The market-to-book ratio and announcement returns during M&A activity

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The market-to-book ratio and

announcement returns during

M&A activity

B. ter Huurne

s1553038

Rijksuniversiteit Groningen

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Abstract

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1. Introduction

There has been a growth in merger and acquisition activity in the last decade. In 2000 this resulted in a record of mergers and acquisitions worldwide, with a total value of more than $3.3 trillion.1_{The economic downturn after 2000 caused a steep decline in} M&A activity in the years 2001 and 2002. However, recently M&A activity has reached new records. In the year 2007 M&A activity grew with 21% in comparison with 2006, towards a total value of $4.7 trillion.2_{Because of this enormous growth and economic} impact, mergers and acquisitions are one of the most researched areas in finance. Moeller et al. (2005) found that between 1998 and 2001 the shareholders of acquiring companies lost $240 billion around the announcement of takeovers. This loss can be attributed to a small number of firms with extremely high market-to-book ratios. This is remarkable since Lang et al. (1989) and Servaes (1991) found that announcement returns and market-to-book ratios are positively related. This raises the question: what is the market-to-book ratio really capturing? A few studies have been devoted to the role of the market-to-book ratio on shareholders announcement returns, but not one has given a solid explanation for the differences in research results.

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This research is unique because it investigates a different geographical area and it covers a different time period than previous research. Earlier studies by Lang et al. (1989), Servaes (1991), Rau and Vermaelen (1998), Dong et al. (2003) and Moeller et al. (2005) focussed on the U.S. market, covering the time period 1968 – 2001. This research focuses on the European market which outperformed the U.S. market in terms of total value by over 300 billion dollar in 2007.3_{The period of 1999 – 2007 is interesting} because it covers a period of high stock market valuation (1999 – 2001) and low stock market valuation (2002 – 2004). Moeller et al. (2005) already showed that market-to-book ratios are positively related to stock market valuations. Dividing the sample period of 1999 – 2007 in calendar years, enables the possibility to study the relation between stock market valuations and a possible difference in abnormal returns between low and high market-to-book acquirers.

The remainder of this research is organised as follows. The next section gives an overview of existing literature according the market-to-book ratio and its influence on abnormal returns and method of payment during M&A activity. Section 3 will outline the data sample, some descriptive statistics and the methodology used. The results will be presented in section 4. Finally I will conclude and give recommendation for further research in section 5.

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2. Literature review

This chapter will analyse the relevant literature for this research. Section 2.1 will discuss the drivers of the market-to-book ratio. Section 2.2 gives an overview of prior research results on the relationship between the market-to-book ratio and abnormal returns for acquiring firms. Based on this earlier research the hypotheses for this research will be formulated. In section 2.3 the relationship between the market-to-book ratio and the incentives to pay with shares rather than cash is discussed. Finally, in section 2.4 the empirical results of the relationship betwe en the method of payment and abnormal returns will be discussed.

2.1. Drivers of the market-to-book ratio

The market-to-book ratio is based on market and book values. Market value depends on the balance among various investors’ expectations and speculations about a firms’ future performance. Several drivers can determine this future perception of investors and therefore influence the market value. Book value is based on accounting values which are influenced by a firm its accounting policies. Research resulted in many drivers of the market-to-book ratio. This section will describe the drivers of the market-to-book ratio found by earlier research and will show that the drivers are not all independent of each other. The influence of these drivers on the abnormal returns of acquiring shareholders will be discussed in section 2.2.

Performance

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dividends, a lower pay-out ratio will not affect the share price. While managerial performance and future investment opportunities appear to be two different variables, they are closely related to each other. A firm with high future investment opportunities will only be able to exploit these opportunities if it possesses a management that is aware of the future opportunities and is capable to anticipate on it. Fama and French (1992) relate a firms’ market-to-book ratio with financial distress. They have examined the returns of a large sample of stocks in the period 1940 - 1990 and found that a firms’ market-to-book ratio explains a large proportion of the variation in average stock returns. Fama and French (1992) argue that low market-to-book firms are associated with poor prospects relative to firms with high market-to-book ratios. Poor prospects increase the possibility of financial distress and are thus related to risk. However, poor future prospects can be the results of poor management and poor investment opportunities. So, although literature makes a distinction between investment opportunities (Hovakimian et al., 2001), managerial performance (Lang et al., 1989) and financial distress (Fama and French, 1992) as drivers of the market-to-book ratio, in this research these drivers will be assigned to performance since these drivers are not independent of each other.

Investor misvaluation

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ratio is driven by investor misvaluation. The interpretation of the market-to-book ratio by Lakonishok et al. (1994) is in line with the extrapolation hypothesis of Rau and Vermaelen (1998), which will be described in section 2.2.

Summarizing section 2.1, earlier research found a diverse set of drivers of the market-to-book ratio. However, not all drivers are independent of each other. This research defines performance and investor misvaluation as two clearly independent drivers of the market-to-book ratio. The results of the abnormal return calculations will show which driver influenced the returns for acquiring firms in Western Europe in the period 1999 – 2007. Though accounting policy is also a driver of a firms’ market-to-book ratio, it is beyond the scope of this research to take into account this driver since it is very time consuming to detect the influence of a firms’ accounting policy on its book value.

2.2. Empirical results

Although the consequences of mergers and acquisitions on shareholder returns of bidding firms are investigated very often, the results show only little consensus. Loughran and Vijh (1997) found that acquiring shareholders earn little to no short term abnormal returns around the announcement of mergers and acquisitions. Summarizing 130 studies, Bruner (2001) concludes that shareholders of acquiring firms do essentially break even on the long run. To examine whether mergers and acquisitions lead to abnormal announcement returns for acquiring shareholders, the following proposition is made:

Hypothesis 1: Mergers and acquisitions lead to abnormal returns for the shareholders of acquiring firms around the announcement date of mergers and acquisitions.

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high market-to-book firms acquirer low market-to-book firms.4_{Lang et al. (1989) argue} that the market-to-book ratio is a measure of managerial performance which will influence the deal negotiations since well managed bidders are able to get a better deal than poorly managed bidders. In addition they argue that well managed bidders are also able to better manage the targets’ current and future projects compared to poorly managed bidders, which will result in higher future cash flows for high market-to-book firms. So according to Lang et al. (1989) well managed bidding firms earn higher abnormal returns around the announcement of mergers and acquisitions than poorly managed firms. The results of Lang et al. (1989) and Servaes (1991) are in line with the performance hypothesis mentioned in section 2.1. Table 1 gives an overview of the results of earlier empirical research.

4_{Lang et al. (1989) and Servaes (1991) used tobin’s q instead of the market-to-book ratio. In}

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Authors (year) M/B CAAR Year Sample size

Event

window Country Notes

Lang, Stulz and H 3,83% ** 1968 - 1980 87 -5,5 U.S. Tender offers Walkling (1989) L -1,37%

Servaes (1991) H - L 6,36% * 1972 - 1987 704 -1,1 U.S. All takeovers

Rau and H -5,60% * 1980 - 1991 987 0,1080 U.S. Mergers and tender offers Vermaelen (1998) L 5,60% *

Dong, Hirshleifer, H -2,00% * 1978 - 2001 2922 -1,1 U.S. Mergers and acquisitions Richardson, Teoh L -0,40% *

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Moeller, Schlingemann H -10,60% * 1998 - 2001 4136 -1,1 U.S. Acquisitions and Stulz (2005) L Positive

* and ** = statistically significant at a 1% and 5% level.

Summary of earlier studies that examined the relationship between market-to-book ratios of acquiring firms and the CAAR around the announcement of M&A activity. M/B stands for market-to-book ratio, H stand for

high and L stands for low.

