Merger Arbitrage: Evidence of Profitability
Taewon Yang and Ben Branch
Visiting Assistant Professor
University of Massachusetts
Amherst, Mass. 01002
Professor of Finance
Isenberg School of Management
University of Massachusetts
Amherst, Mass. 01002
Merger arbitrage is widely considered one of the principal areas of hedge fund
investment. While the investment process of merger arbitrage is generally known, less
information exists, at least in the practitioner community, as to academic research as to
the basis for various merger activity as well as to the profitability of such merger activity.
In this article we review various approaches to merger arbitrage as well as academic
research on the profitability of various merger arbitrage strategies.
Merger arbitrage specialists invest in companies involved in a merger or an
acquisition. In an acquisition situation the manager will usually go long the stock of the
company being acquired and short the stock of the acquiring company. The stock of the
company being acquired will in general trade at a discount since all acquisitions take time
and there always is a risk that the acquisition will not be completed. Merger arbitrage
funds make investment profits when they successfully anticipate the outcome of an
announced merger and capture the spread between the current market price and the price
at which the stock will be trading at after the merger is completed.
When a merger is pending, uncertainty about the outcome creates a pricing
disparity between the price of the acquiring company’s stock and the price of the target
company’s stock. Merger arbitrage managers evaluate announced mergers and
acquisitions and if they find favorable risk/return characteristics they will go long the
target company’s stock and sell the acquiring company’s stock. If the deal is completed
in the way the manager anticipates, profits will be made from the long position. Since
traditional investment funds are limited to their use of short selling, the merger arbitrage
strategy can not be found in a traditional mutual fund. Merger arbitrage hedge fund
managers do not attempt to anticipate possible mergers. Instead, they analyze already
announced mergers and acquisitions to identify favorable risk/return characteristics.
A simple example would be an acquisition where a company is being acquired
through the use of cash only. Since the outcome of the acquisition is uncertain before the
transaction has taken place, the target company’s stock will trade at a discount from what
the deal would suggest. When the deal is completed, the investor receives the discount as
an investment return. In a stock-for-stock transaction the manager of a merger arbitrage
fund will go long the acquiring company’s stock and sell the target company’s stock short
to lock in the spread. For other than cash or stock-for-stock transactions the outcome of
the deal is generally more uncertain and the discount (and potential profit) greater.
Managers of merger arbitrage funds control the risk of the portfolio by
diversifying across different markets and by investing in both announced mergers and
acquisitions. Holding a diversified portfolio will lower the impact any one position will
have on the portfolio. Open positions are monitored constantly. If new information
regarding the merger/acquisition process is announced the manager can either increase
the exposure (if the information makes the deal less uncertain) or withdraw money from
the position (if the information makes the deal more uncertain).
Merger arbitrage is mainly event driven rather than market driven. Therefore,
investment returns generally have a low correlation with market returns. Since the
strategy is event driven the fund can theoretically make investment returns in any market
environment. However, mergers and acquisitions situations tend to occur in times of
economic upturns and bullish markets where high stock prices make stock-for-stock
acquisitions favorable. In periods of downturn the manager can have a hard time finding
enough merger arbitrage situations to keep the portfolio diversified.
Merger Arbitrage: Academic Evidence
Until recently, most of the risk arbitrage literature focused on two types of
mergers: Stock swap mergers and cash tender offers (Brown and Raymond ,
Samuelson and Rosenthal , Duke et al. , Karolyi and Shannon  and
Jindra and Walkling , Mitchell and Pulvino , Huston  and Baker and
Savasoglu ). In addition to the above merger types, other strategies include collar
mergers. The collar merger structure is a device in which the would-be acquirer offers a
variable exchange rate (acquirer shares for target shares). The proposed exchange rate is
made variable in order to reduce the risk of over/under payment in merger deals.
Historically, collar merger has not been included in merger/risk arbitrage research.
Collar mergers seemed to be implicitly classified as a sub-category of fixed rate stock
swap mergers in the merger literature. However, in risk arbitrage, the range of exchange
rates in collar mergers might well have different effects on returns and/or success rates
from that of fixed exchange rate mergers.
Academic research n risk arbitrage followed the success stories of the 1980’s merger
wave. Initially, risk arbitrage research focused on the predictability of success and price
movements associated with the proposed mergers.
