Download Determinants of abnormal returns in mergers

Determinants of abnormal returns in mergers
and acquisitions:
macroeconomic factors
Name
Robin Ketelaars
ANR
Date
Supervisor
S679805
22-11-2012
V.P. Ioannidou
Tilburg university
Master Thesis Finance
Faculty of Economics & Business Administration
Department of Finance
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Abstract
This research aims to determine whether or not macroeconomic factors have an influence on the
abnormal equity returns that accompany mergers and acquisitions. This will be tested using an event
study and an ordinary least squares regression, executed on a sample of 1734 mergers and
acquisitions between January 2001 and August 2011. It is shown that the data used in this research is
partially in line with prior research. Five macroeconomic factors will be investigated. These factors
are consumer price index, producer price index, a monetary aggregate, the interest rate and the
investment level in the economy. This research shows that some of these factors have a statistically
significant influence on the level of abnormal equity returns. The results show that a favorable state
of the economy contributes to higher abnormal returns. The effect of the macroeconomic factors is
different for acquiring companies than for target companies. This shows that a certain state of the
economy does not equally benefits or harms acquiring and target companies.
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Table of Contents
Abstract ................................................................................................................................................... 2
1. Introduction ......................................................................................................................................... 4
2. Theoretical framework ........................................................................................................................ 6
2.1 General introduction to mergers and acquisitions ....................................................................... 6
2.1.1 Mergers and acquisitions ....................................................................................................... 6
2.1.2 Abnormal returns ................................................................................................................... 7
2.2 Evidence on mergers and acquisitions .......................................................................................... 7
2.2.1 Long run performance ............................................................................................................ 7
2.2.2 Motives for mergers and acquisitions .................................................................................... 9
2.2.3 Evidence on abnormal returns ............................................................................................. 10
2.3 Investor Sentiment ...................................................................................................................... 11
2.4 Macroeconomic factors............................................................................................................... 13
3. Research question and methodology................................................................................................ 16
3.1 Hypotheses formulation .............................................................................................................. 16
3.2 Research plan .............................................................................................................................. 18
3.3 Data resources............................................................................................................................. 19
4. Results and hypotheses review ......................................................................................................... 21
4.1 Sample Statistics .......................................................................................................................... 21
4.2 Empirical analysis and results ...................................................................................................... 26
4.2.1 Abnormal returns ................................................................................................................. 26
4.2.2 Wealth effect ........................................................................................................................ 29
4.2.3 Macroeconomic factors........................................................................................................ 31
4.3 Hypotheses review ...................................................................................................................... 33
5. Concluding remarks ........................................................................................................................... 35
Bibliography........................................................................................................................................... 37
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1. Introduction
Acquisitions and mergers have become an important method for businesses to expand. In 2001, 8309
mergers and acquisitions were announced by U.S companies, with a value exceeding $700 billion.
However, these amounts were even lower than the preceding years. In 2000, 1999 and 1998 the
total value of merger and acquisition deals were $1.28 trillion, $1.4 trillion and $1.2 trillion
respectively.
The topic of mergers has been broadly covered in the existing literature. Nelson (1959) for example
states that the merging of enterprises exists as long as humans have started to form enterprises.
However, the type of mergers and acquisitions that can cover entire industries as we know them
today did not occur until the 1890’s. Nelson (1959) identifies three major merger waves in the United
States. He states that the first large merger wave took place from 1898 to 1902, the second wave
from 1926 to 1930 and the third wave from 1946 to 1956. Lamoreaux (1985) states that the merger
wave of the late 19th century took place between 1895 and 1904. She states that the consolidation of
Standard Oil Trust in 1882 was the first consolidation ever documented. Furthermore, in accordance
with Nelson (1959), Lamoreaux (1985) argues that the passage of the general incorporation law in
New Jersey in 1888 served as a boost to the first large merger wave of the late 19th century. More
recently, Holmstrom and Kaplan (2001), among others, discuss the merger waves of the 1980’s and
the 1990’s. Martynova and Renneboog (2008) also discuss the historical U.S. merger waves and state
that there is a clear pattern: the beginning of all five documented merger waves in history coincided
with economic prosperity and economic recovery, whereas the end of every merger wave coincided
with a stock market crash. This may indicate that macroeconomic factors, which determine the state
of the economy, have an influence on the presence or absence of merger waves.
In the last few decades, focus of academic research has shifted more towards the behavioral finance
and the psychology of economics. It has become more and more apparent that the classical
economic theories are inadequate in explaining certain outcomes. For example, as opposed by the
classical theories, investors and managers are only rarely fully rational in decision making. This
bounded rationality has an effect on economic decisions and their outcomes.
This paper researches the abnormal returns of equity shares that come with mergers and
acquisitions. It may be possible that investors who are not fully rational overreact to changes in
macroeconomic factors or are guided in their investment decisions by general under- or
overconfidence. As stated above, merger waves coincided with periods of economic prosperity. As
will be argued below, this suggests that managers can time their corporate decisions on mergers and
acquisitions to execute these decisions in periods when the economy is in a favorable state. It can be
expected that managers time these decisions to accomplish the maximum gain for their
shareholders. Investors are willing to pay more for equity shares when the economy is strong.
Therefore it is to be expected that factors that portray a strong economy such as low inflation, a low
interest rate and a high level of investment in the economy have a positive effect on the abnormal
returns. The goal of this paper is to determine if macroeconomic factors have any influence on
abnormal returns and if so to determine the level and significance of this effect. By answering this
question, this paper can provide evidence on whether or not the timing of mergers and acquisitions
in times of economic prosperity is justified. Moreover, by determining the extent of the possible
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impact of macroeconomic factors on abnormal returns, this research can support investors and
managers in their expectation of the extent of the abnormal returns. To accomplish this, a sample of
mergers and acquisitions and the accompanying abnormal returns will be investigated. Some control
variables will be added to make it possible to check the outcomes of this research with prior
academic work.
This paper is organized as follows: Chapter two will review prior academic work on different topics
that are of importance for this research. Chapter three will contain the methodology, the sample of
mergers and acquisitions and the data. Chapter four will describe the analyses and will contain a
review of the results. Finally, chapter five will contain some concluding remarks.
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2. Theoretical framework
2.1 General introduction to mergers and acquisitions
2.1.1 Mergers and acquisitions
Since the first merger wave in the late 19th century, mergers and acquisitions have evolved in one of
the most important, if not the most important method for businesses to expand rapidly. There are
only slight differences between the two terms. According to the Farlex Financial Dictionary, a merger
is defined as follows:
“A decision by two companies to combine all operations, officers, structure, and other
functions of business. Mergers are meant to be mutually beneficial for the parties
involved. “
Through a merger, two (or more) companies mutually decide to form a new corporation. Both
companies will cease to exist and new shares of stock of the newly formed company will be issued.
Shareholders of the two old companies will be offered to substitute their shares of the old company
for share of the new corporation. A horizontal merger is a merger where two companies in the same
industry engage in a merger. Mostly this type of merger is to realize more efficiencies of scale or to
realize greater market share. Vertical mergers are mergers where two companies in the same supply
chain engage in a merger. A well-known merger for example is the 1999 merger of Glaxo Wellcome
and SmithKline Beecham, who together formed GlaxoSmithKline. More well-known mergers are the
2002 merger of Hewlett-Packard with Compaq Computers and the 2000 merger of America Online
with Time Warner.
The Farlex Financial Dictionary defines an acquisition as:
“An investment in which a company or person buys a publicly-traded company, or,
more commonly, most of the shares in that company. For example, if Corporation A
buys 51% or more of Corporation B, then Corporation B becomes a subsidiary of
Corporation A, and the activity is called an acquisition. Acquisitions occur in exchange
for cash, stock, or both. Acquisitions may be friendly or hostile; a friendly acquisition
occurs when the board of directors supports the acquisition and a hostile acquisition
occurs when it does not.”
In an acquisition, the target company does not have to support the acquisition of shares of stock by
the bidding company. If the bidding company acquires 100 percent of the shares of the target
company, the target company becomes a subsidiary of the bidding company and since the bidding
company holds all the shares of the target company, the shares of the target company will cease to
trade.
The most significant difference between mergers and acquisitions is thus that in a merger, both
companies involved will cease to exist and a new company is formed, whereas in an acquisition, both
companies continue to exist. Moreover, in a merger both companies will have to agree to engage in a
merger, whereas in an acquisition, the target company may not approve the acquisition but can be
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unable to prevent it. However, in this paper these differences are not significant. This paper focuses
on the abnormal returns on equity shares involved in mergers and acquisitions.
2.1.2 Abnormal returns
Abnormal returns are defined as the excess returns of a stock compared to the expected rate of
return. Abnormal returns normally occur due to announcements from or about the corporation.
Financial restatement announcements, mergers and acquisitions, stock split announcements etc.
Fama et al. (1969) first looked at these abnormal returns. They investigated the rate of returns in the
months surrounding stock splits. Fama et al. (1969) stated that the residual returns on stocks of
companies that announced a stock split were abnormally high surrounding the announcement date.
To compute these results they introduced the “event study” research method. This method considers
the relationship of a stock with the market to compute an expected rate of return. If the realized
return deviates from this expected return, one can speak of abnormal returns, which can be both
positive or negative. In this paper, an event study will also be used to compute abnormal returns.
More details on the event study research method will be discussed in section 3.
2.2 Evidence on mergers and acquisitions
2.2.1 Long run performance
A company engages into a merger or acquisition in the hopes of benefitting from several factors.