Table 1: Empirical results of earlier research

Controlled for method of payment and

organizational form Controlled for method of payment

Controlled for method of payment, size, multiple bidders and hostility

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measure the market-to-book ratio as an absolute number. Since the market-to-book ratio is sector specific (Lindenberg and Ross, 1991) their analysis does not control for sector specific influences on the market-to-book ratio. Moeller et al. (2005) found that during the period 1998 – 2001, acquiring U.S. shareholders lost $240 billion within the two days surrounding acquisition announcements. This considerable loss is initiated by the 2.1% biggest deals in that period made by large firms with extremely high market-to-book ratios. Without this small percentage of big deals, the announcement returns for acquiring U.S. shareholders would have been $157 billion positive. Moeller et al. (2005) argue that mergers and acquisitions made by high market-to-book acquirers lead to the reconsideration of the high stand-alone values of these firms, which will result in a correction of this stand-alone value. Rau and Vermaelen (1998) found long-term underperformance of high market-to-book firms after the announcement of mergers and acquisitions. They state that the market overreacts to the past performance of acquiring firms (extrapolation hypothesis). Acquirers with high market-to-book ratios signal high future growth in cash flows and earnings to the market. Relying on such past performance, the market may give managers of these acquiring firms the “benefit of the doubt” when approving their acquisition plans. Though the results of Dong et al. (2003), Moeller et al. (2005) and Rau and Vermaelen (1998), are in contrast with earlier results of Lang et al. (1989) and Servaes (1991), they are in line with the misvaluation hypothesis of Lakonishok et al. (1994) which is described in section 2.1. Based on most recent research, the following proposition is made:

Hypothesis 2: Low market-to-book acquirers earn higher abnormal returns than high market-to-book acquirers around the announcement of mergers and acquisitions.

2.3. The market-to-book ratio and method of payment

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examined by Martin (1996). He found a positive relation between market-to-book ratios and firms’ incentives to pay by means of shares. Firms with a market-to-book ratio of 2.0 are 2.7 times more likely to pay by means of shares than firms with a market-to-book ratio of 1.0. Jensen (2004) found that the “large loss deals” between 1998 – 2001, made by firms with extremely high market-to-book ratios (Moeller et al., 2005), used equity as payment method in 71.6% of the deals opposed to 35.2% for the other bidders in the same period and 30.3% for all bidders in the period 1980 – 1997. Jensen relates a firms’ market-to-book ratio to investor misvaluation and concludes that managers of overvalued firms rather use their overvalued shares as method of payment than cash. The results of Jensen (2003) are in line with the asymmetric information hypothesis introduced by Myers and Majluf (1984). They argue that managers with information about the intrinsic value of their firm, who act in the interest of their shareholders, will use shares if they are overvalued. Based on the results of Martin (1996) and Jensen (2004) the following proposition is made:

Hypothesis 3: High market-to-book acquirers are more likely to use shares as method of payment than low market-to-book acquirers.

2.4. The method of payment and abnormal returns

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asymmetric information hypothesis as a determinant of announcement returns, low market-to-book acquirers earn higher announcement returns than high market-to-book acquirers irrespective the method of payment. In addition, if the asymmetric information hypothesis dominates, cash acquirers earn higher announcement returns than share acquirers irrespective the market-to-book ratio.I will make use of graphical examples to clarify the method of Sudarsanam and Mahate (2003). In the next three figures I will demonstrate possible announcement returns as a result of the domination of (n)either the misvaluation hypothesis (n)or the asymmetric information hypothesis. If neither the misvaluation hypothesis nor the asymmetric information hypothesis dominates as a determinant of announcement returns, the situation described in figure 1 occurs. When comparing the announcement returns horizontally, cash acquirers earn higher returns than share acquirers. When comparing the announcement returns vertically, low market-to-book acquirers earn higher returns than high market-market-to-book acquirers. When comparing diagonally (shaded areas), no difference in announcement returns is found. If I find evidence for the situation presented in figure 1, I will conclude that neither the asymmetric information hypothesis nor the misvaluation hypothesis dominates as a determinant of announcement returns.

Cash Shares High M/B Low M/B 4 0 0 -4 + + -+ -+ Asymmetric information: cash 2 shares -2 Misvaluation: low M/B 2 high M/B -2 Figure 1

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low book acquirers earn higher announcement returns than high market-to-book acquirers, irrespective the method of payment. If I find evidence for the situation presented in figure 2 and the difference in announcement returns between high market-to-book cash acquirers and low market-market-to-book share acquirers is significantly positive, I will conclude that the asymmetric information hypothesis dominates the misvaluation hypothesis as a determinant of announcement returns.

Cash Shares 6 -2 2 -6 High M/B Low M/B + + -+ -+ Asymmetric information: cash 4 shares -4 Misvaluation: low M/B 2 high M/B -2 Figure 2

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Cash Shares 6 2 -2 -6 High M/B Low M/B + + -+ -+ Asymmetric information: cash 2 shares -2 Misvaluation: low M/B 4 high M/B -4 Figure 3

Sudarsanam and Mahate (2003) found stronger support for the asymmetric information hypothesis. In line with their hypothesis the following proposition is formulated:

Hypothesis 4: Low and high market-to-book acquirers who pay by means of shares earn lower announcement returns than low and high market-to-book acquirers who pay by means of cash.

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3. Data and methodology

In this section the data selection and the event study methodology will be described. Section 3.1 will outline the sample selection criteria and will give an overview of the sample characteristics. The event study methodology is presented in section 3.2.

3.1 Data sample and sample statistics

The Zephyr database (part of Bureau van Dijk electronic publishing) is used to construct a sample of 900 mergers and acquisitions. For every year in the research period the 100 largest deals with their accompanying International Securities Identifying Numbers (ISIN) are selected. The ISIN will be used to collect the daily stock prices with the use of Datastream. The daily stock prices are adjusted for capital gains. Acquiring firms without an ISIN or without sufficient share price data for calculating normal returns in the estimation window, are substituted by the next biggest deal during the same year to minimize the loss of data. Delisting is the most common reason for firms without an ISIN. The exclusion of firms can lead to survivorship bias. If the excluded firms had negative returns, their exclusion would bias the sample return estimates upward. However, Higson and Elliott (1998) found that the difference in announcement returns between tests including and excluding non-surviving firms are not statistically significant. Therefore they argue that survivorship bias not appears to be a serious problem. They Table 2 gives an overview of the sample selection criteria:

Selection criteria Specification

Time period 01/01/1999 to 31/12/2007

Geography Acquirer and target situated in Western Europe

Deal status Completed

Percentage of stake > 50%

Quoted companies Listed acquirer

Deal type Mergers and acquisitions

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The choice for the time period 1999 - 2007 is threefold. First, it includes the period 1999 – 2001, a bull market period caused by mega capitalization stocks active in the Technology-Media-Telecommunications (TMT) sector (Koller et al., 2005). Furthermore this period was dominated by large loss deals made by firms with extremely high market-to-book ratios (Moeller et al., 2005). Secondly, including the period 1999 – 2001 enables the option to compare the research results of Moeller et al. (2005) with the results of this research. Extending the research period of Moeller et al. (2005) to 2007 enables the option to conclude whether high market-to-book firms are als o initiators of large loss deals in the period 2002 - 2007. Finally, the broad research period covers multiple stock market tendencies which makes it possible to examine the relationship between those tendencies and a possible difference between announcement returns of low and high market-to-book firms. To realize this, the data will be analysed by year. The target and acquirer should be situated in Western Europe. This because related research has focused on U.S. mergers and acquisitions only . Furthermore, M&A activity in Europe increased by 31% in 2007 to $ 1.78 trillion, exceeding the U.S. ($ 1.57 trillion) for the second time in history.5_{This makes Europe the biggest merger and acquisition} market of the world.

In this research I will use the market-to-book ratio as provided by Datastream. The market value per share is defined as the daily closing price per share adjusted for capital gains. The market value will be measured on the last day of the estimation window through which it is not affected by possible abnormal returns during the event window. The book value per share represents the book value of equity divided by the outstanding shares at the firms’ last fiscal year end. Earlier research used various methods for the classification of the market-to-book ratio in low and high categories. Lang et al. (1989) placed firms with book ratios above (below) one in the high (low) market-to-book category. Their choice is motivated by the theory that firms with a market-to-market-to-book ratio below one have projects with negative net present values (Lang and Litzenberger, 1989). However, a firms’ market-to-book ratio is industry specific (Lindeberg and Ross, 1981). Therefore, this research will classify the market-to-book ratios of bidding firms in low and high categories based on the industry average and median market-to-book

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ratios. Bidding firms with an above (below) industry average/median market-to-book ratio will be classified as high (low) market-to-book firms. This is in line with earlier research of Servaes (1991) and Ang and Chen (2006). The median market-to-book ratio is chosen since the samples’ average and median market-to-book ratio diverge which implies the existence of outliners. The classification of the sample by industry categories will be realized using the North American Industry Classification System (NAICS 2002). To limit the number of industry categories the first two digits of the NAICS 2002 are used.