The return derived from a risk arbitrage strategy depend on three factors:
1. The locked-up initial spread1.
2. The probability that the proposed merger will succeed and
3. The return for the risk arbitrager if the merger effort fails.
Among them, only the locked-up initial spread is likely to be known on the
announcement date. Even this initial spread may be changed later. Clearly, predicting
which mergers are likely to succeed (and over what time period), as well as plausible
results and/or price movements, especially target price movements is a major issue and
challenge for the risk arbitrage industry (Asquith , Samuelson and Rosenthal
, Brown and Raymond , Sander and Zdanowicz , Jindra and
Walkling  and Huston ).
The second line of research has explored why a risk arbitrage strategy may be
profitable and which factors explain the first factor in the return-generating process – the
initial spread. This research resulted from empirical findings of high abnormal returns
from the risk arbitrage strategy. Duke et al.  and Jindra and Walkling 
found an annualized excess return of over 100%. Karolyi and Shannon  found an
annualized excess return of 33.9%. Baker and Savasoglu  found a monthly
abnormal return of 8%.
The third line of study focuses on how to calculate the appropriate risk-adjusted
return for a risk arbitrage strategy. This line of research seeks to analyze what the risk
arbitrage return-generating-process is and to test whether the existing linear asset pricing
model can be properly used to calculate the relevant excess return. The just discussed
second line of study in the literature implicitly assumes the correctness of the linear
return process in calculating the risk-adjusted return for a risk arbitrage strategy. The
literature in the third, however, finds evidence of a nonlinear return-generating-process.
(Merton , Kalay and Loewnstein , Bhagat, Brickley and Loewenstein
, Glosten and Jagannathan  and Fung and Hsieh ). This finding
suggests that a nonlinear pricing model should be used to calculate the risk arbitrage risk-
adjusted return (Mitchell and Pulvino ).
The fourth line of risk arbitrage research focuses on technical issues such as how
to set up an index-time series. To undertake empirical analysis, one needs to deal with
time series or cross-sectional data that represent the market well. However, constructing
a time series or cross sectional data well representing the market is difficult. Especially,
if the investment is stylized, it is more difficult to have correct data for the stylized
market such as risk arbitrage.
In this article, we review the extant literature along the second and the fourth lines
that may of more interest to the readers of this Journal.
Performance Literature on Stock Prices of the Acquirer and the Target
The price movement or performance of the target and acquirer’s stocks has been research
may further be classified into two strands. One focus on the wealth effect and the other
on the performance of risk arbitrage. The wealth effect literature explores the abnormal
returns of the target or acquirers’ stocks around the merger periods and their
determinants. This research tends to dominate the merger and acquisition literature. The
risk arbitrage literature, on the other hand, deals with the locked up spreads from the
targets’ and acquirers’ stock price movements. Risk arbitrage has been practiced
extensively as a trading technique on Wall Street for a number of years. Interestingly, the
wealth effect and risk arbitrage literatures seem to converge. That is, the wealth effect
literature represents the movement of the underlying securities – targets and acquirers’
stocks. The risk arbitrage literature deals with the long/short trading technique over the
movement of the underlying securities. Therefore, we first briefly review the underlying
hypotheses and empirical tests in the wealth effect literature. We then proceed to review
the risk arbitrage literature.
Wealth Effects in Merger: Hypotheses and Empirical Tests.
The wealth effect is well documented in the merger and acquisition literature, relating
lots of hypotheses for underlying motives to various empirical results in finance. We
concentrate on the literature dealing with abnormal returns during a merger
announcement and consummation dates.
Hypotheses Tested in Abnormal Returns Literature
Synergy, information and wealth transfer hypotheses (Hubris) were generally tested to
explain the gains over a merger period2. If the payment method –cash or stock - tends to
impact the abnormal returns over the merger period, hypotheses relating to asymmetric
information, taxation, investment opportunities, mode, cash availabilities, ownership
structure or business cycle hypothesis, are subsequently tested. 3
1) Synergy Theory.
This theory asserts that acquisition may increase the combined value of the target and the
acquirer. The increase in value tends to result from capitalizing some specialized or
inefficiently used pre-merger resources such as inefficient management and operating
systems of the target. Therefore, if the resources are captured by other bidders in the
bidding competition, an original bidder may suffer losses. Empirical support for this
hypothesis was shown in Dodd and Ruback , Bradley , Bradley, Desai and
Kim  and Bradley et al. .
2) Information Hypothesis.
