performance. The results show that the relationship is not significant (B=0.000, p>0.1). The coefficient is zero, indicating that there is a random, nonlinear relationship. The adjusted R-square presents a decrease of 1.8 percent. Indicating model 5 explains even less than the baseline model 1. Based on these results hypothesis 3b can be rejected as well.
Robustness
To check the robustness of the model the same regression was made on the calculated CARs for three additional event windows. A five day event window (-2, +2), an 11 days event window (-5, +5) and a 21 days event window (-10, +10).The regression models can be found in appendix 8. Our main result, the positive effect of ratio negative, remains robust for CAR(-10,+10) and CAR(-5,+5). Interesting to see is that for CAR(-2,+2) the ratio negative converts into a negative and non-significant relationship in the model without the moderator.
21
performance of the acquiring firm. The moderating effect of the MTBV on the relation between the media coverage and the CAR is negative and significant for CAR(-10,+10), CAR(-5,+5) and CAR(-2,+2). However, the coefficient is close to zero, which indicates that the effect is nihil.
Because our models did not indicate a moderating effect of the MTBV for CAR(-20,+20) the regressions are repeated with other variables on which firms could be divided into value and glamour firms. Based on Yan and Zhao (2011) the regressions are done with the following variables as moderator: the equity to price ratio (EP); average of annual growth in sales over the previous three years (SG) and the cash flow from operations scaled by the market value of equity (CP). The results indicated a non-significant relationship as well.
5. DISCUSSION
The focus of the study was to examine the effect of the tone and volume of the media on de stock market performance of acquiring firms. This relationship was expected to be moderated by the MTBV of the firm. Because the effect of the media was expected to be different for glamour and value firms. The main findings are that a negative tone of the media has a positive influence of the stock market. The volume of media coverage only had a significant relationship in the regression model without the moderating variable, and no support was found for the moderating effect of the MTBV.
Tone of the media
The results showed that the more negative the media talks about the acquisition, the more positive the stock market performance of the acquiring firm will be. However, the ratio negative was expected to negatively influence the stock market performance. The findings raises the question, how could it be that negative publicity has a positive influence? From the literature can be derived that people are negatively biased. People pay more attention to negative events and negative events will be more easily remembered. “Negative information receives more processing and contributes more strongly to the final impression than does positive information” (Baumeister, Bratslavsky, Finkenhauer and Vohs, 2001, p.323-324). However, that does not explain the positive relation found in the results.
22
the negative information is remembered better, firms that are negatively covered by the media are more likely to be on the mind of the investors. The negative news creates awareness of the stock and consequently investors attain more attention to these stocks. These arguments suggest that investors would be more likely to buy a stock of a firm they have read about, than from an unknown stock, even when the news contained negative information. This line of reasoning is consistent with the empirical results of Barber & Odean (2008) and Brammer, Brooks and Pavelin (2004). Stock prices and the demand for particular stocks increases even when information about the stock is negative and the reputation scores of the firm have fallen down. What can be concluded is that there is no such a thing as bad publicity.
Research from a number of fields is helpful in explaining the positive effects of the bad publicity. Firstly, research on the effect of the media in the cultural industry indicates that presence in the media is more important than whether the information is favorable or unfavorable (Hirsch, 1972; Gemser, van Oostrum and Leenders, 2007). What matters is getting media coverage, not the tone of the media coverage.
Second, the field of political science provides evidence that exposure to negative political advertisements does not withhold people to vote. Moreover, exposure to negative advertisements had a positive and strong effect on turnout, it stimulated people to vote (Freedman and Goldstein, 1999). These results are similar to our results. In our study negative news does not withhold investors to invest in the firm, the opposite is true. Exposure to negative news about the acquisition made by the firm had a positive effect on the firm performance.
23
not respond on the news by selling their stock. Hence, the prices of the stock will not fall down.
Volume of the media
The volume of media coverage was expected to have a positive effect on the stock market performance. The results of the study found a significant effect for the volume of media coverage in the regression model without the moderating variables. However the coefficient is 0.001. This indicates that when the total coverage increases with 1, the stock market performance will increase with 0.001 percent. Thereby, the total coverage does not remain significant when adding the moderating variable.