To test whether extremely high market-to-book acquirers are also initiators of large losses during the period 1999 - 2007, the sample will also be categorized by industry-relative market-to-book ratios. This is in line with the methodology of Ang and Cheng (2003). Ten categories based on industry-relative market-to-book ratios will be constructed, where the first category includes the 0-10% firms with the lowest relative market-to-book ratio and so on. The firms with the 10% highest industry-relative market-to-book ratios are placed in the 90-100% category. The industry-industry-relative market-to-book ratio is calculated by dividing a firms’ market-to-book ratio by its industry average market-to-book ratio.

As a benchmark the MSCI Europe index is used since it shows the highest geographical similarity with the sample. All countries covered by the MSCI European Index are included in the sample. Only two countries in the sample (Iceland and Liechtenstein), with a total of 9 deals, are not included in the MSCI Europe index.

Sample characteristics

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Country (acquirer) No. of events Industry Classification No. of events

Austria 11 Mining 22

Belgium 19 Utilities 57

Denmark 14 Construction 59

Finland 23 Manufacturing 241

France 103 Wholesale Trade 51

Germany 57 Retail Trade 39

Greece 10 Transportation and Warehousing 33

Iceland 8 Information Services 94

Ireland 24 Finance and Insurance 163

Italy 70 Real Estate, Rental and Leasing 17

Liechtenstein 1 Professional, Scientific, and Technical 55

Norway 16 Services

Portugal 8 Administrative and Support and Waste 22

Spain 57 Management and Remediation Services

Sweden 46 Educational Services 2

Switzerland 34 Health Care and Social Assistance 5

The Netherlands 44 Arts, Entertainment and Recreation 2 United Kingdom 355 Accommodation and Food Services 38

Total 900 Total 900

Table 3: Number of events per country and industry

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1999 2000 2001 2002 2003 2004 2005 2006 2007 All years M/B (N = 900)* Mean 4,00 5,25 2,87 1,91 2,25 2,24 2,30 2,27 2,88 2,89 Median 2,57 2,58 2,27 1,98 1,63 1,65 1,70 1,97 2,47 2,09 Cash 65% 63% 68% 75% 64% 72% 63% 66% 64% 66,67% Shares 23% 21% 23% 15% 22% 18% 18% 21% 26% 20,78% Other 12% 16% 9% 10% 14% 10% 19% 13% 10% 12,56%

Table 4: Market-to-book ratio and method of payment per year

Method of payment (N = 900)

* For average and median market-to-book ratios per industry category see appendix table A23.

3.2. Methodology

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Figure 4: Event time

Abnormal returns

To measure abnormal returns, information about the expected return is needed first. Several models exist to calculate the expected returns, such as: CAPM, Fama and French three factor model, the mean return model and the market and risk adjusted model (Brown and Warner, 1985). By adding factors for size (market capitalization) and value (book-to-market ratio) to the CAPM, Fama and French constructed the three-factor-model. However, the gains from using multifactor models are small as proven by Brown and Warner (1980). They have shown that relatively simple models often yield results similar to those of more sophisticated models when measuring expected returns. MacKinlay (1997) shows that the market model represents a potential improvement over the constant mean return model, since the market model removes the portion of the return that is related to the variation in the market return. This can lead to increased ability to detect event effects. In this research the market model based on the event study methodology of MacKinlay (1997) is used to make results in line with research of Lang et al. (1989), Servaes (1991), Dong et al. (2003) and Moeller et al. (2005). For any security i the expected return for the model is:

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E

(

R

_it

)

=

α

_i

+

β

_i

R

_mt

Where E(R_it)is the expected return for security i at time t and Rmt is the return of the

market portfolio (MSCI Europe Index) at time t. α and ß are estimated values of true

parameters through Ordinary Least Squares (OLS) regression. The market model parameters will be estimated over the 200 days prior to the event window.

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The abnormal return is defined as:

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AR

it

=

R

it

−

α

i

−

β

i

R

mt

Where

AR

it is the abnormal return for security i at time t, and

R

mt is the actual daily return. The actual daily return is calculated as the difference in stock price at t and t-1

divided by the stock price at t-1.

The abnormal returns of the individual shares will be aggregated by using ARit to

calculate the average abnormal returns for each event day. The average abnormal return, given N events, is defined as:

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∑

=

N i it t

AR

N

AR

1

Since the estimation window is large, the variance is defined following the methodology of MacKinlay (1997): (4)

∑

=

N i t t

N

AR

1 2 2

1 )

var(

σε

If the AR_t differs significantly from zero, I will conclude that the market reacted on the

merger or acquisition announcement. For the aggregation it is assumed that there is not any overlap in the event windows of the included shares. This implies that the abnormal returns and the cumulative abnormal returns will be independent across shares.

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With a variance: (6)

∑

= =

=

2 1 2 , 1

)

var(

)

var(

t t t t t t t

AR

CAR

The number of days to be included for the average CAR calculations will be based on the significance of the average abnormal returns .

Normality

The results of the abnormal return calculations are not sufficient to conclude that the event created or destroyed shareholder value. Therefore the observed abnormal returns need to be significant different from zero. Before determining the significance of the abnormal returns, the normality of the abnormal returns in the estimation window needs to be tested since non-normality can decrease the validity of the t-test. “The normality assumption is important for the exact finite sample results to hold. Without assuming normality, all results would be asymptotic” (MacKinlay, 1997). To test for normality the Jarque-Bera (JB) test is used. The JB test measures the departure of normality and is based on the Skewness (S) and the Kurtosis (K) of the abnormal returns (Jarque and Bera, 1987). The null hypothesis assumes normality and it is tested at a 5% significance level (critical value 5,99). The JB test is constructed as:

(7) _

(

)

    − + = 4 3 6 2 2 K S N JB

The results of the JB test are presented in table A1 of the appendix. The abnormal returns are not normal distributed in the years 1999, 2003 and 2007. Therefore non-parametric tests will also be conducted.

Parametric test

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test is used with the null hypothesis that the average abnormal returns and the average CAR’s for a given event window is equal to zero. The test is defined as:

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The critical values are 1% and 5% with N-1 degrees of freedom. If H0 is rejected, the announcement created or destroyed value for bidding firms’ shareholders.

To test whether low market-to-book firms earn higher abnormal returns during M&A activity the following t-test is used:

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To test whether high market-to-book firms more often pay by means of shares than low market-to-book firms, the following test of Keller (2005) is used:

(10)     + − − = 2 1 1 1 ) ˆ 1 ( ˆ ) ˆ ˆ ( N N p p p p z h l

Where

pˆ

h is the proportion mergers and acquisitions announced by high market-to-book firms paid by means of shares and

pˆ

l is the proportion mergers and acquisitions announced by low market-to-book firms paid by means of shares. pˆ is the total

proportion mergers and acquisitions paid by means of shares.

Non-parametric tests

For the parametric test to be valid, the underlying distribution must me normal. To test the robustness of the results, non parametric tests will also be conducted. The non-parametric rank test is better specified under the null hypothesis and more powerful

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test has the advantage that it does not have the requirements of symmetric abnormal returns. Furthermore in comparison with the parametric test, the specification of the rank test is less affected by event day abnormal returns variance increase. The rank test statistic with a null hypothesis of no abnormal returns is defined as:

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∑

= − = N i i i K S K K N t 1 0 ) ( 1 Where (12)

∑ ∑

=

(

)

= =       ₋ = 2 0 2 1 1 1 ) ( t t t t N i i it K K N T K S

The abnormal returns of each firm will be ranked (

K

it) over the period that includes the estimation and the event window (T). The ranking procedure transforms a distribution of abnormal returns in an uniform distribution of rank value, that is independent of the asymmetry of the original distribution (Corrado, 1989). The ranks in the event period for each firm will be compared with the expected average rank (Ki=0.5 +T/2).

The generalized sign test examines whether the number of firms with positive (cumulative) abnormal returns in the event window exceeds the number expected in the absence of abnormal performance (Cowan, 1992). The expected number is based on the fraction of positive abnormal returns in the 200 day estimation period. The generalized sign test is defined as:

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The test statistic uses the normal approximation to the binomial distribution with parameter pˆ. w is defined as the number of stocks in the event window for which the (cumulative) abnormal return is positive. The generalized sign test statistic is defined as:

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[

ˆ(1 ˆ)

]

ˆ p p n p n w ZG − − = OLS regression

To test whether there is a relation between the average CAR’s and the industry-relative market-to-book ratios, an ordinary least squares regression analysis will be conducted. The regression is:

(16) CARit =α₀ +α₁ _M _B_i M_B_ind_+ ε

Where i

B

M _{is the market-to-book ratio of firm i and}

ind

B

M _{is the industry average}

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4. Results

This section will answer the question whether the market-to-book ratio influences the abnormal returns for acquiring firms and for what reason. Section 4.1 will present the results of the abnormal return calculations. The influence of the market-to-book ratio on abnormal returns will be discussed in Section 4.2. Section 4.3 discusses whether the market-to-book ratio determines the method of payment and finally, section 4.4 will examine if the method of payment can explain the influence of the market-to-book ratio on bidding firms’ abnormal returns.