These factors can be but financial or strategic. More details about the motives of why companies
engage in mergers or acquisitions will be discussed below.
2.2.1.1 Increase in Long run performance
Even though decreases in long term performance following mergers and acquisitions is broadly found
in the existing literature, increases in long term performance have also been well documented. For
instance, Healy et al. (1992) investigated the 5 year post-merger performance of mergers in the US
industry between 1979 and 1984 and found that the asset productivity, operating cash flow returns
and the asset turnover increased. Linn and Switzer (2001) also investigated mergers in the US
industry and found an increase in cash flow divided by market value over a 5 year post-merger
performance for mergers between 1967 and 1987. Ghosh (2001) found an increase in cash flow
returns to assets over a 3 year post-merger period for mergers between 1981 and 1995 in the US.
Cosh et al. (1980) found an increase in growth of net assets and an increase in leverage ratio over a 5
year post-merger period for mergers between 1967 and 1969 in the UK, and Powell and Stark (2005)
investigated mergers between 1985 and 1993 in that same industry and found an increase in cash
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flow to total market value, an increase in cash flow to book value and an increase in cash flow to
sales over a 3 year post-merger period. Kumps and Wtterwulghe (1980) investigated Belgian mergers
between 1962 and 1974 over a 5 year post-merger period and found increases in net income to
equity, net income to total assets and an increase in total assets growth rate.
2.2.1.2 Decrease in Long run performance
Even though companies expect to benefit from a merger of acquisition in the future, a merger or
acquisition may turn out to be less beneficial then expected beforehand. Many economists have
researched the different merger waves in history and the results show that the expected increase in
performance is not always realized. Martynova and Renneboog (2008) summarize some of the
literature on post-merger performance.
There have been several academics who investigated the long run performance during the 1960’s
merger wave. Mueller (1980) investigated mergers and acquisitions and the 3 to 5 year post-merger
performance of companies in the US from 1962 until 1972 and found a decrease in, amongst others,
return on equity, return on assets, return on sales and a decreased sales growth rate. Mueller (1985)
also investigated annual averages from 1950 until 1972 for companies that engaged in a merger and
found a drop in market share. Jenny and Weber (1978) researched mergers and acquisitions and the
4 year post-merger performance in France over the same period as Mueller (1980) and found
decreases in profit per equity, profit per asset, profit per sale and a decreased sales growth rate. Peer
(1980) researched mergers and acquisitions in The Netherlands from 1962 until 1973 and found
amongst others decreases in return on sales, return on equity and a lower total assets growth rate.
Ryden and Edberg (1980) researched the 1962-1976 merger and acquisition period in Sweden and
also found decreases in return on equity, return on assets and return on sales in a 3 year post-merger
period. Ikeda and Doi (1983) investigated the 3 year post-merger performance of mergers and
acquisitions between 1964 and 1975 and also found a decrease in return on equity, whereas,
amongst others, return on assets and sales growth remained at the same level as before the merger.
Moreover, Meeks (1977) researched long run performance of mergers and acquisitions in the UK
over a 3 year and 5 year post-merger period and found a decrease in EBIT divided by net assets.
The long run performance for mergers and acquisitions in the merger wave of the 1980’s and the
1990’s has also been researched extensively. Clark and Ofek (1994) for instance researched the 2
year post-merger performance of mergers in the US and found a decrease in earnings before
interest, taxes and depreciation (EBITD) divided by revenues. Odagiri and Hase (1989) investigated
Japanese mergers between 1980 and 1987 and their 3 year post-merger performance and found a
decrease in gross profit divided by assets and a lower sales growth for horizontal mergers and
acquisitions. Carline et al. (2002) researched mergers in the UK and found a decrease in earnings
before interest, taxes, depreciation and amortization (EBITDA) divided by the market value over a 5
year post-merger period for mergers between 1985 and 1994. Gugler et al. (2002) conducted a
worldwide investigation on mergers between 1981 and 1998. They found a decrease in sales divided
by assets for all deals investigated worldwide over a 5 year post-merger period and a decrease in
profit divided by assets for merger deals in Japan.
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As shown above, there has been a lot of scientific research on the long term performance of mergers
and acquisitions. Even though companies engage in a merger or acquisition with the expectation to
realize better performance in the future, it has been well documented that a better performance is
often not the case. However, the academic work that focused on long term performance which is
summarized above, did not focus on the factors that determine whether long run performance
increased or decreased. Moreover, Martynova and Renneboog (2008) state that the results of the
prior literature, combined with the result that the share price of the acquiring firm drops
substantially in the 5 years following the acquisition, suggest that the gains companies hope to
realize through a merger or acquisition are overstated.
2.2.2 Motives for mergers and acquisitions
There are many reasons why companies decide to engage in a merger or acquisition. One of these
reasons may for example be that the two companies combined can realize more efficient production,
or benefit from each other’s know-how. Yagil (1996) states that, based on prior literature, there are
two main types of motives for managers to engage in a merger or acquisition: Financial motives and
operating motives. Under operating motives, Yagil (1996) names improving market control and
operating efficiencies, enhancing growth and to pool the resources of the two companies together to
increase technological expertise. He states diversification, reducing the risk of bankruptcy and the
accompanying costs and tax benefits are financial motives for mergers and acquisitions. Gugler,
Mueller and Yurtoglu (2006) state that there are two main reasons for mergers and acquisitions: (1)
following the neoclassical theories, mergers and acquisitions are initiated to maximize profits and
shareholder wealth and (2) following the non-neoclassical theories, mergers and acquisitions are
initiated for other reasons than to maximize shareholder value.
Bruner (2001) states that the motives why companies engage into mergers or acquisitions that the
motives for these decisions may be of strategic benefit and do not create wealth for the
shareholders. He even states that some mergers and acquisitions take place for the sole reason that
the two companies or the CEOs of the two companies are very friendly. These motives are no
guarantee that the mergers or acquisitions will be beneficial. Capron and Pistre (2002) also name
some motives such as industry overcapacity, financial diversification and preemption. These motives
do not enhance shareholder value per se. Martynova and Renneboog (2008) argue that herding
behavior is also a reason for managers to engage in mergers and acquisitions. They state that if a
company accomplishes a successful merger or acquisitions, other companies are likely to follow in
the same actions. These following mergers and acquisitions are not so much based on a clear
economic perspective, but they are engaged to copy the actions of the first company to successfully
engage in a merger or acquisitions. Amihud and Lev (1981) state that diversification is based on the
incentive of the manager for risk reduction. However, in perfect capital markets risk reduction is not
beneficial for the shareholders of the company, since they can diversify their own portfolio of equity
shares to minimize the risk they bear. Even so, Amihud and Lev (1981) found evidence that managercontrolled firms engage more in diversifying mergers and acquisitions than owner-controlled firms.
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2.2.3 Evidence on abnormal returns
Extensive research has been conducted on the effects of mergers and acquisitions, both for the
acquiring firm and the target firm, as well as for its shareholders and bondholders. Abnormal returns
are defined as the excess return of a stock compared to the expected return. Researchers have
aimed to provide evidence on which factors influence abnormal returns and which do not. Billett,
King and Mauer (2004) for example state that significant positive announcement period returns are
earned by target bonds that are below investment grade. Capron and Pistre (2002) investigate the
post-acquisition transfer of internal resources between acquiring and target company. These internal
resources are divided in three categories: innovation resources, marketing resources and managerial
resources. They find that the acquiring company cannot earn abnormal returns when the company
merely transfers internal resources from the target company to their own company. They state that
the abnormal returns that would have been earned by only transferring resources from the target
company to the acquiring company would have been competed away by other bidding companies,
since those companies would have been equally capable of capturing those resources. Instead they
state that the acquiring company should transfer its own managerial and innovative resources into
the target company and utilize the target’s own marketing resources. Fuller, Netter and Stegemoller
(2002) investigated acquisitions and concluded that shareholders of the acquiring firm gain when the
acquiring firm bought a private firm or subsidiary of a public firm and they lose when the acquiring
firm bought a public firm. Furthermore, they stated that the absolute value of the gain or loss would
be greater if the size of the target was larger and when the acquiring firm used stock to finance the
acquisition.
Mulherin and Boone (2000) also differentiated between abnormal returns to the shareholders of the
acquiring company and abnormal returns to the shareholders of the target company. They found
that the shareholders of the target company experienced an abnormal return of 20.2%, while the
shareholders of the acquiring company faced an abnormal return of -0.37%. Although the abnormal
returns to the shareholders of the acquiring companies were not significant, the abnormal returns to
the shareholders of the target companies were significant. Andrade, Mitchell and Stafford (2001)
found an averaged 16% abnormal return for target firms during a three-day event window compared
to a -0.7% abnormal return for acquiring firms during that same event window.
Bruner (2001) presents an overview of prior research concerning abnormal returns. All the research
summed up came to the following conclusion: the cumulative abnormal returns for the shareholders
of the target firm are on average significantly positive. Bradley, Desai and Kim (1988) for instance
found cumulative abnormal returns of 31.77% between 1963 and 1984. Servaes (1991) researched
mergers between 1972 and 1987 and found cumulative abnormal returns of 23.64%. Schwert (1996)
investigated roughly the same period, from 1975 until 1991 and found abnormal returns for the
shareholders of the target company of 26.3%. DeLong (2001) investigated deals between 1988 and
1995 where at least one of the involved parties was a bank and found abnormal returns of 16.61%.
Bruner (2001) sums up even more prior literature and all research summed up concludes that
cumulative abnormal returns to the shareholders of the target company are significantly positive.