This view asserts that new information generated during the acquisition leads to
reevaluate the targets. The reevaluation generates higher abnormal returns for the target
stockholders. Dodd and Ruback (1977) and Bradley (1980) found that the unsuccessful
target in tender offers tends to experience significantly positive abnormal return
This hypothesis contends that the abnormal returns to the target result from the wealth
transferring from the bidders to the target. This was theoretically developed by Roll
4) Asymmetric Information.
This hypothesis contends that the method of payment signals the intrinsic value of
bidders to the market, because bidders with the intrinsic value information may choose
the payment method that benefits themselves most. This hypothesis is consistent with
Jensen and Meckling  and Myer and Majluf . They suggest that if the
bidder’s value is undervalued, managers of the acquiring firm would use cash, while they
would use stock if the stock is overvalued. This is empirically supported by Travlos
Mergers that are accomplished with cash payment are directly related to the issue of
taxation. Target stockholders offered a cash payment may demand a premium to offset
the tax impact of the transaction. The premium may explain the abnormal returns to the
target stockholders (Wansley, Lane and Yang  and Huang and Walkling ).
6) Investment Opportunities.
Debt financing maximizes the values of firms with poor investment opportunities while
equity financing maximize the value of firms with good investment opportunities.
Therefore, the firms with valuable investment opportunities are more likely to issue
equity. And the market may welcome the equity issuing. (Jung , Kim and Stulz 
and Martin )
7) Risk Sharing
Hansen  models the choice of payment method under the condition of information
asymmetry. In his model, if the bidder has less information than the target, the bidder
wants to use the stock forcing the target shareholders to share any post-acquisition risks.
He implied that this problem may become more apparent, as the target size increases.
Shareholders and managers of the target firm will have different positions vis a vis the
takeover. The shareholders want to maximize the value of their stockholders as a result
of the takeover. For example, managers will not give up their position unless the wealth
gains from merger offset the lost benefits (Stulz, Walkling and Song  and Song and
Walkling ). Also, managers are reluctant to use their firms’ stock to finance
acquisition if doing so will dilute their control (Amihud, Lev and Travlos  and
Jung, Kim and Stulz ). Therefore, their ownership position may influence the
gains from the merger.
9) Cash availabilities.
Firms with larger free cash flows are more likely to use the cash to finance their
investments (Myer  and Jensen )
10) Regulation (Mode)
Mergers accomplished with cash payment tend to take less time than those with stock
payment to compete the acquisition, meeting legal requirements. Cash payment in merger
transactions is subject to Williams act and stock payment is to Securities Act of 1933.
11). Economic environments
Increasing economic activity has been shown to be positively related to stock financing
(March  and Choe, Masulis and Nanda )
Tender offers might have more competition in the future than mergers. This competition
may drive the abnormal returns (Suk and Sung ).
Empirical Tests for Abnormal Returns and Hypotheses
In the beginning, the issues were positive/negative abnormal returns in successful/
unsuccessful merger and acquisitions, depending on the estimation period. In general,
studies find a positive abnormal return to the stockholders of the target (Dodd and Bruck
 and Bradley ) and a negative or zero abnormal return to those of the
acquirers around an announcement date. During the merger period, the abnormal return
for successful targets tends to increase. But the abnormal return for unsuccessful targets
tends to decrease. The acquirer has mixed results –negative or zero abnormal returns
(Dodd , Asquith , Bradley, Desai and Kim , Song and Walkling
, Jennings and Mazeo , Sullivan, Jensen and Hudson  and Suk and
Huang and Walking  and Travlos  are among the first researchers to
pay attention to the payment method in mergers and acquisitions. Huang and Walkling
 and Travlos  find that cash payments tend to generate higher abnormal
returns than do stock payments. This finding has been supported by other empirical
studies. However, takeover attempts involving cash payments tend to suffer greater losses
than those involving stock payment at a termination date (Chang and Suk ).