4.1. Results of the abnormal return calculations

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1999 2000 2001 2002 2003 2004 2005 2006 2007 -20 -0,059 -0,112 -0,094 0,168 -0,026 -0,122 -0,178 -0,053 0,013 -0,124 -19 0,101 0,173 0,681 ** 0,277 -0,181 0,072 -0,044 -0,058 0,225 -0,239 -18 -0,024 0,132 0,255 -0,145 0,108 -0,279 -0,027 -0,128 0,081 -0,213 -17 -0,023 -0,039 -0,031 0,137 -0,017 -0,046 -0,220 -0,122 -0,089 0,218 -16 -0,048 -0,080 -0,095 0,056 -0,122 -0,082 -0,053 0,023 -0,136 0,059 -15 -0,044 0,273 0,118 -0,444 0,055 0,066 -0,015 -0,164 -0,110 -0,171 -14 -0,064 -0,075 -0,405 -0,119 0,063 0,174 -0,190 0,004 0,327 ** -0,359 ** -13 -0,017 0,063 -0,375 -0,137 0,319 0,184 0,001 -0,023 -0,165 -0,020 -12 -0,099 -0,101 -0,238 0,063 -0,160 -0,039 -0,021 -0,032 0,009 -0,372 ** -11 -0,038 -0,040 -0,159 0,054 -0,304 -0,064 0,178 0,039 -0,042 -0,001 -10 -0,070 0,057 -0,052 -0,412 0,035 -0,122 -0,135 -0,025 0,025 -0,005 -9 -0,004 0,289 -0,277 -0,072 0,117 -0,148 0,328 0,047 -0,110 -0,211 -8 -0,012 -0,243 -0,169 -0,298 0,117 -0,002 0,220 0,074 0,108 0,086 -7 0,009 -0,015 -0,460 0,501 ** 0,021 0,031 0,072 -0,220 0,135 0,012 -6 0,043 -0,084 -0,053 -0,249 0,259 0,185 0,093 0,203 -0,003 0,034 -5 -0,077 0,090 0,000 0,045 -0,376 0,039 -0,182 -0,121 -0,033 -0,159 -4 0,088 0,004 -0,276 0,272 0,013 0,406 0,056 0,339 ** 0,111 -0,131 -3 0,074 -0,049 0,371 0,033 -0,334 0,093 0,140 0,222 0,034 0,159 -2 0,091 -0,043 0,348 -0,107 0,054 0,178 0,370 ** -0,129 0,145 0,003 -1 0,027 -0,369 0,007 0,036 -0,036 0,091 0,256 0,027 0,222 0,009 0 0,604 * 0,886 * 0,708 * 0,235 0,958 * 0,263 1,002 * 0,826 * 0,164 0,394 ** 1 0,496 * 0,793 * 0,113 1,042 * 0,356 0,360 -0,003 0,612 * 1,024 * 0,166 2 -0,019 0,181 -0,188 0,088 -0,320 0,177 -0,387 ** 0,548 * -0,308 * 0,036 3 0,052 0,049 -0,153 0,162 0,091 0,125 -0,050 -0,239 0,400 * 0,086 4 0,044 0,006 0,276 0,530 ** 0,084 -0,117 0,023 -0,192 -0,138 -0,071 5 -0,009 0,028 0,131 -0,041 -0,150 0,099 -0,016 0,125 -0,234 -0,021 6 -0,024 0,091 -0,164 0,365 -0,296 0,501 ** -0,265 -0,257 -0,096 -0,095 7 -0,043 0,045 -0,793 * -0,005 0,046 0,298 -0,035 0,030 -0,148 0,174 8 0,034 0,372 0,031 0,120 0,218 -0,101 0,015 -0,113 -0,167 -0,072 9 -0,025 0,140 -0,134 0,128 0,052 -0,102 -0,016 0,216 -0,222 -0,282 10 -0,019 0,028 -0,130 0,035 0,007 0,021 0,094 -0,127 -0,101 0,003 11 -0,041 -0,232 -0,467 -0,038 0,066 0,095 0,140 -0,041 0,040 0,066 12 -0,122 0,036 -0,249 0,008 -0,163 -0,124 -0,019 -0,137 0,107 -0,555 * 13 0,035 0,077 0,151 0,275 0,028 -0,181 0,000 0,073 -0,205 0,096 14 0,000 0,203 -0,544 ** 0,288 -0,017 0,142 0,216 0,076 -0,133 -0,228 15 0,116 0,016 0,131 0,251 0,134 0,112 0,321 -0,034 0,036 0,075 16 -0,134 -0,179 -0,469 -0,172 -0,019 -0,169 -0,137 -0,135 -0,081 0,151 17 0,026 0,021 0,058 -0,019 -0,137 0,152 0,212 -0,069 0,206 -0,189 18 0,108 -0,152 0,250 0,073 0,388 0,225 -0,105 -0,142 0,422 * 0,016 19 0,034 0,295 0,099 -0,010 -0,022 0,096 0,085 -0,157 0,058 -0,133 20 0,033 -0,139 0,438 -0,003 0,179 0,305 -0,085 0,163 -0,445 * -0,115

Table 5: The average abnormal returns for acquiring companies around the announcement of mergers and acquisitions in Western Europe, (N = 900).

Event day

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Table 6 shows significant positive average CAR’s within the two days event window, for every year in the research period. Therefore the first hypothesis is accepted that mergers and acquisitions lead to abnormal returns for shareholders of acquiring companies around the announcement date. The results of the parametric t-test are consistent with the results of the non-parametric generalized sign test according the all years results. The results are in line with Moeller et al. (2004) who found small positive abnormal returns for acquiring firms’ shareholders.

1999 2000 2001 2002 2003 2004 2005 2006 2007 0,1 1,10 * 1,68 * 0,82 ** 1,28 * 1,31 * 0,62 ** 1,00 * 1,44 * 1,19 * 0,56 **

-1,1 1,13 * 1,31 * 0,83 1,31 * 1,28 * 0,71 1,26 * 1,46 * 1,41 * 0,57

-5,5 1,37 * 1,58 ** 1,34 2,29 * 0,34 1,71 ** 1,21 ** 2,02 * 1,39 * 0,47

Table 6: The cumulative average abnormal returns in % for acquiring companies around the announcement of mergers and acquisitions in Western Europe, (N = 900). Event

window

All years

* and ** = statistically significant at a 1% and 5% level. Results of the (non)parametric tests are presented in the appendix.

4.2. Results on the market-to-book ratio and the average CAR’s

Section 4.1 showed that shareholders of acquiring firms in Western Europe earn positive abnormal returns around merger and acquisition announcements in the period 1999 – 2007. This section tries to find a relat ionship between these abnormal returns and the market-to-book ratios of the companies involved.