However, the results on the abnormal returns to the shareholders of the acquiring companies are not
as unanimous as the results on the target companies. For instance, Asquith, Bruner and Mullins
(1987) find cumulative abnormal returns for the shareholders of the acquiring companies of -0.85%
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between 1973 and 1983. Jennings and Mazzeo (1991) find abnormal returns of -0.8% for deals
between 1979 and 1985. Walker (2000) researched deals between 1980 and 1996 and found
abnormal returns of -0.84%. Houston et al. (2001) investigated deals where both parties were banks
and found abnormal returns of -4.64% for deals between 1985 and 1990 and abnormal returns of
-2.61% for deals between 1991 and 1996. On the other hand however, there is also academic work
that reports positive cumulative abnormal returns to the shareholders of the acquiring company. For
instance, Kummer and Hoffmeister (1978) found positive cumulative abnormal returns of 5.20% for
deals between 1956 and 1970. Jarrel, Brickley and Netter (1987) researched deals between 1962 and
1985 and reported abnormal returns of 1.14%. Loderer and Martin (1990) found abnormal returns of
1.72% between 1966 and 1968 and abnormal returns of 0.57% between 1968 and 1980. This shows
that there is consensus in the literature about the abnormal returns to shareholders of the target
company, but that the results on abnormal returns to the shareholders of the acquiring company are
much less unanimous. On the other hand, all academic work summarized by Bruner (2001) report a
positive wealth effect. This means that the combined returns to shareholders of the bidding firm and
the target firm are positive.
2.3 Investor Sentiment
Behavioral finance has been a rising topic in the academic literature over the last decades. In the
classic financial theories, shareholders are expected to be fully rational. However, economists have
become more and more aware that this is not the case. Baker and Wurgler (2006) investigate the
effect of investor sentiment on cross-sectional stock returns and offer a possible definition of
investor sentiment: investor sentiment is the tendency to speculate. They state that under this
definition, the relative demand for speculative investments is driven by investor sentiment. Another
explanation may be the optimism or pessimism about stocks in general. Daniel, Hirshleifer and
Subrahmanyam (1998) have developed a theory based on overconfidence of investors and biased
self-attribution that leads to changes in confidence. They state that this theory implies that private
information causes investors to overreact and that public information causes investors to underreact.
Barberis, Schleifer and Vishny (1998) have created a model for investor sentiment. The model shows
how investors form beliefs about future earnings and is based on psychological evidence. They
classify different types of news by two categories: the strength and the statistical weight of the news.
In their paper, they argue that investors pay too much attention to the strength of the news, and too
little attention to its statistical weight. However, they could only classify the news in hindsight. The
model is not suited to classify the strength and the statistical weight a priori.
Helwege and Liang (2004) investigate market cycles of initial public offerings (IPOs) between 1975
and 2000. They looked at characteristics and possible differences in these characteristics of hot and
cold IPO markets. Helwege and Liang (2004) define a hot IPO market as experiencing severe
underpicing, frequent oversubscription of offerings, an unusually high number of IPOs and at times
concentrations in particular industries. Cold IPO markets on the other hand are defined as having less
underpricing, lower amount of oversubscription of offerings and much lower volume of IPOs. The
results show that the characteristics of firms that go public in a hot market do not differ so much
from firms that go public in cold markets. Moreover, the results show that there are only slight
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differences in profits, age of the firm or growth potential. Finally, Helwege and Liang (2004) state
that hot markets are not caused by changes in for example managerial opportunism or technological
innovations, but rather that hot IPO markets are the results of greater investor optimism. Ljungqvist,
Nanda and Singh (2006) also investigate investor sentiment in initial public offerings. They created a
model which shows that return anomalies such as underprcing, hot IPO markets and long-run
underperformance can be traced to a common source, namely irrational investors. They also show
that issuers can take advantage of the presence of irrational investors. This implies that managers
can time the moment of issuance to maximize the gains of the offering.
Baker and Wurgler (2006) investigate how investor sentiment influences the cross-sectional returns
on stocks. They predict that investor sentiment plays a greater role in securities of companies that
are more difficult to valuate. For their research, they created a proxy of investor sentiment based on
six factors: the closed-end fund discount, the share turnover on the New York Stock Exchange, the
dividend premium, the equity share in new issues, the number of IPOs and the average first-day
returns on IPOs. It is interesting to notice that the number of IPOs is considered a determinant of the
level of investor sentiment. As stated above, Ljungqvist, Nanda and Singh (2006) stated that
managers can benefit from the presence of investor sentiment when their company engages in an
IPO. Therefore it was argued that managers can time the moment of issuance so to benefit the most
from the offering. The fact that Baker and Wurgler (2006) include the number of IPOs as a
determinant for the investor sentiment proxy supports this statement. Based on the results, Baker
and Wurgler (2006) state that future cross-sectional stock returns depend on the begin-of-period
proxy for investor sentiment. The results show that stocks which are interesting for speculators earn
relatively low returns when it is estimated that investor sentiment is high. Thus they have shown that
investor sentiment does play a role in the cross-sectional returns on certain stocks. Tetlock (2007)
investigates the effect of media on the stock market. Using news from a Wall Street Journal column,
he finds that market prices are likely to decline when pessimism in the media is high. Moreover, he
argues that extremely high or low pessimism predicts a high trading volume. Ozoguz (2008)
investigates the effect of the beliefs and uncertainty of investors. She uses a model which uses the
state of the economy to describe investors’ beliefs and uncertainties and market returns. The results
show that investors’ beliefs and uncertainties are very successful when it comes to explaining large
cross-sectional variations in portfolio returns. She also finds a negative relationship between
investors’ uncertainty and the valuation of assets, and that the level of uncertainty varies strongly
depending on the state of the economy. Moreover, the results show that investors’ beliefs also have
an impact on the valuation of assets. When investors’ perceive that they are economically in a bad
time, these beliefs have a negative impact on the prices of assets.
Schleifer and Vishny (2003) investigated the role of stock mispricing in the takeover market. They
produce a model to investigate stock market driven acquisitions. One of their conclusions is that
managers can benefit from an overvaluation of the equity shares of the company. Managers have an
incentive to achieve an overvalued stock, and once the equity shares of the company are overvalued,
managers can use these shares as a currency to pay for acquisitions and mergers of relatively less
overvalued targets. Say for example that company A and B both have a stock which is worth $25 and
the stock of company A sells for $50 and the stock of company B sells for $40. Company A can then
use its stock to pay for company B. if both stocks were priced correctly, company A has to pay one
share per share of company B. however, since both companies are overpriced, and company A is
overpriced more than company B, but companies will have an incentive to participate in the deal. On
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the other hand, the long run performance of overvalued bidding companies is lower than the
performance of bidding companies that are more accurately valuated. Schleifer and Vischny (2003)
speak of the performance extrapolation hypothesis. This states that the future earnings of
overvalued bidding companies are extrapolated wrongly by the market, which leads to a false view
on the combined value of the firms post-merger. This is more or less the same as what happened in
the merger between AOL and Time Warner in 2001. Steve Case, CEO of AOL, used the equity shares
of AOL, which were highly overvalued, to pay for the merger with Time Warner. The total amount
paid by AOL was $164 billion. When the dot-com bubble burst, the value of the combined firm AOL
Time Warner dropped from $226 billion to around $20 billion. This shows how investor sentiment
and overvaluation can drive the stock price of a company. Dong et al. (2006) examined the
misvaluation hypothesis, which states that the takeover market is driven by misvaluations. Some
results immediately stand out: Bidding companies are relatively higher valued than the target
companies. Also, the higher the bidding company is valued by the market, the more likely it is that
the company will prefer to use stock as the method of payment, and the less likely the company is to
use cash as a currency. Moreover, the higher the bidding company is valued, the more it is willing to
pay for the target company. Intuitively this makes sense. When the stock of the bidding company is
highly overvalued, the manager can use stock as a currency, but this currency does not have real
value since it is likely to drop again when the overvaluation becomes apparent. Dong et al. (2006)
conclude with the statement that, according to their findings, the takeover market is indeed driven
by misvaluations. Rosen (2003) investigated the investor sentiment involved in stock market
reactions and focused the effects of mergers on the stock prices of the bidding firms. His research
was based on three theories. First, the neoclassical theory states that the only goal of managers is
the enhance shareholder value. Merger momentum could in this case arise from the fact that shocks
in the market produce opportunities for bidding firms to increase the value and performance of the
firm through a merger or acquisition. A second theory assumes that managers can engage in mergers
without the aim of enhancing shareholder value, but that mergers are initiated based on operating
motives. This could include motives as diversification and empire building. Lastly, he mentions the
possibility that reactions on merger announcements are not based on fundamentals but rather on
overly optimistic beliefs from managers or shareholders. He found evidence of a momentum factor
in the merger markets: If prior merger announcements received a favorable reaction, later merger
announcements tend to continue to do so. On the other hand, he also found evidence that the
favorable short-term reaction is revised in the long run. Mergers that received a too favorable
reaction surrounding the announcement, showed a decline in the stock price of the bidding company
in the long run. This shows that the merger was overvalued at the time of the announcement, and
that the overvaluation was corrected in the long run when the mispricing became apparent. This
shows that investor sentiment is an important factor in the reaction that the equity shares of the
bidding company receive by the market surrounding the merger announcement.