There are several explanations for the result found in the study. First, it may be due to our sample of acquisitions. The focus in this research was on how the volume of media coverage influences the stock market performance. Hence, acquisitions that were not covered by the media were excluded. Our result suggest that for the acquisitions that are covered by the media, the amount of articles does not have a strong influence on the stock market performance of the acquiring firm. However, it could be that for articles that are not yet covered by the media the effect of the volume of media coverage will be greater.
A second explanation might be that we did not distinguished between the authors of the news. It could make a difference if an article is written by a normal journalist or a stock market analyst. Investors base their action not purely on their own analysis of the market. It is likely that an investor will use social proof, “using the actions of others to infer the value of a course of action” (Rao, Greve and Davis, 2001, p.502). The recommendation from an analyst to buy or sell affects the prices on the stock market (Womack, 1996). Further research should take into account the author of the news articles and how influential this author is.
Moderating effect of the market to book value
24
are underrepresented in our sample, and therefore we were not able to observe the a significant effect for our moderator MTBV.
Second, there are no exact rules in the literature how to divide firms into glamour and value firms. Researchers mostly divide firms into glamour and value firms based on the median or percentiles of the MTBV in their sample. This means that the average MTBV for value and glamour firms is different for each study. Moreover, different measures are used to divide firms in glamour and value firms. Research would benefit from the creation of guidelines how to divide firms into glamour and value firms. A standard measure in the financial literature will make it possible to compare the findings of different studies as well.
Short term versus long term effects
A final clarification for our results might be the chosen event window. Results may be different for the long term firm performance. Based on literature we suggest that the positive effect of the negative news will have an effect on the short term, but will be diminished when looking at the longer term. In first instance because of the attribution bias. “Biased self-attribution adds positive short-run earnings “drift,” but negative correlation between future returns and long-term past stock market and accounting performance” (Daniel, Hirshleifer and Subrahmanyam 1998, p.1839). This implies that the effect of the media found in the study only holds true on the short term because of the self-attribution bias. On the longer term the effect of the self-attribution bias will vanish. Accordingly, the market will update the value of the stock price consistent with the real value of the firm.
25
on a small event window and a wider event window in order to differentiated between short term effects and long term effects on the firm performance.
Managerial implications
A managerial implication of this study is that managers of glamour firms should encourage the media to write about them. According to (Ahern and Sosyura, 2014) managers can influence the media coverage. Research about the effect of the media will help managers to develop the right strategy concerning the media. By managing the media coverage they have a better opportunity to manage the firm performance. Our results even suggest that glamour firms could benefit from gaining negative attention. Therefore, actions of the firm to attain negative media attention could pay off.
Limitations and future research directions
In the discussion some limitations of our study are already highlighted. One of the limitations briefly mentioned is that the sample only includes acquisitions with media coverage. As discussed above we were not able to study firms with no media coverage. It may be due to this sampling that a significant effect for our moderator MTBV was not found. Future research should take into account acquisitions that are not covered by the media as well, in order to get a balance between glamour and value firms.
A second limitation might be the newspapers used for the collection of the news articles concerning the acquisition. All English-language newspapers are included. However, the effect of these newspapers may be different for countries where English is not the mother tongue. In addition, there is also a difference between more specialized financial newspapers and general daily newspapers. It might be true that the influence of these media sources on the stock market performance differs. Further research should distinguish between those two sources of the media. Thereby, as already mentioned in the discussion, future research should take into account the author of the news article.
26
enters an acquisition for the first time, negative news may create awareness for the firm and thereby increase the demand for the stock on the market. Future research should take the acquisition experience into account.
6. CONCLUSION
In this research the influence of the media on the stock market performance of the acquiring firm is examined. We investigated whether the MTBV is a condition under which the relationship between the media and the stock market performance varies. The influence of the media was divided in the tone of media coverage and the volume of media coverage. The tone of media coverage was measured by the ratio of negative words in the article. The volume of media coverage by the amount of articles concerning the acquisition
In the beginning of this research the following question was stated: is the media able to influence the stock market performance of the acquiring firm? Based on previous literature it was suggested that the media can influence the stock market performance and that the efficient market hypothesis does not hold true. Because of the information asymmetry and investors’ biases, there is room for the media to explain the stock market performance. The relation between the media and the stock market performance was expected to be moderated by the MTBV. Based on the MTBV firms could be divided into glamour and value firms. The influence of the media on the stock market performance was expected to differ between these firms because of their valuation by the market, reputation and expectations.