To examine the difference in abnormal returns between low and high market-to-book acquirers, thirteen different categories are constructed based on NAICS 2002 codes. Although the sample consists of sixteen industry categories, three categories are left out because of their small number of events per category.6_{Table 7 shows a positive} difference in average CAR’s between low and high market-to-book firms for the whole sample at a 1% significance level. This positive difference exists for all event windows. The results of the parametric t-test are in line with the results of the non-parametric generalized sign test. Looking at the industry categories individually, not all differences

6_{These categories are: Education services, Health care and social assistance and Art s, entertainment and}

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Industry category M/B split 0,1 -1,1 -5,5 0,1 -1,1 -5,5 0,1 -1,1 -5,5 All industries (N = 891) Average 1,29 * 1,41 * 1,82 * 0,70 * 0,62 * 0,74 0,59 * 0,79 * 1,07 **

Median 1,17 * 1,30 * 1,74 * 0,58 * 0,49 * 1,01 * 0,60 * 0,81 * 0,73 Mining (N = 22) Average 0,56 0,74 2,58 1,49 1,74 3,80 -0,93 -1,00 -1,22 Median 0,40 0,25 1,70 1,48 2,05 4,46 -1,08 -1,80 -2,76 Utilities (N = 57) Average 1,10 * 1,27 * 1,23 0,56 0,21 -0,34 0,53 1,07 1,56 Median 0,59 0,41 0,88 1,19 ** 1,33 ** 0,43 -0,60 -0,92 0,45 Construction (N = 59) Average 1,48 * 1,11 2,61 ** 1,87 * 1,19 ** 1,72 -0,38 -0,08 0,89 Median 2,15 * 1,49 * 2,29 ** 1,32 * 0,84 1,71 0,83 0,65 0,58 Manufacturing (N = 241) Average 1,82 * 1,98 * 2,22 * 1,58 * 1,64 * 1,96 * 0,24 0,34 0,26 Median 2,35 * 2,62 * 2,52 * 1,10 0,89 1,53 * 1,25 * 1,73 * 0,99 Wholesale Trade (N = 51) Average 2,53 * 2,46 * 2,72 * 0,82 1,70 ** 1,36 1,71 ** 0,76 1,36 Median 3,02 * 2,99 * 3,17 ** 0,94 1,45 ** 1,41 2,09 * 1,54 1,76 Retail Trade (N = 39) Average 2,92 * 3,22 * 6,13 * 0,64 0,23 2,92 2,28 ** 2,99 ** 3,20 Median 3,74 * 4,36 * 5,37 * 0,88 0,50 5,08 * 2,86 * 3,87 * 0,29 Average -0,02 0,30 1,88 0,55 0,24 -1,99 -0,57 0,06 3,87 Median -1,43 ** -1,20 -0,06 1,83 * 1,87 ** 1,52 -3,26 * -3,07 ** -1,58 Average 0,48 0,75 0,41 -0,44 -0,50 -4,90 ** 0,91 1,25 5,31 ** Median 0,32 0,74 0,01 0,09 0,02 -2,35 0,23 0,72 2,36 Average 0,07 0,14 0,12 0,47 0,38 1,15 -0,40 -0,24 -1,03 Median 0,23 0,36 0,22 0,22 0,11 0,80 0,01 0,25 -0,58 Average -1,20 -1,27 -1,51 3,15 * 2,71 ** -0,49 -4,35 * -3,98 * -1,02 Median -1,20 -1,27 -1,51 3,15 * 2,71 ** -0,49 -4,35 * -3,98 * -1,02 Average 2,56 * 2,70 * 2,39 -2,89 * -2,61 -2,72 5,45 * 5,30 * 5,10 Median 2,65 * 2,30 * 2,28 -0,64 0,04 -0,43 3,29 * 2,26 2,71 Average 0,72 -0,23 0,87 2,51 2,53 2,06 -1,79 -2,77 -1,18 Median 1,85 1,33 3,58 0,74 -0,04 -1,07 1,11 1,37 4,65 Average 1,83 * 2,23 * 3,97 * 1,24 0,04 2,60 0,59 2,19 1,37 Median 1,70 * 2,13 * 3,88 * 1,69 ** 1,29 3,41 0,01 0,84 0,47 Information Services (N = 94)

Finance and Insurance (N = 163)

Real Estate, Rental and Leasing (N = 17)

Professional, Scientific and Technical Services (N = 55)

Table 7: The cumulative average abnormal returns in % for acquiring companies around the announcement of mergers and acquisitions in Western Europe, divided by industry category and market-to-book ratio (N = 891).

Event window

Transportation and Warehousing (N = 33)

Administrative and Support Services (N = 22)

Accommodation and Foodservices (N = 38)

Difference between low and high market-to-book High market-to-book

Low market-to-book

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Table 8 presents the average CAR’s based on industry-relative market-to-book ratio categories to test whether the results presented in table 7 are caused by extremely high market-to-book firms. The results in table 8 show positive average CAR’s for all categories within the two days event window. Even the firms with the 10% relative highest market-to-book ratios earn an (insignificant) average CAR of 0,70%. The results within the three days event window also show positive average CAR’s for firms in the highest marke t-to-book category. Therefore the results are in contrast with the results of Moeller et al. (2005). The results of the OLS regression show a (insignificant) negative relation at a 5% level between the industry-relative market-to-book ratios and the average CAR’s. The results of the OLS regression are presented in table A12 of the appendix. 0,1 -1,1 -5,5 0 - 10% 1,56 * 1,39 * 1,93 ** 10 - 20% 1,57 * 2,04 * 2,73 * 20 - 30% 2,81 * 3,08 * 2,95 * 30 - 40% 1,73 * 1,83 * 2,94 * 40 - 50% 0,89 * 0,77 ** 0,09 50 - 60% 0,01 -0,20 0,65 60 - 70% 0,81 ** 0,85 ** 2,37 * 70 - 80% 0,71 ** 0,50 -0,35 80 - 90% 0,44 0,65 0,99 90 - 100% 0,70 0,65 -0,31 Event window M/B category

Table 8: The average CAR's in % for acquiring companies around the

announcement of mergers and acquisitions in Western Europe, divided by

market-to-book category (N = 891).

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market-to-book acquirers do not earn lower announcement returns in the period 1999 - 2001 than in other years. In the years 1999 – 2000 high market-to-book acquirers earned even higher announcement returns than low market-to-book acquirers. So although high valuation periods result in high market-to-book ratios, there is no evidence that these high valuation periods can explain the positive difference in average CAR’s between low and high market-to-book firms as presented in table 7.

Year 0,1 -1,1 -5,5 0,1 -1,1 -5,5 0,1 -1,1 -5,5 All years 1,29 * 1,41 * 1,82 * 0,70 * 0,62 * 0,74 0,59 * 0,79 * 1,07 ** 1999 1,14 * 1,03 ** 1,83 ** 2,20 * 1,75 * 1,05 -1,06 -0,72 0,78 2000 0,93 ** 0,78 3,14 * 1,06 ** 0,96 0,14 -0,13 -0,18 3,00 2001 1,87 * 2,25 * 3,87 * -0,50 -0,33 -0,37 2,37 * 2,58 * 4,23 ** 2002 1,21 * 1,46 * 0,25 0,84 0,43 0,47 0,37 1,03 -0,22 2003 0,72 0,90 1,38 1,06 0,57 1,78 -0,33 0,32 -0,40 2004 1,03 * 1,26 * 0,99 -0,03 0,55 1,67 1,06 ** 0,70 -0,68 2005 2,27 * 2,29 * 2,69 * -0,30 -0,68 -0,19 2,57 * 2,97 * 2,89 * 2006 0,88 * 1,13 * 1,64 ** 1,74 * 2,02 * 1,23 -0,86 -0,89 0,41 2007 1,49 * 1,51 * 0,83 0,21 0,30 0,91 1,28 ** 1,20 -0,08

Table 9: The average CAR's in % for acquiring companies around the announcement of mergers and acquisitions in Western Europe, divided by year and market-to-book

ratio (N = 891).

Difference between low and high market-to-book Low market to book firms High market-to-book firms

(N = 560) (N = 331)

4.3. Results on the market-to-book ratio and method of payment

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M/B ratio

number % number %

Low 370 66,19 101 18,07

High 224 67,67 79 23,87

Difference 1,48 5,80 ** Table 10: The method of payment of Western European acquirers divided by market-to-book ratio

(N = 774).

Cash Shares

* and ** = statistically significant at a 1% and 5% level. Results of the parametric test are presented in the appendix.

Table 10 shows that high market-to-book firms significantly more often use shares as payment method than low market-to-book firms. The results are in line with Myers and Majluf (1984), Martin (1996), Jensen (2004) and Moeller et al. (2005). In contrast to their results, low market-to-book firms do not use cash more often as method of payment compared to high market-to-book firms. However, the hypothesis that high market-to-book acquirers are more likely to use shares as method of payment than low market-to-book acquirers is accepted.

4.4. Results on the method of payment and abnormal returns

Section 4.3 showed that high market-to-book firms are more likely to use shares as method of payment than low market-to-book firms. This section tries to expla in the difference in average CAR’s between low and high market-to-book acquirers by examining the method of payment.

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Cash Shares (N = 594) (N = 180)

0,1 1,20 * 0,43 0,77 *

-1,1 1,15 * 0,66 ** 0,49

-5,5 1,45 * 0,33 1,12

Table 11: The cumulative average abnormal returns in % for acquiring companies around the announcement of mergers and acquisitions in Western Europe, divided by

method of payment (N = 774).