2.4 Macroeconomic factors
As described above, academic research has been focusing more and more on the psychological
aspects of finance than before. However, the determinants of investor sentiment have not had much
attention. Baker and Wurgler (2006) created a measure based on six proxies for investor sentiment,
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but they also state that these proxies are not definitive or uncontroversial. The rest of the academic
work described above acknowledges the impact of investor sentiment, but does not aim to
determine the causes of it. The approximation on investor sentiment is only reviewing or rather
theoretical. That is, the results do not provide clear quantitative results as to what extent investor
sentiment influences stock trading.
Kwon and Song (2011) conducted research on the Korean merger market. One of the two most
important conclusions of their work is that the global financial crisis has a significant negative impact
on the cumulative abnormal returns of the bidding company when the merger is announced. As
explanation they state that it may be possible that investors do not appreciate the large outflows of
cash during a period of crisis. Martynova and Renneboog (2008) reviewed the history of merger
waves and identified 5 major merger waves. The events coinciding with the beginning and ending of
all merger waves show some striking resemblance. According to Martynova and Renneboog (2008),
the first merger wave took place from the late 19th century until 1903. The beginning of the merger
wave coincided with economic expansion due to industrialization and the development of trading on
the New York Stock Exchange, whereas the end of the merger wave coincided with a stock market
crash and the beginning of the First World War. The second merger wave took place from the late
1910s until 1929. The start of the merger wave coincided with economic recovery of the stock
market crash and the First World War, and the ending of the merger wave coincided with a stock
market crash and the beginning of the Great Depression. The third merger wave started in the 1950s,
coinciding with economic recovery after the Second World War and ended in 1973, coinciding with
the stock market crash due to the oil crisis. The fourth merger started in 1981, during economic
recovery from the oil crisis and ended in 1989 when another stock market crash took place. Finally,
the fifth merger wave took place from 1993 until 2001. The beginning of the last wave coincided with
economic boom and the globalization process and ended with the stock market crash in 2001. The
pattern in merger waves is apparent: the beginning of all five documented merger waves in history
coincided with economic prosperity and economic recovery, whereas the end of every merger wave
coincided with a stock market crash. This shows that it is very likely that (macro) economic factors
influence whether or not the economy is experiencing a merger wave, and thus influence the
decisions of managers whether or not to engage into a merger or acquisition. Unfortunately,
presented in Martynova and Renneboog (2008) is only an overview of these merger waves, not an indepth investigation to test if so what economic factors determine the presence of merger waves.
Figlewski, Frydman and Liang (2012) researched the effect of macroeconomic factors on default risk
and corporate credit ratings and their transitions. They used several economic factors in their model,
such as unemployment rate, inflation, real GDP growth, 3-month T-Bill rate and S&P 500 return and
volatility. They state that adding economic factors in their model strongly increased the explanatory
power of the model. Furthermore they point out that the unemployment rate and inflation are
strongly related to the intensity of a credit rating upgrade. A high unemployment rate and high
inflation are associated with a reduction in the intensity of a credit rating upgrade. Even though
corporate credit ratings and their transitions are not directly linked to abnormal returns in mergers
and acquisitions, academic work such as that of Figlewski, Frdyman and Liang (2012) does indicate
that macroeconomic factors can have a direct influence on companies.
Flannery and Protopapadakis (2002) investigated the effect of announcements of 17 macroeconomic
factors. They state that macroeconomic factors are risk factors for companies, since these factors
14
may influence the cash flows of many companies and simultaneously affect the discount rate of
these companies. They cite Chen, Roll and Ross (1986) by saying that economic variables may act as
exogenous risk factors that causes comovement in the cross-sectional returns on equity shares.
Flannery and Protopapadakis (2002) state that two macroeconomic factors, inflation and money
supply, are well documented factors that have a significant effect on equity returns. In their research,
Flannery and protopapadakis (2002) searched for macroeconomic factors that either had an effect on
equity returns or increased the volatility of the stock market. Of the 17 factors investigated, six
turned out to have an impact on the level of equity returns or on the market’s volatility. Balance of
trade, Unemployment and the amount of housing units in the beginning of the period only had an
effect on the volatility of the equity returns. The effect these factors have on the volatility of equity
returns is positive for all factors. The consumer price index and producer price index only affected
the level of equity returns, and the money supply affected both the level of equity returns as well as
the volatility of the equity returns. They found that the relationship between CPI, PPI and money
supply with equity returns is negative for all three factors. Furthermore they found that the effect of
the money supply on the volatility of the equity returns is positive. Moreover, Flannery and
Protopapadakis (2002) state that two measures that are regarded as popular measures of economic
activity, real GNP and industrial production, do not seem to have the same effect on the level and the
volatility of equity returns. They state that announcements about real GNP lead to a lower volatility
of the equity returns, and that industrial production shows a similar effect, although the effect of
industrial production is weaker.
Yagil (1996) also came to the same conclusion as argued above following the work of Martynova and
Renneboog (2008) that the fact that merger waves tend to start during periods of economic recovery
and that the end of a merger wave coincides with a stock market crash points in the direction that
merger waves are influenced by macroeconomic factors. He investigates mergers between 1954 and
1979 that were paid either with cash or securities. He found that the investment level and the
interest rate in the economy are related to merger activity. The two macroeconomic factors have a
positive effect on merger activity and the impact of the interest rate on mergers that were paid with
securities is negative. Furthermore, he found that the significance level of the interest rate is higher
than the significance level of the investment level.
Reviewing the prior academic work in the different topics above, some results stand out. Ljungqvist,
Nanda and Singh (2006) stated that managers can gain from timing the moment of IPOs when there
are irrational investors present. Moreover, Baker and Wurgler (2006) created an estimate of investor
sentiment in which one of the used proxies was the number of IPOs. As argued above, this is an
indication that investor sentiment and the number of IPOs are not unrelated and that managers may
consider this in making and timing their corporate decisions. Furthermore it has been argued in prior
literature that macroeconomic factors are related to the appearance of merger waves. If managers
do time their corporate decisions, one could state that investor sentiment is related to
macroeconomic factors, which can also be intuitively argued by stating that one would be willing to
pay more for equity shares if the economic conditions such as unemployment rate and interest rate
are favorable. This research aims to determine statistically if there is a relation between
macroeconomic factors and abnormal returns involved in mergers and acquisitions and if so to
determine what the impact of these relationships are. Rational investors are expected to be
influenced more (less) by these macroeconomic factors then irrational investors in the beginning
(ending) of a merger wave due to underconfidence (overconfidence) of these irrational investors. As
15
stated above investors are willing to pay more for equity shares when the economy is in a favorable
state. Therefore it is to be expected that factors that portray a strong economy such as low inflation,
a low interest rate and a high level of investment in the economy have a positive effect on the
abnormal returns. The relationship for rational investors between inflation and interest rate with
abnormal returns can thus be expected to be negative, whereas the relationship between
investment in the economy and abnormal returns is expected to be positive. However, this research
aims to determine if there is a statistical relationship between macroeconomic factors and abnormal
returns, and if so to determine the extent of these relationships. This research does not aim to
provide an answer to the question whether or not these relationships are different for rational
investors on one hand and irrational investors on the other hand. The academic areas of both
abnormal returns involved in mergers and acquisitions as well as the effect of macroeconomic
factors on the intensity of mergers and acquisitions has been well documented. However, research
on a relationship between these two areas is thin. This research may support corporate executives in
their understanding of the circumstances in which it is most favorable for the corporations and its
shareholders to initiate corporate decisions. Furthermore, it can help investors in understanding the
circumstances that determine the abnormal returns in mergers and acquisitions, which can aid them
to profit from this.
3. Research question and methodology
3.1 Hypotheses formulation
The aim of this paper will be to determine if macroeconomic factors have an effect on abnormal
returns that accompany mergers and acquisitions. Moreover, it aims at determining if and how
strong the impact of several macroeconomic factors is on the height of these abnormal returns. The
main research question will therefore be as follows:
What is the effect of macroeconomic factors on the level of abnormal returns that accompany
acquisitions?
To be able to answer this research question adequately, several hypotheses will be formulated. First
step in answering the research question is to determine if the data is in line with prior research. It
may be possible that the findings in this research do not correspond with prior findings, since the
sample period used in this research is more recent than most periods researched in prior academic
work. According to Fuller, Netter and Stegemoller (2002) an important factor that influences the
abnormal returns is the method of payment. Furthermore it is stated in the discussion of the prior
literature above that payment of the bidding company by stock may indicate an overvaluation of the
equity shares of the bidding company, which in turn may be an indicator of higher investor
sentiment. This paper evaluates if the samples used in this research are in line with the findings of
Fuller, Netter and Stegemoller (2002). This may be important for the generalization of the results. For
example, if samples used in this research are absolutely not in line with prior research, it may be
possible that possible new results are only applicable to the sample used in this research, and not
applicable to different research. The first hypotheses will therefore be:
16
Hypothesis 1: The abnormal return of acquiring firms is higher for firms that finance the acquisition
with stock than firms that finance their acquisition with cash.
Next, the abnormal returns for the acquiring firm, the target firm and the combined wealth
generation will be computed. According to Bruner (2001) many papers concluded that the target firm
would experience positive abnormal returns and the combined returns would also be positive. The
results on abnormal returns to acquiring firms are mixed. Bruner (2001) reports both scientific
papers that show positive abnormal returns to acquiring firms as well as scientific papers that show
negative abnormal returns. The second hypothesis will therefore be:
Hypothesis 2: Both abnormal returns to target firms as well as the combined wealth effect are
positive.
Hypotheses 1 and 2 make it possible to check the outcomes with prior research as discussed earlier.