The study proofs that the tone of the media is able to influence the stock market performance. The results indicate that the negative tone of the media is able to positively influence the stock market performance of the acquiring firm. The more negative the media talks about the acquisition, the more positive the stock market performance. Although these results seems to be counterintuitive, some explanations in other research fields are found explaining the positive effects of negative publicity. For the volume of the media a significant positive relationship with the stock market performance was found as well. However, the coefficient was very low indicating that the effect is nihil. No support was found for the moderating effect of our MTBV.
27
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8. APPENDICES
Appendix 1
124 largest stock listed companies:
1. 3M 2. Abbott 3. Agricultural Bank of China 4. Allianz 5. Amazon 6. América Móvil 7. American Express 8. Amgen 9. Anheuser-Busch InBev 10. ANZ 11. Apple 12. ArcelorMittal 13. AstraZeneca 14. AT&T 15. Banco Bradesco 16. Banco Santander 17. Bank of America 18. Bank of China 19. Bank of Communications 20. Bank of Nova Scotia 21. Barclays 22. BASF 23. Bayer 24. Berkshire Hathaway 25. BG Group 26. BHP Billiton 27. BNP Paribas 28. BP 29. British American Tobacco 30. Canon 31. Chevron 32. China Construction Bank 33. China Shenhua Energy Co Ltd 34. Cisco Systems 35. Citigroup 36. CNOOC Limited 37. Coca Cola 38. Comcast 39. Commonwealth Bank 40. ConocoPhillips 41. Credit Suisse Group 42. Deutsche Telekom 43. Diageo 44. E.ON 45. Ecopetrol 46. EDF 47. ENEL 48. ENI 49. Exxon Mobile 50. Gazprom 51. GDF Suez 52. General Electric 53. Gilead Sciences 54. GlaxoSmithKline 55. Goldman Sachs 56. Google 57. Hewlett-Packard 58. Home Depot 59. Honda Motor 60. HSBC Holdings 61. IBM 62. ICBC 63. Inditex 64. Intel 65. Itaú Unibanco Holding
66. Johnson & Johnson 67. JPMorgan Chase 68. Lloyds Banking Group 69. L'Oreal Group 70. McDonald's 71. Merck & Co 72. Microsoft 73. Mitsubishi UFJ Financial 74. National Australia Bank 75. Nestle 76. News Corp
77. Nippon Telegraph & Telephone Corporation 78. Novartis 79. Novo Nordisk 80. Occidental Petroleum 81. Oil & Natural Gas
Corporation Ltd. (ONGC) 82. Oracle 83. Orange (former France Telecom) 84. PepsiCo 85. Petrobras 86. PetroChina 87. Pfizer 88. Philip Morris International 89. Procter & Gamble 90. Qualcomm 91. Reliance Industries 92. Rio Tinto 93. Roche Holding 94. Rosneft 95. Royal Bank of Canada
33
Appendix 2
Figure 4 shows the number of acquisition per country. The majority of the acquisitions in our sample is done by firms from the United states.
1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 3 4 4 5 7 14 19 103 B elg iu m B raz il Italy L u x em b o u rg New Z ea lan d Po lan d R u ss ian Fed So u th A fr ica Sw ed en Fra n ce Is rae l Jap an Neth er lan d s No rway Si n g ap o re So u th K o rea S p ain In d ia A u str ali a Me x ico Sw itzer land C an ad a Ger m an y Un ited Kin g d o m Un ited States
34
Appendix 3
Table 5 presents all the steps used in the collection of the articles. 183 Acquisitions are covered by news articles in the period one month after the announcement day. From these 183 acquisition 42 were covered in the period one month before the announcement date as well. One acquisition was only covered by news articles in the month before the announcement date. This explains the total sample of 184 acquisitions.
Table 5: Selection procedure news articles
Steps Selection criteria Acquisitions Articles
Step 1: Collect acquisitions from SDC Thomson database.