Method of payment

Difference cash and shares Event

window

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M/B Cash Shares Low M/B 1,19 * 0,69 *

High M/B 1,26 * 0,05 * and ** = statistically significant at a 1% and 5% level. Results of the (non)parametric tests are presented in the appendix.

Table 12: The cumulative average abnormal returns in % for acquiring

companies within the two days event window around the announcement of mergers and acquisitions in Western Europe, divided by method of payment and

market-to-book ratio (N = 774).

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5. Conclusion

This section will give the main conclusions concerning the four hypotheses of this research and will answer the question whether the market-to-book ratio is capable of explaining abnormal returns for acquiring firms.

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determinant of abnormal returns around the announcement of mergers and acquisitions. This is in line with Sudarsanam and Mahate (2003).

5.1. Recommendations for further research

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Appendix

1999 2000 2001 2002 2003 2004 2005 2006 2007 Skewness 0,1901 -0,4944 0,2134 0,0992 0,0511 0,5473 0,1591 0,1064 0,2365 -0,1502 Kurtosis 3,4828 3,4212 3,1206 3,1589 2,8873 3,9478 2,8516 2,7654 2,9290 5,3169 Jarque-Bera 3,1468 9,6266 1,6394 0,5385 0,1929 17,4694 1,0274 0,8358 1,9062 45,4864 Probability 0,2073 0,0081 0,4406 0,7640 0,9081 0,0002 0,5983 0,6584 0,3855 0,0000 Observations 200 200 200 200 200 200 200 200 200 200 All years

(45)

1999 2000 2001 2002 2003 2004 2005 2006 2007 -20 -0,8687 -0,4717 -0,3611 0,7295 -0,1282 -0,5370 -1,0602 -0,3961 0,0828 -0,7028 -19 1,4851 0,7262 2,6048 ** 1,2065 -0,8774 0,3163 -0,2607 -0,4277 1,4835 -1,3594 -18 -0,3545 0,5556 0,9748 -0,6311 0,5222 -1,2328 -0,1597 -0,9479 0,5362 -1,2088 -17 -0,3429 -0,1653 -0,1202 0,5971 -0,0801 -0,2036 -1,3098 -0,9041 -0,5850 1,2368 -16 -0,7046 -0,3351 -0,3652 0,2438 -0,5903 -0,3610 -0,3150 0,1681 -0,8961 0,3343 -15 -0,6427 1,1472 0,4532 -1,9323 0,2665 0,2919 -0,0896 -1,2120 -0,7283 -0,9713 -14 -0,9516 -0,3147 -1,5486 -0,5189 0,3041 0,7680 -1,1320 0,0313 2,1607 ** -2,0410 -13 -0,2523 0,2654 -1,4350 -0,5959 1,5470 0,8107 0,0057 -0,1741 -1,0888 -0,1122 -12 -1,4610 -0,4260 -0,9115 0,2758 -0,7745 -0,1710 -0,1266 -0,2358 0,0589 -2,1150 ** -11 -0,5551 -0,1691 -0,6078 0,2367 -1,4768 -0,2817 1,0590 0,2882 -0,2745 -0,0069 -10 -1,0370 0,2416 -0,1995 -1,7925 0,1683 -0,5364 -0,8019 -0,1816 0,1669 -0,0265 -9 -0,0612 1,2133 -1,0578 -0,3134 0,5698 -0,6549 1,9494 0,3464 -0,7277 -1,1964 -8 -0,1769 -1,0232 -0,6468 -1,2965 0,5689 -0,0100 1,3087 0,5460 0,7106 0,4896 -7 0,1280 -0,0620 -1,7595 2,1799 ** 0,1042 0,1383 0,4285 -1,6290 0,8878 0,0677 -6 0,6321 -0,3519 -0,2028 -1,0810 1,2551 0,8187 0,5526 1,5032 -0,0221 0,1947 -5 -1,1432 0,3786 0,0014 0,1946 -1,8256 0,1711 -1,0813 -0,8979 -0,2154 -0,9049 -4 1,2991 0,0148 -1,0572 1,1827 0,0644 1,7932 0,3309 2,5088 ** 0,7306 -0,7452 -3 1,0985 -0,2046 1,4208 0,1414 -1,6211 0,4126 0,8343 1,6454 0,2276 0,9002 -2 1,3406 -0,1806 1,3302 -0,4660 0,2617 0,7856 2,1989 ** -0,9571 0,9547 0,0162 -1 0,3977 -1,5530 0,0286 0,1554 -0,1742 0,3999 1,5250 0,2009 1,4634 0,0492 0 8,9138 * 3,7240 * 2,7084 * 1,0224 4,6516 * 1,1607 5,9606 * 6,1230 * 1,0856 2,2348 * 1 7,3158 * 3,3337 * 0,4320 4,5320 * 1,7281 1,5877 -0,0152 4,5321 * 6,7569 * 0,9401 2 -0,2850 0,7590 -0,7209 0,3814 -1,5513 0,7796 -2,3019 ** 4,0585 * -2,0298 * 0,2068 3 0,7714 0,2070 -0,5871 0,7054 0,4423 0,5504 -0,2970 -1,7728 2,6414 * 0,4862 4 0,6552 0,0249 1,0543 2,3039 ** 0,4089 -0,5167 0,1345 -1,4260 -0,9117 -0,4027 5 -0,1300 0,1197 0,4994 -0,1794 -0,7262 0,4359 -0,0973 0,9279 -1,5428 -0,1206 6 -0,3516 0,3837 -0,6256 1,5873 -1,4354 2,2128 ** -1,5738 -1,9067 -0,6327 -0,5389 7 -0,6369 0,1902 -3,0341 * -0,0233 0,2234 1,3164 -0,2107 0,2218 -0,9739 0,9858 8 0,4993 1,5648 0,1193 0,5215 1,0602 -0,4462 0,0887 -0,8347 -1,0996 -0,4073 9 -0,3622 0,5867 -0,5108 0,5574 0,2501 -0,4515 -0,0939 1,5993 -1,4650 -1,6038 10 -0,2789 0,1173 -0,4965 0,1531 0,0344 0,0905 0,5580 -0,9401 -0,6643 0,0151 11 -0,6093 -0,9741 -1,7868 -0,1667 0,3216 0,4184 0,8332 -0,3042 0,2621 0,3724 12 -1,7939 0,1502 -0,9520 0,0348 -0,7891 -0,5457 -0,1103 -1,0134 0,7090 -3,1516 * 13 0,5129 0,3253 0,5763 1,1942 0,1371 -0,7998 -0,0026 0,5408 -1,3540 0,5441 14 0,0058 0,8523 -2,0795 ** 1,2528 -0,0806 0,6268 1,2826 0,5645 -0,8781 -1,2942 15 1,7082 0,0656 0,5022 1,0928 0,6504 0,4944 1,9076 -0,2520 0,2376 0,4252 16 -1,9828 -0,7532 -1,7934 -0,7461 -0,0901 -0,7464 -0,8139 -0,9992 -0,5348 0,8550 17 0,3847 0,0889 0,2205 -0,0813 -0,6662 0,6719 1,2594 -0,5139 1,3579 -1,0710 18 1,6000 -0,6396 0,9548 0,3167 1,8849 0,9931 -0,6218 -1,0491 2,7850 * 0,0926 19 0,5080 1,2387 0,3775 -0,0444 -0,1079 0,4223 0,5080 -1,1658 0,3819 -0,7534 20 0,4877 -0,5832 1,6747 -0,0114 0,8692 1,3444 -0,5083 1,2094 -2,9381 * -0,6541 * and ** = statistically significant at a 1% and 5% level.