To be able to answer the main research question, a hypothesis about the role of macroeconomic
factors in abnormal returns has to be postulated and tested. Flannery and Protopapadakis (2002)
found six macroeconomic factors that have an influence on equity returns. Of these factors, two have
an influence on the level of equity returns, three factors influence the return volatility and one factor
has an influence on both the level of the equity returns as well as on the volatility of these returns.
Only the three factors that influence the level of equity returns will be included in this research, since
it is the aim to determine the effect of macroeconomic factors on the level of equity returns and not
to the determine the effect on the volatility. These factors are CPI (consumer price index), PPI
(producer price index) and a monetary aggregate M1. The monetary aggregate M1 consists of all
currency plus demand deposits plus other checkable deposits. These factors will be included in this
research to check whether or not these factors also have an influence on abnormal equity returns.
Furthermore, Yagil (1996) found two factors, investment level and interest rate in the economy that
are related to merger activity. As stated before, managers can take advantage of these factors by
timing their corporate decisions so that the gains from these decisions are maximized. Since
investment level and interest rate in the economy have an effect on merger activity, it can be
assumed that these factors also have an effect on the gains that arise from mergers and acquisitions
due to this timing factor. Therefore, investment level and interest rate in the economy will also be
included in this research as possible macroeconomic factors that have an effect on abnormal returns.
The third hypothesis will thus be:
Hypothesis 3: macroeconomic factors have an effect on the abnormal equity returns involved in
mergers and acquisitions
The effect of the macroeconomic factors on equity returns and merger activity is mixed in prior
research. That is, some macroeconomic factors portrayed a positive effect, whereas other factors
portrayed a negative influence. It is therefore expected that the effect on abnormal returns will also
be mixed.
17
3.2 Research plan
The sample will consist of mergers and acquisitions between January 2009 and December 2011. The
sample will only include mergers and acquisitions where both the acquiring as well as the target
company are listed on the New York Stock Exchange. An event study will be conducted to determine
the abnormal returns that accompany the acquisition announcement. The abnormal return is
estimated by:
(1)
Where
is the abnormal return for firm I in period t,
is the realized return for the same firm
in the same period and
is the normal return for this firm for this period. The normal return is
calculated using an estimation window and is calculated using the following formula:
(2)
Where
is the return on the market during the estimation window, and α and β are obtained
using an Ordinary Least Squares (OLS) regression. The estimation window will range from 180 days
prior to the acquisition announcement to 30 days prior to the acquisition announcement. The event
window of which the abnormal return will be calculated will range from 5 days prior to the
acquisition announcement to 5 days past the announcement. The cumulative abnormal returns (CAR)
can be calculated as follows:
(3)
Where CAR is the cumulative abnormal return, k is the first day of the event window and l is the last
day of the event window. As stated above, k will thus be 5 days prior to the event and l will be 5 days
after the event. Furthermore, AR is the abnormal return for firm I on day t. To compute the abnormal
returns for the firms in the sample, the statistical software package STATA will be used. This software
package will be programmed to determine the normal relationship between the market portfolio and
the equity shares of all the companies in the sample. Using this relationship, the expected returns of
the shares of a company can be determined based on the returns of the market portfolio, as shown
in equation (2). After that, STATA will be programmed to determine the abnormal returns as the
difference between the expected returns and the realized returns. This is portrayed in equation (1).
After that, STATA will sum up these abnormal returns over the [-5;5] day period to compute the
cumulative abnormal return for every company as shown in equation (3).
18
The cumulative abnormal returns will be calculated for both acquiring firms and target firms. These
abnormal returns will be used to calculate the combined wealth effect. The combined wealth will be
calculated in line with the method outlined by Mulherin and Boone (2000), who defined the
combined wealth effect as the value-weighted CAR:
(4)
Where:
Target firm value of equity
Bidder (or acquirer) firm value of equity
Cumulative abnormal returns for the target firm
Cumulative abnormal returns for the bidding firm
Finally, the cumulative average abnormal return (CAAR) can be calculated. This will be done using the
following formula:
(5)
The acquisitions will be sorted in three different groups, based on the method of payment used for
acquisition. This is in line with Fuller, Netter and Stegemoller (2002) who also used three methods of
payment as criteria. The methods of payment are 1) cash; 2) stock and 3) a combination of cash and
stock. Once the acquisitions have been assigned to the groups, statistical tests will be conducted to
determine if the samples used in this research are in line with the findings of Fuller, Netter and
Stegemoller (2002).
Finally, ordinary least squares (OLS) regressions will be run. The macroeconomic factors will be
included in these OLS regressions. This way it can be determined if these macroeconomic factors
have an effect on the abnormal returns and if they do have an effect to determine the height and
statistical significance of this impact. Finally, it will be determined if the results support the
hypotheses postulated above.
3.3 Data resources
The sample consists of all mergers and acquisitions since January 2001 in which both the acquiring
firm as well as the target firm were listed on the New York Stock Exchange. Corporate actions such as
share repurchases will not be included in the sample since it is possible that the share price reacts
differently compared to the reaction of share prices to mergers and acquisitions. Data on these
mergers and acquisitions will be retrieved from the SDC Platinum database. This data includes the
announcement dates and the method of payment used in the merger or acquisitions. Data on the
share prices of the companies involved in these mergers and acquisitions will be retrieved from the
Compustat database. This database contains financial information up to July 2011. Therefore, the
19
sample will consists of all mergers and acquisitions as described above between January 2001 and up
to July 2011. The total sample consists of 1735 mergers and acquisitions.
To compute the combined wealth effect of all mergers and acquisitions, data on the value of
common equity is needed. Information about the value of common equity of the target company can
be retrieved from the SDC Platinum database. Data on the value of common equity of the acquiring
company will be retrieved from the Compustat database.
Data on the macroeconomic factors will be collected from several sources. The interest rate on
treasury bonds will be retrieved from the Compustat database. Information on the Consumer Price
Index (CPI) and the change in Producer Price Index (PPI), which are two factors to measure inflation,
will be retrieved from the website of the Bureau of Labor Statistics from the United States
Department of Labor. Data on the money supply M1 will be collected from the Federal Reserve Bank
and the information about the investment level in the United States Economy will be retrieved from
the website of the Bureau of Economic Analysis, part of the United States Department of Commerce.
20
4. Results and hypotheses review
4.1 Sample Statistics
The initial sample of mergers and acquisition announcements done by publicly listed firms between
January 2001 and December 2011 that are recorded in the SDC Platinum database consists of 16524
mergers and acquisitions. When the constraint is added that the merger or acquisitions is domestic
(the main market of both the acquiring firm as well as the target firm is the United States) and the
target firm is listed as well, the sample diminishes to 10891 mergers and acquisitions. Furthermore,
corporate decisions such as share repurchases are left out, which decreases the sample size to 2371
mergers and acquisitions. Finally, unavailability of financial information on some firms causes the
sample size to decrease slightly more. The final composition of the sample is shown in Table 1.
Furthermore, table 2 shows the timing distribution of the mergers and acquisitions. Table 3 provides
information about the size of the companies involved by describing details on the values of equity.
Finally, table 4 displays information about the five macroeconomic variables CPI, PPI, M1 and the
interest rate and investment level in the United States Economy.
Table 1 and 2 show that most mergers and acquisitions are paid for with equity. Almost 65% of all
mergers and acquisitions included in this research are paid for with equity. As stated before, it is
possible that managers use their own equity as a currency in the merger or acquisition transaction
when their own equity is overvalued. However, since this research does not have the aim to
determine whether or not stocks are overvalued, this possibility cannot be substantiated with
statistical tests. It can also be seen in tables 1 and 2 that the amount of mergers and acquisitions that
are paid for with stock diminish during the sample period. The quantity of mergers and acquisitions
that were paid with cash also diminishes over time, except for 2005 and 2006, when these types of
deals experienced a slight increase. The quantity of deals that were paid for with a mix of cash and
equity remains fairly stable over the sample period. Furthermore, table 1 shows that although there
have been thousands of mergers and acquisitions over the sample period, only 2293 remain when
actions such as share repurchases are left out.
21
Table 1
Sample formation and sample composition
Table 1 shows all mergers and acquisitions listed in the SDC Platinum database announced
between January 2001 and December 2011. The first column shows the criteria for the sample. The
standard ranking criterion leaves out announcements concerning action such as share repurchases.
The second column shows the number of mergers and acquisitions that meet these criteria. Panel A
shows the formation of the entire sample. Panel B shows the composition of this sample based on
method of payment.
Panel A: Sample formation
Criteria
Sample Size
Firm criteria
Target status: Public
16524
Acquirer status: Public
11646
Target & Acquirer Nation: United States
10891
Deal criteria
Standard ranking
2371
Method of payment: Cash or Stock
2293
Available financial data
1734
Total
1734
Panel B: Sample composition
Method of Payment
Cash only
Sample size with
available data
338
Stock only
1123
Combination of cash and stock
Total
273
1734
22
Table 2
Timing distribution of mergers and acquisitions
Table 2 shows the distribution of the merger and acquisition announcements from January
2001 up to July 2011 per quarter.