1. Between 01/01/2012 and 31/12/2014
2. Deal value > 10 million dollars
3. 100% ownership
12,098
Step 2: Filter on firms that are on Forbes list of largest stock listed companies 2013
1. SEDOL number
2. Organization name 278
Step 3: Collect articles one month after deal of
announcement
1. Delete business entities
2. At least two time occurrence of acquiring and target firm,
3. > 75 articles, add "acquisition”
183 2975
Step 4: Collect articles one month before deal of announcement
1. Delete business entities
2. > 75 articles, add "acquisition” 43 317
Step 5: Check quality of articles one month after deal of announcement
Deleted:
1. Articles that did not concern the acquisition
2. Articles that only mentioned the acquisition as a reference
3. Articles that concerned a lot of acquisitions or other news and only briefly mention the acquisition
4. Duplicates
183 2275
Step 6: Check quality of articles one month after deal of announcement
Deleted:
1. Articles that did not concern the acquisition
2. Articles that only mentioned the acquisition as a reference
3. Articles that concerned a lot of acquisitions or other news and only briefly mention the acquisition
4. Duplicates
43 244
35
Appendix 4
Both students were asked to rank 15 random selected articles on a scale from 1 to 10 how negative the articles are. A score of 10 would indicate that the article is very negative, while a score of 1 indicates that the article is not negative at all. Table 6 shows the scores of the students and the belonging ratio negative. Table 7 displays the correlation matrix of the ratio negative and the rating of the independent students.
Table 6: Student ratings tone articles
Acquisition ID Article Number of words Ratio negative Student 1 Student 2
1 4 253 0,023715 1 1 31 3 229 0,017467 2 2 62 7 236 0,059322 10 8 69 35 114 0,052632 4 4 89 9 334 0,128743 9 9 101 12 524 0,03626 1 2 125 19 261 0,015326 1 3 132 8 536 0,020522 4 7 150 1 281 0,010676 1 5 157 7 437 0,02746 4 7 164 4 672 0,028274 6 5 171 22 228 0,035088 4 4 178 39 210 0,07619 6 4 180 45 471 0,016985 4 7 184 15 262 0,034351 3 3
Table 7: Correlation matrix of ratio negative
Ratio negative Student1 Student2
Ratio negative 1.000
Student1 0.7310 1.000
36
Appendix 5
Table 8 contains a list of all the firm specific characteristics with their definition and construction or the Datastream codes used in constructing them.
Table 8: Variables
Variable Definition Construction / Datastream code
Firm performance Cumulative abnormal return of the
stock market performance of the acquiring firm
See analytic approach
Ratio negative Average ratio negative of all news
articles concerning the acquisition
Amount of negative words / total amount of words
Total coverage Amount of articles before and
after the announcement date
-
Circulation Average circulation of all articles
for an acquisition
-
Match country Country of the newspaper matches
country of the acquiring firm.
Dummy variable: 0 different countries, 1 match countries.
Relative deal value Deal value / market value
acquiring firm
Deal value (SDC database) / MV (Datastream)
International acquisition Acquiring firm and target firm from different countries
Dummy variable: 0 same countries (national), 1 different countries (international)
Size Number of employees of the
acquiring firm
WC07011
Cash flow Net cash flow from operating
activities of the acquiring firm
WC04860
MTBV Market to book value end previous
fiscal year
MTBV
37
Appendix 6
Table 9 shows the VIF’s for the variables in model 4 and 5 of the regression results in table 4.
Table 9: Multicolinearity for key variables
Variable VIF
Ratio negative Total coverage
Ratio negative 2.80 -
Total coverage - 3.10
Ln(circulation) 1.23 1.32
Match country 1.22 1.21
Relative deal value1 1.20 1.21
International acquisition 1.17 1.16 Ln(size) 1.16 1.08 Ln(cash flow) 1.15 1.16 Ln(MTBV) 4.22 1.93 Ratio negative * MTBV 4.93 - Total coverage * MTBV - 3.72 Appendix 7
Figure 5 presents the industries by which the acquisitions are classified with the frequencies. From one of the acquiring firms the industry code could not be retrieved from Datastream, therefore the sample consist of 183 acquisitions.
Figure 5: Distribution of acquisitions per industry