All Years Event

day

(46)

1999 2000 2001 2002 2003 2004 2005 2006 2007 -20 -1,1802 -0,0497 -0,5671 -0,0213 0,2062 -1,9499 -0,2508 -0,2036 0,1359 -1,391 -19 0,7183 0,2809 2,6345 * 1,4253 -0,6577 0,5311 -0,8240 -0,4581 0,8114 -1,242 -18 -0,5354 0,1263 0,6705 0,3595 0,0472 -1,2255 0,1433 -1,5606 0,3180 -0,774 -17 0,0584 -0,6598 -0,0043 0,6196 0,1900 -0,0401 -1,0576 -0,1469 -0,2365 1,533 -16 -0,7932 0,7082 -0,4235 0,4732 -0,8235 -0,6858 -0,6506 -0,3447 -0,7951 -0,177 -15 -0,5024 0,9353 -0,8054 -1,4936 0,7130 0,4567 0,2049 -0,6618 -0,5559 -0,603 -14 -0,7645 -0,2486 -0,7265 -0,5002 0,5297 0,2176 -1,1822 -0,2153 1,5602 -2,14 ** -13 0,0669 0,1559 -1,8693 -0,1464 0,8774 0,7759 0,8956 0,5338 -1,0791 0,0845 -12 -0,5268 0,0564 -0,0603 0,7390 -1,2387 0,2276 0,4543 0,1382 0,0014 -2,026 ** -11 -0,9779 -0,2379 -0,0775 0,4874 -1,7549 -0,5025 0,1834 -0,0713 -0,2800 -0,988 -10 -1,0651 -0,3561 -0,2254 -1,7010 0,0054 -1,6664 1,2338 -0,4872 -0,5640 0,1098 -9 -0,5882 1,7658 -1,0179 -0,0938 1,1187 -2,0200 ** 1,8572 0,7665 -2,4762 ** -1,936 -8 0,7901 -1,6045 -0,3216 -0,4746 0,8680 0,2634 1,1966 1,2988 1,1579 0,3688 -7 -1,2267 -0,2513 -1,5175 1,6740 0,2399 0,6757 -0,8240 -3,1430 * -0,1808 -0,971 -6 0,2883 0,1075 -0,7954 -0,6295 1,9099 0,7960 0,3726 -0,9483 -0,1943 0,2506 -5 -0,2423 0,2594 -0,0603 1,8176 -1,1362 0,2534 -0,4027 -0,0800 -0,4281 -0,978 -4 1,8901 -0,0685 -1,1572 1,3245 0,8694 1,9127 1,1994 1,6857 1,1851 -0,459 -3 0,9664 0,2943 1,2088 0,1990 -1,8088 -0,2348 1,5247 1,0617 0,4403 0,7475 -2 1,3708 0,5375 1,0394 -0,4135 0,6240 1,1940 2,1939 ** -0,9657 0,3996 0,0577 -1 0,4500 -1,3976 -1,0739 1,3316 -0,3113 1,1124 0,1935 -0,8639 1,8443 0,6982 0 4,6758 * 2,2415 ** 1,0308 1,7081 3,4033 * 1,8024 1,8328 2,1351 ** 0,6687 1,053 1 3,9100 * 3,6405 * 0,8571 2,4116 ** 1,5271 1,2942 0,2393 1,6930 1,4148 0,1295 2 -0,5343 0,8937 0,3805 -0,3709 -0,9084 1,3643 -2,3301 ** 1,1214 -1,6472 -0,251 3 0,6388 0,6867 -0,8944 0,3681 0,6887 0,7845 -0,3754 -1,1315 2,4504 ** -0,58 4 -0,2607 0,4851 0,9203 1,9739 ** 0,5661 -0,5727 -0,0272 -1,7700 -1,4148 -1,07 5 0,0666 -0,7095 0,2383 0,3155 -0,7871 0,8676 0,9028 0,6356 -0,7815 -0,296 6 -1,0419 0,0175 0,4149 1,4509 -1,1969 0,9978 -1,7354 -1,8457 -1,2300 -0,39 7 -0,1710 0,4421 -2,4837 ** 0,1549 -0,3087 0,9936 0,1605 0,1527 -0,1699 0,4448 8 -0,0712 0,9098 -0,0345 0,4476 0,3464 -0,3207 -0,2479 -0,0654 -1,1457 -0,158 9 0,3215 0,8292 -0,0330 0,8782 0,4434 1,2713 -0,4170 0,1993 0,0598 -2,143 ** 10 0,0420 0,0658 -0,3919 0,4277 0,0526 0,7731 0,9071 -0,7723 -1,1620 0,2773 11 -0,3808 -0,4663 -1,5075 0,1364 0,1321 0,0043 0,8741 -0,4276 -0,2229 0,1703 12 -1,3945 0,5093 -1,7932 0,6821 -0,7534 -1,0522 0,3654 -0,6458 0,6360 -2,766 ** 13 -0,1589 0,3360 0,5858 0,2188 -0,1725 -0,9563 -0,6434 0,8101 -1,0492 0,3646 14 0,2548 0,9353 -1,4945 1,9952 ** 0,4124 0,2963 0,9945 0,0247 -1,0832 -1,208 15 1,8866 0,8090 1,9841 ** 0,9848 0,6604 0,2319 2,1767 ** -0,5774 -0,3955 0,5941 16 -1,9759 -1,0415 -1,0509 -0,0711 0,2089 -1,4259 -0,7796 -1,6944 -0,6374 -0,317 17 0,0257 -0,2916 0,4422 -0,0526 -0,4596 1,0021 1,5921 -0,7505 0,4254 -1,754 18 1,3355 0,4972 0,7107 0,7134 1,9463 1,0780 -0,2966 -1,0210 1,3998 -0,611 19 0,7000 0,7458 1,8693 -0,8754 0,1213 0,5655 0,8412 -1,1417 0,6904 -0,466 20 0,0570 -1,2014 1,5103 -0,0085 0,2763 1,7079 -0,7050 0,4320 -0,6578 -1,021 Event day All Years

* and ** = statistically significant at a 1% and 5% level.

(47)