Period
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
Q1
Q2
Q3
Q4
Q1
Q2
Cash only
10
20
11
10
10
6
12
12
10
6
7
5
5
7
8
7
7
10
12
15
12
17
14
12
10
10
9
5
5
12
6
6
1
3
2
1
1
6
7
3
4
2
Method of Payment
Stock only
Mix of cash & stock
52
8
79
0
47
5
41
7
25
5
31
7
26
6
28
2
29
1
35
6
31
9
36
7
47
7
29
9
28
8
30
9
36
4
22
12
29
6
23
7
14
7
29
12
28
13
25
18
33
7
33
9
32
8
27
5
19
5
21
5
15
8
24
1
5
0
18
4
8
4
15
4
10
4
14
9
10
5
15
8
13
4
13
7
Total
70
99
63
58
40
44
44
42
40
47
47
48
59
45
44
46
47
44
47
45
33
58
55
55
50
52
49
37
29
38
29
31
6
25
14
20
15
29
22
26
21
22
23
Table 3
Equity values of companies involved
Table 3 displays a descriptive analysis of the value of equity of both the acquiring firm as well
as the target firm. Apart from the data of the entire sample, the data is also split based on method of
payment. All numbers are in millions US$. The difference in number of observations is due to missing
financial data on several companies.
Observations
Mean
Standard
Deviation
Min
Max
1474
1702
5054.24
648.76
14318.24
4798.27
-2564.00
-13593.00
160055.00
173760.00
Method of payment: cash
Acquirer Equity
Target Equity
287
334
6436.15
160.44
13761.76
705.19
-1440.00
-2022.6
139003.00
9618.00
Method of payment: stock
Acquirer Equity
Target Equity
949
1099
3091.02
854.03
10192.91
5927.39
-2564.00
-13593.00
136888.00
173760.00
237
268
11254.94
415.99
24005.45
1023.25
-23.54
-1266.7
160055.00
12255.00
Entire sample
Acquirer Equity
Target Equity
Method of payment: mix
Acquirer Equity
Target Equity
24
Figure 1
Macroeconomic factors time series
Figure 1 shows the time series of the five macroeconomic factors. The interest rate is in
percentages. CPI (PPI) is the Consumer Price Index (Producer Price Index) divided by 100. Money
Supply M1 is the total money supply M1 in trillions US dollars. The investment in the economy is the
total investment in the economy in US dollars divided by 10 billion.
10,00
Interest rate
8,00
6,00
CPI
PPI
4,00
Money supply
M1
2,00
Investment in
the economy
-2,00
Table 3 shows data on the values of equity of both the acquiring companies as well as of the target
companies. Perhaps the most important thing to notice is the difference in relative equity size
between the methods of payment. Firms that financed the merger or acquisition with stock had an
average equity value of $3,091.02 million, whereas their target firms had an average equity value of
$845,03 million. So on average, companies that financed the merger or acquisition with stock bought
targets that had an equity value of around 27% their own equity value. On the contrary, firms that
financed their mergers or acquisitions with cash (mix of cash and stock) on average bought
companies that had an equity value of 2% (4%) of their own equity value. It seems odd that some
companies face a negative value of common equity. The Compustat website states the following
about negative equity values:
“Although negative equity on the balance sheet is unintuitive, it is possible. For example, a
company with high leverage might be forced to write off much of its assets and can find that
has lower assets than its book liabilities.”
Finally it can be seen that the average value of equity of firms that financed their merger or
acquisition with a mix of cash and equity is a lot higher than the average value of equity of
companies that financed their acquisitions otherwise.
Figure 1 finally displays data on the five macroeconomic factors that will be used to determine
whether or not any of those factors have an impact on the abnormal returns to shareholders in
mergers and acquisitions. The negative value in net investment is due to the fact that in a period with
negative investment, more capital was extracted from the economy than invested.
25
4.2 Empirical analysis and results
To determine whether or not the hypotheses that have been formulated earlier can be accepted or
rejected, a three stage approach is used. Every step focuses on a topic of one of the hypotheses. First
step is to calculate the abnormal returns for both the acquiring as well as for the target companies.
Secondly, these abnormal returns will be used to calculate the combined wealth effect of the
acquiring company and the target company. The first two steps do not yet include the
macroeconomic factors, since the first two hypotheses are aimed at determining whether the recent
financial data and the corresponding results are in line with prior research as stated before. The final
step will include the macroeconomic factors to determine whether or not these factors have an
effect on the abnormal returns. The last part of the result section will reflect the results on the
hypotheses postulated above and will discuss if these hypotheses are accepted or rejected.
4.2.1 Abnormal returns
The results on the abnormal returns are split in two categories. The abnormal returns of the
acquiring companies and the abnormal returns of the target companies will be separately computed.
However, the method of computing these returns is for both categories the same. Furthermore, the
abnormal returns will also be separately reported based on the method of payment since prior
research has differentiated between methods of payment and hypothesis 1 states that there is a
difference in the level of abnormal returns between the different payment methods. First, the results
on the abnormal returns for acquiring companies will be discussed, followed by the results on
abnormal returns of target companies.
Hypothesis 1 states that the abnormal returns for firms that finance their mergers and acquisitions
with stock than for firms that finance their mergers and acquisitions with cash. To determine if this
hypothesis holds, we need to compute the abnormal returns of the acquiring firms per group, based
on method of payment. To get an overall view of the abnormal returns of acquiring firm, the
abnormal returns of the entire sample will also be computed. The abnormal returns for target firms
will also be split up in subsamples based on the method of payment. Table 5 displays the results on
the abnormal returns for all firms in the sample.
Table 4
Abnormal returns for acquiring and target firms
Table 4 displays the results for the abnormal returns for both acquiring firms as well as for
target firms. CAR is the cumulative abnormal return for the entire sample. CARc is the cumulative
abnormal return for companies in deal that were financed their cash. CARs is the cumulative
abnormal return for companies involved in deals that were financed with stock and CARm is the
cumulative abnormal return for companies that were involved in deals that were financed with a mix
of cash and stock. The mean, minimum and maximum values and the confidence interval are in
percentages.***,** and * show significance of the confidence interval at the 0.01, 0.05 and 0.10 level
respectively, indicating whether or not the mean values are different from 0.
26
Mean
T-test
P
Min
Max
0.000
0.529
0.000
0.001
95% Confidence interval
Low
High
-1.9353
-1.5129
-0.4791
0.2462
-3.0807
-0.2486
0.2296
0.8757
Acquiring firms
CAR***
CARc
CARs***
CARm***
-1.7241
-0.1165
-2.7833
0.5526
-16.00
-0.63
-18.34
3.35
-207.4173
-69.0291
-207.4173
-45.8732
111.0515
39.1330
111.0515
29.7695
Target firms
CAR***
CARc***
CARs***
CARm***
23.2455
31.1311
20.0877
27.7582
27.37
13.50
20.40
13.08
0.000
0.000
0.000
0.000
21.5792
26.5876
18.1547
23.5739
-126.455
-117.6649
-91.8239
-126.455
271.7744
195.1714
271.7744
227.1033
24.9118
35.6745
22.0206
31.9425
As can be seen in table 4, the abnormal returns for acquiring companies are slightly negative when
there is no differentiation between methods of payments. When a distinction between methods of
payment is made however, it can be seen that the abnormal returns for acquiring companies that
financed their acquisitions with cash or stock is slightly negative and the abnormal returns for
companies that financed their acquisitions with a mix of cash and equity is slightly positive. However,
the results for deals that were financed with cash only are statistically insignificant, whereas the
other subsamples as well as the entire sample for acquiring firms is significant at the 0.01 level. It can
thus be concluded that the overall cumulative abnormal returns for acquiring firms are slightly
negative, but when a company decides to finance the deal with a mix of cash and equity, the
abnormal return is slightly positive.
Contrary to the results on the abnormal returns of the acquiring firms, all the results on the abnormal
returns of the target firms are significant at the 0.01 level. Although according to the minimum value
some target firms experience a negative abnormal return, the average abnormal returns for both the
entire sample as well as for all of the subsamples are positive. The average level of abnormal returns
for target firms is over 23%, and for deals that were financed with cash only the abnormal returns
were even over 31%.
Next step is to determine whether or not there is a significant difference in abnormal returns for
acquiring firms when a distinction between methods of payment is made. To accomplish this, the
mean abnormal returns will be compared in STATA. For a complete view, the differences in abnormal
returns of the subsamples of the target firms are also included. The results of this are portrayed in
Table 5.
27
Table 5
Differences in abnormal returns between methods of payment
Table 5 shows the differences in abnormal returns between the different subsamples which
are based on the method of payment. CAR is the cumulative abnormal return for the entire sample.
CARc is the cumulative abnormal return for deals financed with cash. CARs is the cumulative
abnormal return for companies involved in deals that were financed with stock and CARm are the
abnormal returns for firms involved in deals that were financed with a mix of cash and stock. The first
column shows which (sub)samples are being compared. Mean shows the difference between the
means of the (sub)samples in percentages. The confidence interval is also in percentages. ***,** and
* show the significance of the differences on the 0.01, 0.05 and the 0.10 level respectively.
Mean
T-test
Acquiring firms
CAR, CARc***
CAR, CARs***
CAR, CARm***
CARc, CARs***
CARc, CARm***
CARs, CARm***
-1.6076
1.0592
-2.2767
2.6667
-0.6691
-3.3359
-6.1817
5.8418
-8.2254
8.9911
-2.6574
-10.6125
95% Confidence Interval
Low
High
-2.1173
-1.0979
0.7038
1.4145
-2.8192
-1.7342
2.0854
3.2482
-1.1626
-0.1755
-3.952
-2.7197
Target firms
CAR, CARc***
CAR, CARs***
CAR, CARm***
CARc, CARs***
CARc, CARm***
CARs, CARm***
-7.8856
3.1579
-4.5127
11.0434
3.3729
-7.6706
-11.6402
7.9633
-6.5724
16.2686
3.5602
-11.3018
-9.2134
2.3806
-5.8585
9.7128
1.5155
-9.0009
-6.5577
3.9351
-3.1669
12.3740
5.2302
-6.3402
Several conclusions can be drawn from Table 5. Concerning acquiring firms, some of the
(sub)samples show significant differences in abnormal returns. For instance, the cumulative
abnormal returns for companies that financed their acquisition with a mix of stock and cash if on
average 2.28 percent higher than the entire sample, and this difference is strongly significant.
However, comparing the subsamples which are based on the methods of payment with the entire
sample causes some problems, since the data in the subsample will also be included in the entire
sample. Focus of this research is furthermore on the different subsamples, so the entire sample will
not be considered in this discussion of the differences in abnormal returns. It can be seen in Table 5
that there is a significant difference in abnormal returns between all the subsamples. On average, the
abnormal returns for firms that finance their acquisition with a mix of cash and equity is 0.67 percent
higher than the abnormal returns for firms that finance their acquisition with cash only. It can also be
concluded that the abnormal return of firms that finance their acquisition with a mix of cash and
equity are on average 3.34 percent higher than the abnormal returns for firms that finance their
acquisition with equity only. Finally it can be seen that the abnormal returns for firms that financed
the deal with cash is 2.67 percent lower than abnormal returns for firms that paid their deal with
equity. Therefore it can be stated that firms experience the highest abnormal returns when they
28
finance the deal with a mix of equity and cash, followed by deals financed with cash and finally
experience the lowest abnormal returns when the deal is financed with equity.
The data for the target companies show a different result. As stated above, the differences between
the subsamples and the full sample will not be discussed because these differences are not a point of
interest and might be biased. Therefore we focus on the comparison between subsamples, and that
shows that, just as with the acquiring firms, there is a significant difference in abnormal returns
between firms that were involved in deals that were paid in cash and firms that were involved in
deals that were paid for with a mix of cash and equity. However, acquiring companies would benefit
more from mixed payment deals, followed by cash only deals and finally equity only deals, this is not
the case for target firms. The abnormal returns for firms that were paid for with a mix of cash and
equity are on average 3.37 percent lower than the abnormal returns for firms that were paid for with
cash only. Furthermore, it can be seen that companies for which the deal was paid with a mix of cash
and equity experienced higher abnormal returns then companies for which the deal was paid for
with equity only. The abnormal returns for firms that were paid for with a mix of cash and equity
were on average 7.67 percent higher. Finally, firms that were paid for with cash only experienced on
average abnormal returns that were 11.04 percent higher than the abnormal returns of target
companies involved in equity only deals.
By reviewing Table 4 it can be concluded that the abnormal returns for target firms is always
significantly positive, indifferently of the method of payment. For the acquiring firms, the abnormal
returns only show a positive abnormal return when the merger or acquisition is paid for with a mix of
cash and equity, and negative when the deal is paid otherwise. However, the results on abnormal
returns for acquiring firms that paid for the deal with cash are not significant. Reviewing Table 5 it
can be concluded for acquiring companies the abnormal returns are highest when the deal is paid
with a mix of equity and cash, followed by cash only deals and are lowest for equity only deals. For
target firms however, the abnormal returns are highest in cash only deals, followed by mixed
payment deals and finally lowest for equity only deals.
4.2.2 Wealth effect
In the next step, the combined wealth effect of both the acquiring firm and the target firm will be
analyzed as described by Mulherin and Boone (2000). The combined wealth effect is the value
weighted abnormal return based on the equity values of the acquiring and the target company. By
examining the combined wealth effect it can be determined if the deal in total lead to higher returns
for the shareholders of both companies. Just as in the analysis of the abnormal returns above, there
will be a differentiation based on the method of payment, and it will tested if there is a significant
difference in the combined wealth effect between the different methods of payment. Panel A of
Table 6 contains the levels of the overall combined wealth effect and for each subsample based on
method of payment. Panel B contains the results of the tests to determine if there are significant
differences in the combined wealth effect between the subsamples.
29
Table 6
Combined wealth effect
Panel A contains an analysis of the levels of the overall combined wealth effect as well as the
levels of the combined wealth effect for each subsample. Panel B contains an analysis of differences
between the (sub)samples based on method of payment. The mean variable in panel B shows the
average differences in combined wealth effect between the two (sub)samples. The confidence interval
in Panel B is the interval in which the difference in average combined wealth effect falls with 95%
certainty. WE is the overall combined wealth effect. WEc is the combined wealth effect for deals paid
for with cash. WEs is the combined wealth effect for deals paid for with stock and WEm is the
combined wealth effect for deals paid for with a combination of cash and equity. The variables mean
and the confidence intervals are in percentages. ***,** and * show significance at the 0.01, 0.05 and
the 0.10 level respectively
Panel A: Level of combined wealth effect
Sample
Mean
T-test
P
WE
WEc
WEs
WEm
-0.01
0.59
0.85
1.58
0.993
0.557
0.393
0.115
T-test
P
-0.0160
0.7767
3.4951
1.4267
Panel B: Differences between subsamples
Sample
Mean
WE, WEc
WE, Wes
WE, WEm
WEc, Wes
WEc, WEm
WEs, WEm
-0.7927
-3.5112
-1.4427
-2.7184
-0.65
2.0684
-0.3448
-0.7802
-0.6912
-0.6327
-0.4058
0.4938
0.7303
0.4353
0.4895
0.5270
0.6849
0.6215
95% Confidence Interval
Low
high
-3.707
3.6749
-1.8180
3.3714
-4.5300
11.5202
-0.3463
3.1997
95% Confidence Interval
Low
high
-5.3019
3.7164
-12.3365
5.3142
-5.5363
2.6509
-11.1444
5.7076
-3.7914
2.4914
-6.1454
10.2823
From panel A it can be seen that for none of the (sub)samples the results are statistical significant.
Although the various subsamples show a positive wealth effect, the overall sample shows a negative
wealth effect. Because these results are statistically insignificant, there are not many results that can
be drawn from panel A.
Panel B shows the differences in combined wealth effect between the different samples. It can be
easily noticed that none of the differences is significant. This insignificance may, as well as the
insignificance in panel A, be due to a small sample size, and perhaps that a comparable research with
a larger sample may find significant differences between the different samples.
30
4.2.3 Macroeconomic factors
The final step of the empirical analysis is to determine whether or not the macroeconomic factors
described above have an influence on the level of abnormal returns for both the acquiring firm as for
the target firm, and if so to determine the level of this influence. Table 7 includes data on the
regression ran to determine this.
It can be seen in table 7 that most macroeconomic factors do not have a significant influence on the
abnormal returns. For the abnormal returns of acquiring firms, the consumer price index seems to
have a significant negative impact on the abnormal returns. When more factors are entered, the
influence of the PPI also becomes significant but positive furthermore, when more factors are
entered, the strength of the significance of the CPI increases. In the analysis of the abnormal returns
to target companies, the interest rate has a significant negative influence on the abnormal returns
throughout all the models tested. CPI and PPI only have statistical significance in some models, and
their influence is positive. The investment level in the economy is also statistical significant. The
economic significance however is only small. The money supply M1 is for both acquiring firms as well
as for target firms not only statistical insignificant, but the economic significance is also close to zero.
The most important factor seems to be the interest rate in the economy.
31
Table 7
Effect of macroeconomic factors on abnormal returns
Panel A of table 7 shows the effect of macroeconomic factors on the abnormal returns of the
acquiring companies. Panel B shows the effect of macroeconomic facts on the abnormal returns of
the target companies. Dcash is a dummy variable for cash deals, Dstock is a dummy variable for all
equity deals and Dmix is a dummy variable for deals paid with both equity and cash. In panel A Dcash
is omitted due to collinearity. This is also the case for panel B model 1. For the rest of the models in
panel B Dmix is omitted because of this reason. ** Displays significance at the 0.05 level. Dependent
variables in both panels are the cumulative abnormal returns
Panel A: Macroeconomic effects on acquirer abnormal returns
Independent variables
Model
(1)
(2)
(3)
(4)
Method of payment
Dstock
-0.024*** -0.025*** -0.025*** -0.025***
Dmix
0.009
0.009
0.009
0.009
Macroeconomic factors
Interest rate
CPI
PPI
Money supply M1
Investment in the
economy
R-squared
Adj. R-squared
0.012
0.011
(5)
(6)
-0.025***
0.008
-0.026***
0.007
-0.050
-0.050
0.000
-0.050
-0.003
0.003
0.234
-0.003*
0.002
0.000
0.323
-0.003**
0.003*
0.000
-0.000
0.012
0.010
0.012
0.009
0.015
0.011
0.017
0.012
0.017
0.012
(5)
(6)
Panel B: Macroeconomic effects on target abnormal returns
Independent variables
Model
(1)
Method of payment
Dcash
Dstock
Dmix
-0.104***
-0.035
Macroeconomic factors
Interest rate
CPI
PPI
Money supply M1
Investment in the
economy
R-squared
Adj. R-squared
0.020
0.018
(2)
(3)
(4)
0.038
-0.072***
0.043
-0.065***
0.042
-0.068***
0.040
-0.070***
0.037
-0.072***
-1.398***
-1.248**
0.001*
-1.264**
-0.005
0.007*
-1.911**
-0.004
0.007*
-0.000
-2.317***
-0.003
0.005
-0.000
0.000*
0.025
0.023
0.028
0.024
0.030
0.026
0.032
0.027
0.035
0.029
32
4.3 Hypotheses review
To conclude the empirical analysis, the results above will be reflected on the hypotheses postulated
above. By reviewing the results of the hypotheses, the main research question can be answered. The
first hypothesis was as follows:
Hypothesis 1: The abnormal return of acquiring firms is higher for firms that finance the acquisition
with stock than firms that finance their acquisition with cash.