1999 2000 2001 2002 2003 2004 2005 2006 2007 -20 -2,5030 42,56 ** 0,3902 -0,8662 -0,0421 0,1252 -2,2583 ** -0,7047 -0,2046 0,2600 -4,2230 * -19 0,4382 47,44 0,1896 3,1395 * 1,9611 -0,4757 0,1431 -0,1033 -0,4053 0,8622 -4,0214 * -18 -1,7677 43,78 -0,4123 -0,2654 1,1598 -0,0751 -1,2577 0,2977 -2,2110 ** 0,4607 -3,0138 * -17 -0,8319 45,33 -0,8135 -0,2654 0,5589 0,5257 0,3432 -0,7047 -0,0040 -0,5430 -1,6031 -16 -1,2329 44,67 0,7915 0,5358 0,1582 -0,2754 0,1431 -0,7047 -0,6059 -0,7437 -3,0138 * -15 -0,8987 45,22 0,7915 -1,2668 -1,0436 2,3282 ** 0,5433 0,4982 -0,8066 -0,5430 -3,2153 * -14 -1,8345 43,67 -0,0110 0,3355 -0,2424 0,1252 0,1431 -0,7047 -0,4053 0,8622 -5,6336 * -13 -0,4308 46,00 -0,0110 -2,0680 ** 0,3586 1,1266 0,3432 1,3002 0,9992 -0,9445 -2,4092 ** -12 -0,5645 45,78 -0,0110 -0,0651 0,9595 -1,0765 0,7434 0,8992 0,5979 0,2600 -4,0214 * -11 -2,4361 42,67 ** -0,4123 -0,2654 0,1582 -1,6773 -0,4573 -0,5042 -0,4053 -0,7437 -3,0138 * -10 -1,4335 44,33 -0,0110 -0,2654 -1,0436 -0,6759 -1,6580 2,5031 ** -0,0040 -0,9445 -2,2077 ** -9 -0,3640 46,11 1,7946 -0,6660 1,1598 1,9277 -2,0582 ** 1,9016 -0,4053 -2,1489 ** -2,6108 ** -8 0,9061 48,22 -1,4154 -0,0651 -0,4427 1,9277 0,3432 1,3002 0,9992 1,0629 -0,9986 -7 -2,6366 42,33 ** -0,6129 -1,0665 0,9595 -0,0751 0,3432 -1,3062 -3,2142 * -0,1415 -2,8123 * -6 0,0371 46,78 -0,4123 -0,0651 -1,0436 2,7288 * 1,1437 0,8992 -1,8097 -0,3423 -0,9986 -5 0,5050 47,56 -0,0110 1,3369 2,1614 0,3254 -0,4573 0,6987 0,1966 -0,5430 -2,2077 ** -4 2,0424 50,11 ** 0,5908 -1,4671 0,3586 1,1266 1,7440 1,7011 1,4004 1,6652 -0,9986 -3 0,1039 46,89 -0,6129 0,7361 0,1582 -1,8776 -0,4573 1,9016 1,1998 0,2600 -0,9986 -2 0,9061 48,22 -0,0110 0,7361 0,3586 0,5257 0,7434 1,5006 -1,0072 0,2600 -0,3940 -1 1,2403 48,78 -0,4123 -1,0665 1,1598 0,1252 1,7440 0,0972 -1,0072 2,0666 ** 1,0167 0 4,9835 55,00 * 1,7946 0,9363 2,1614 ** 2,3282 ** 1,9441 ** 0,8992 2,8049 * 0,8622 1,2182 1 3,8472 53,11 * 3,6002 * 0,3355 1,5604 1,9277 1,1437 0,6987 1,1998 0,8622 0,2106 2 0,2376 47,11 1,3933 -0,2654 0,1582 -0,4757 0,9436 -0,9052 0,5979 -0,9445 0,2106 3 1,7750 49,67 0,1896 -0,8662 0,9595 1,3268 1,7440 0,0972 -0,2046 2,2674 ** -0,1925 4 0,0371 46,78 0,3902 1,3369 2,3617 ** 0,3254 -0,2572 -0,7047 -1,4085 -1,5467 -0,3940 5 0,5050 47,56 -0,4123 -0,6660 0,3586 -0,6759 0,5433 2,1021 ** -0,6059 -0,3423 1,2182 6 -1,4335 44,33 0,1896 0,1352 1,1598 -0,2754 -0,0570 -1,7072 -2,4117 ** -1,3460 0,0091 7 -0,1634 46,44 -0,0110 -2,4685 ** 1,1598 -0,8762 -0,0570 0,6987 -0,6059 0,4607 1,2182 8 0,9729 48,33 0,9921 -0,0651 -0,6430 1,5271 -0,0570 -0,1033 -0,2046 -0,3423 1,8228 9 1,7750 49,67 1,3933 0,5358 1,3601 0,5257 1,5439 -1,1057 0,1966 0,0592 0,8152 10 0,2376 47,11 -0,8135 -0,6660 0,7592 0,7260 0,9436 0,0972 -1,6091 -0,7437 2,0243 ** 11 0,9061 48,22 0,3902 -1,0665 0,3586 0,1252 0,5433 0,2977 -0,6059 -0,5430 3,2335 * 12 -0,6982 45,56 -0,0110 -1,6674 0,5589 -0,6759 -1,2577 0,4982 -1,0072 0,8622 0,6136 13 0,2376 47,11 0,9921 0,3355 0,3586 -0,8762 -0,4573 -1,5067 0,3973 -1,1452 2,6289 * 14 1,0398 48,44 0,7915 -0,4657 1,1598 0,7260 0,1431 0,2977 0,1966 -0,9445 1,2182 15 3,7135 52,89 * 0,5908 2,9392 0,7592 0,9263 1,1437 1,9016 -0,0040 -0,3423 3,2335 * 16 -0,4308 46,00 -1,2148 -1,0665 0,5589 -0,0751 -0,4573 -0,7047 -1,8097 -0,5430 4,0396 * 17 0,6387 47,78 -1,4154 1,1366 -0,8433 0,3254 0,7434 0,4982 -1,0072 0,8622 1,6213 18 2,8445 51,44 * 0,1896 1,1366 1,1598 2,3282 ** 0,1431 -0,3037 0,3973 1,4644 2,0243 ** 19 1,6413 49,44 1,1927 1,5372 0,1582 0,5257 -0,8575 1,0997 -1,2078 -0,1415 2,6289 ** 20 0,7724 48,00 -2,0173 ** 2,1381 ** -0,8433 0,1252 1,3438 -2,1081 ** 0,3973 0,6614 2,6289 ** * and ** = statistically significant at a 1% and 5% level.

Event day All Years % Positive

(48)

1999 2000 2001 2002 2003 2004 2005 2006 20007 0,1 11,4826 * 4,9905 * 2,2206 ** 3,9275 * 4,5111 * 1,9934 ** 4,2040 * 7,5343 * 5,5454 * 2,2677 ** -1,1 9,6052 * 3,1782 * 1,8296 3,2965 * 3,5827 * 1,8177 4,3130 * 6,2677 * 5,3727 * 1,8802

-5,5 6,1031 * 1,9971 ** 1,5407 3,0072 * 0,5001 2,2794 ** 2,1683 ** 4,5054 * 2,7619 * 0,8102 * and ** = statistically significant at a 1% and 5% level.

Table A5: T-values corresponding to table 6, calculated using the parametric t-test. Event window All years 1999 2000 2001 2002 2003 2004 2005 2006 2007 0,1 3,6466 55,99 * 1,7946 1,3369 1,9611 ** 1,7274 0,9436 1,7011 0,5979 1,6652 -0,8861 -1,1 3,8472 56,11 * 1,3933 0,7361 1,3601 2,1279 ** 2,3444 ** 2,1021 ** 0,7985 1,0629 -0,4851 -5,5 3,3793 55,89 * 1,9952 ** 0,9363 1,5604 1,7274 1,3438 1,5006 0,7985 0,8622 -0,6856 * and ** = statistically significant at a 1% and 5% level.

All Years Event window % Positive

(49)

Industry M/B split 0,1 -1,1 -5,5 0,1 -1,1 -5,5 All industries (N = 891) Average 11,1989 * 9,9983 * 6,7366 * 4,0428 * 2,9376 * 1,8421 Median 9,1277 * 8,2447 * 5,7744 * 3,9976 * 2,7699 * 2,9882 * Mining (N = 22) Average 0,7542 0,8172 1,4876 0,9552 0,9132 1,0396 Median 0,4741 0,2439 0,8593 1,1401 1,2910 1,4669 Utilities (N = 57) Average 2,8065 * 2,6652 * 1,3407 1,1567 0,3464 -0,2962 Median 1,3470 0,7658 0,8489 2,8364 ** 2,5852 ** 0,4376 Construction (N = 59) Average 2,9049 * 1,7771 2,1742 ** 4,4729 * 2,3325 ** 1,7559 Median 4,9866 * 2,8088 * 2,2592 ** 2,6722 * 1,3828 1,4772 Manufacturing (N = 241) Average 8,2416 * 7,3020 * 4,2756 * 5,1320 * 4,3336 * 2,7080 * Median 5,6567 * 5,8494 * 4,3816 * 0,8682 -0,0121 2,4638 * Wholesale Trade (N = 51) Average 5,7810 * 4,5906 * 2,6520 * 1,3065 2,2192 ** 0,9269

Median 5,7704 * 4,6515 * 2,5764 ** 1,9153 2,4137 ** 1,2223 Retail Trade (N = 39) Average 5,8423 * 5,2695 * 5,2337 * 0,6684 0,2007 1,3070 Median 6,1157 * 5,8227 * 3,7459 * 1,3476 0,6193 3,3195 * Average -0,0420 0,4345 1,4030 0,6329 0,2287 -0,9752 Median -2,1205 ** -1,4535 -0,0365 2,7058 * 2,2532 ** 0,9615 Average 1,1549 1,4881 0,4278 -0,5301 -0,4918 -2,5283 ** Median 0,6410 1,2043 0,0090 0,1519 0,0292 -1,7512 Average 0,3231 0,5127 0,2209 1,3437 0,8970 1,4083 Median 0,8912 1,1462 0,3599 0,7370 0,2965 1,1655 Average -1,6907 -1,4605 -0,9081 3,2526 * 2,2863 ** -0,2151 Median -1,6907 -1,4605 -0,9081 3,2526 * 2,2863 ** -0,2151 Average 4,3796 * 3,7648 * 1,7403 -2,6362 * -1,9424 -1,0558 Median 3,7524 * 2,6640 * 1,3775 -0,8340 0,0440 -0,2376 Average 0,9691 -0,2530 0,4989 1,9267 1,5878 0,6726 Median 2,0810 1,2260 1,7169 0,7617 -0,0306 -0,4731 Average 4,6041 * 4,5736 * 4,2480 * 1,1767 0,0334 1,0524 Median 4,1705 * 4,2794 * 4,0669 * 2,5107 ** 1,5701 2,1595 ** * and ** = statistically significant at a 1% and 5% level.

Accommodation and Foodservices (N = 38) Finance and Insurance (N = 163)

Administrative and Support Services (N = 22)

Professional, Scientific and Technical Services (N = 55)

Event window

Transportation and Warehousing (N = 33)

Table A7: T-values corresponding to table 7, calculated using the parametric t-test.

M/B split stands for the separation point of the market-to-book ratio in low and high categories.

Low market-to-book High market-to-book

Information Services (N = 94)

The market-to-book ratio and announcement returns during M&A activity