As discussed before, Fuller, Netter and Stegemoller (2002) found that the abnormal returns for
acquiring firms that paid for the merger or acquisition with stock rather than cash experienced higher
abnormal returns. Table 4 shows that on average the abnormal returns for acquiring firms that
finance their merger or acquisition with stock are -2.78 percent while the abnormal returns for firms
that finance their acquisition or merger with cash are -0.12 percent. This initially shows that these
results are not in line with the results of Fuller, Netter and Stegemoller (2002) since the abnormal
returns for stock acquisitions are lower than the abnormal returns for cash only acquisitions.
Furthermore, Table 5 shows the outcomes of the statistical tests that were used to determine
whether or not there were significant differences in abnormal returns between the different
methods of payment. Table 5 shows that acquiring firms that finance their acquisitions with stock
only experience abnormal returns that are on average 2.67 percent lower than the abnormal returns
of firms that finance their acquisitions with cash only. Therefore, it cannot be concluded that the
results in this research are in line with the findings of Fuller, Netter and Stegemoller (2002). This
causes hypothesis 1 to be rejected:
Hypothesis 1: The abnormal return of acquiring firms is higher for firms that finance the acquisition
with stock than firms that finance their acquisition with cash.
Is Rejected.
Next, this research had as aim to determine whether or not the data used in this research are in line
with Bruner (2001), who found positive abnormal returns for the target firms, mixed results on the
abnormal returns for acquiring firms and furthermore a positive combined wealth effect, were the
wealth effect is a value weighted average of the total abnormal returns, outlined by Mulherin and
Boone (2000). The second hypothesis was therefore postulate as follows:
Hypothesis 2: Both abnormal returns to target firms as well as the combined wealth effect are
positive.
The first section of the empirical analysis focused on determining the level and significance of the
abnormal returns for the acquiring firms and the target firms. Furthermore it aimed at determining if
there were any differences in abnormal returns dependent on the method of payment. Table 4
shows that the abnormal returns for acquiring firms are slightly negative independent of the method
33
of payment, except for deals were the merger or acquisition was paid for with a mix of equity and
cash. The abnormal returns of this last subsample were slightly positive. This is more or less in line
with the results reported by Bruner (2001) who stated that there is no unanimous view on the
abnormal returns for acquiring companies. In addition to these results, Table 5 showed that there is a
significant difference in the level of abnormal returns for acquiring firms based on the method of
payment. The abnormal returns turn out to be significantly higher when the deal is paid for with a
mix of equity and cash rather than when the deal was paid for with cash only or equity only. This
shows there is a significant difference in abnormal returns based on the payment method.
Table 4 also shows the results on abnormal returns for target firms. It can be seen that the abnormal
returns for target firms are strongly positive, and the statistical significance is also strong in these
results. All results are significant at the 0.01 level. However, different than for acquiring firms, the
abnormal returns for target firms is highest when the deal is paid with cash only, followed by mixed
deals and finally lowest for equity only deals.
The second section of the empirical analysis displayed the results on the combined wealth effect. The
results of the combined wealth effect can be seen in table 6. This table shows that even though the
wealth effect for all three subsamples is positive, the results are statistically insignificant. Therefore
these results are not in line with Bruner (2001). However, since the abnormal returns for target
companies are strongly positive and statistically significant, hypothesis 2 is partially accepted:
Hypothesis 2: Both abnormal returns to target firms as well as the combined wealth effect are
positive.
Is Partially Accepted.
The final step in the empirical analysis, and the main aim of this research, was to determine whether
or not macroeconomic factors had an influence on the level of the abnormal returns and if so, to
determine the extent of this impact. Flannery and Protopapadakis (2002) found three
macroeconomic factors that influenced cross-sectional equity returns. These factors were consumer
price index, producer price index and a monetary aggregate M1. Moreover, Yagil (1996) found two
more factors that influenced the level of equity returns namely interest rate and investment level in
the economy. To determine if these factors also have an impact on abnormal equity returns
hypothesis 3 was formulated as follows:
Hypothesis 3: macroeconomic factors have an effect on the abnormal equity returns involved in
mergers and acquisitions
In the third section of the empirical results, linear regressions were run with the cumulative
abnormal equity returns of the acquiring and the target companies as dependent variables to test
whether or not the five aforementioned macroeconomic factors have an influence on the abnormal
equity returns. Table 7 shows the results of these regressions. As discussed in the section concerning
the macroeconomic variables, there are some macroeconomic factors that show a statistical
significant impact on abnormal returns, especially on the abnormal returns for target firms. On the
abnormal equity returns for acquiring companies, the CPI and the PPI have a significant effect. The
CPI has a negative effect on the abnormal returns for acquiring firms, whereas the PPI has a positive
34
effect on the abnormal equity returns. On the abnormal equity returns for target companies, the
interest rate and the level of investment in the economy have a significant effect. The interest rate
has a negative effect on the abnormal returns for target firms, whereas the level of investment in the
economy has a positive effect on the abnormal equity returns. However, the economic significance of
the level of investment in the economy is very small. Overall, it can be concluded that some
macroeconomic factors do have an influence on the level of abnormal equity returns of both
acquiring as well as target companies. Hypothesis 3 is therefore accepted.
Hypothesis 3: macroeconomic factors have an effect on the abnormal equity returns involved in
mergers and acquisitions
Is Accepted.
5. Concluding remarks
According to Nelson (1959), corporate mergers and acquisitions are as old as corporations itself, and
were in the early days mainly arranged through marriage. Despite this long history, the first mergers
and acquisitions that lead to relatively large corporations compared to the market did not emerge
until the late 19th century. Since then, five large merger waves have been identified in the US market
and extensive research has been conducted to determine what factors play a role in these mergers
and acquisitions. Evidence in this area of interest may provide additional understanding to managers
as when to time their corporate mergers and acquisitions as such that it is most profitable for their
shareholders. Furthermore it may aid shareholders in their understanding of the factors that
determine the level of abnormal returns in mergers and acquisitions and may support their
understanding of what to expect with regard to the equity returns when mergers or acquisitions are
announced.
This research focuses on the abnormal returns on equity that the shareholders of the companies
involved experience. Fama et al. (1969) were the first to conduct research on these abnormal
returns, and since then the scientific documentation of these returns has been supplemented by
many other economists. The influence that macroeconomic factors such as inflation have on these
abnormal returns is however less well documented. This research focuses on the effect
macroeconomic factors have on the abnormal returns of the acquiring and the target companies. To
determine whether or not macroeconomic factors have a significant influence on the abnormal
returns in mergers and acquisitions, data on a sample of 1734 mergers and acquisitions that were
announced between January 2001 and August 2011 was collected. After the data collection, three
hypotheses were tested. The first two hypotheses were tested to determine if the data used in this
research is in line with prior research, whereas the third hypothesis had the aim of determining the
impact of macroeconomic factors.
Contrary to prior research, the data in this sample does not support the findings that the abnormal
returns are higher for acquiring firms that finance their merger or acquisition with equity only rather
than with cash only. The results did however show that the abnormal returns for firms that finance
35
their merger or acquisition with a mix of equity and cash is significantly higher than when the deal is
financed with equity only or cash only. The data also shows that the abnormal returns for target
firms is on average significantly positive, regardless of the payment method used. The data has not
been able to substantiate any conclusions about the combined wealth effect accompanying mergers
and acquisitions, since none of the results in this area was statistical significant. Finally, this research
tried to determine whether or not several macroeconomic factors have an influence on the abnormal
returns of both the acquiring firm as well as the target firm. Prior research by Flannery and
Protopapadakis (2002) and Yagil (1996) yielded five macroeconomic factors that had an influence in
the level of equity returns. These five factors were consumer price index, producer price index, a
monetary aggregate M1, the interest rate and the investment level in the economy. These factors
were tested in this research to determine if they did not only have an influence on equity returns as
prior research states, but to determine if they also had an effect on the abnormal equity returns. On
the abnormal equity returns for acquiring companies, the CPI and the PPI have a significant effect.
The CPI has a negative effect on the abnormal returns for acquiring firms, whereas the PPI has a
positive effect on the abnormal equity returns. On the abnormal equity returns for target companies,
the interest rate and the level of investment in the economy have a significant effect. The interest
rate has a negative effect on the abnormal returns for target firms, whereas the level of investment
in the economy has a positive effect on the abnormal equity returns. However, the economic
significance of the level of investment in the economy is very small. Overall, it can be concluded that
some macroeconomic factors do have an influence on the level of abnormal equity returns of both
acquiring as well as target companies.
This paper had as aim to determine if macroeconomic factors had an influence on the abnormal
returns that arise with the announcements of mergers and acquisitions. Some of the factors that
were included in this research showed a significant influence on these abnormal returns.
There are some important limitations to this research. For starters it might well be that there are
other macroeconomic factors that do have a significant impact on the level of abnormal returns.
Also, this research only aimed to determine the impact of these factors on the level of abnormal
returns, disregarding the possible effect of these factors on the volatility of the abnormal returns.
Suggestions for future research might thus be to investigate a broader range of macroeconomic
factors as well as the impact of these factors on the volatility of abnormal returns. Based on this
research, managers and investors can include a set of macroeconomic factors to be able to
determine beforehand what effect these factors will have on their expected abnormal returns.
36
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