To understand the underlying motives for the wealth distribution over the merger
process, many hypotheses and related variables have been intensively tested. A
synergistic hypothesis (Bradley, Desai and Kim [1983,1988], Bhagat, Brickley and
Loewenstein  and Sullivan, Jensen and Hudson ), an information hypothesis
(Dodd and Ruback  and Bradley ) and a wealth-transferring hypothesis (Roll
) have been tested to explain the overall wealth effect between the target and the
acquirer. Empirical results tend to support the synergy hypothesis. On the other hand, an
information asymmetry hypothesis (Myer and Majluf , Sullivan, Jensen and
Hudson  and Chang and Suk ), taxation hypothesis (Huang and Walkling
), growth opportunity hypothesis (Martin ) and competition hypothesis (Suk
and Song ) etc have been used to explain abnormal return patterns with a payment
method (Travoli  and Martin ). Empirical results tend to support the
asymmetric information hypothesis. As explanatory variables, the payment method,
bidder’s competition, target’s resistance or debt ratio of a target mainly are found to drive
the abnormal return significantly. Managerial ownership structure is found to be
significant only in the competing bids but not significant otherwise (Stulz, Walkling and
Song  and Song and Walkling ). Institutional ownership shows mixed
results. The target size is found to affect the gains to targets. And most recently, results
on the types of strategic acquisitions indicate that strategic acquisitions do not generally
influence the gains to bidders over an acquisition, but a diversification strategy with
potential overlap generates negative impacts on the bidder’s stock price (Walker ).
To deal with abnormal return calculation and statistical tests, many researchers
used a market model with equally weighted market or value weighted market index. A t-
or z-test with various standard deviation formulas is used to determine the statistical
significance of the abnormal returns. In the determinant analysis, a multivariate
regression model is used to examine the explanatory factors. The event periods such as t-
10 to t+10, t-5 to t+5 or t-1 to t+1, are typically used for calculating the cumulative
Performance of risk arbitrage
The existing risk arbitrage literature is primarily empirical in nature. Relatively little
theoretical research has been done on the subject. Most risk arbitrage research used cash
tender offers or/and stock swap mergers to calculate returns of risk arbitrage. We adopt
the same classification scheme here.
A) Cash tender offer
Duke et al.  examined 761 cash tender offers that took place during 1971 to 1985.
They reported an average abnormal return of 24.6% for 52.4 days, corresponding to an
annualized abnormal return of 171%. This abnormal return was calculated assuming that
an investor bought the target stock on the tender offer announcement day and sold the
stock on the resolution day. They found that this abnormal return tends to be inversely
related to the probability of tender success.
Jindra and Walkling  measured the excess return of a risk arbitrage strategy
without taking accounts of the input of dividends. They used a sample of 362 cash tender
offers in which a bidder seeks for 100% of target shares and the transaction value exceeds
$10 million during 1981 to 1995. The single factor market model with the CRSP value
weighted market index was used to calculate the excess returns. Parameters were
estimated during a period of t-260 to t-20. They calculated the cumulative abnormal
returns on targets over one day to eight pseudo-weeks after an announcement.
Interestingly, an arbitrageur was found to earn an excess return of 1.42 to 1.54% or an
annualized return of 102 to 115% if she or he takes a long position in a target during one
week following the announcement. Also, they found that an arbitrageur buying the target
and shorting the acquirer during one week following the announcement tended to earn an
excess return of 1.88% or the corresponding annualized return of 156%.
Empirically, they found abnormally high volume4 before and after the tender offer
announcement, indicating significant additional trading activity. In a multivariate
regression analysis, the arbitrage spread5 was found to be, on average, positively related
to the size of bid premium, friendly managerial attitude about the offer and the existence
of rumors about the offer. But it seemed to be negatively related to the target size and
pre-offer run up. The managerial ownership was, on average, found to be only
significant in hostile takeovers. Bidder’s acquisition experience was found to be
insignificant. Also, in terms of variables unknown at the announcement date, the spread
tended to be positively related to the duration of the offer but negatively related to the
revision of the offer.
B) Stock swap merger
Karolyi and Shannon  measured the return of risk arbitrage without dividends.
They used the 37 Canadian acquisitions with over $50 million during 1997 and
multivariate regression analysis. The return was calculated, assuming that an investor
buys the target and shorts the bidder one day after the tender announcement. They found
that risk arbitrage tended to generate 4.78% in excess of the TSE 300 stock index during
an average period of 57 days, or an annualized excess return 33.9%. The spread may be
significantly related to target size and pre-announcement run-up (2 week). But the excess
return was unlikely to be related to the likelihood of success (days to close), target size,
beta, price to sale ratio, price to book ratio, payment method, pre-announcement run-up
or industry sector.
C) Cash tender /Stock swap mergers
Mitchell and Pulvino  calculated the daily excess return. They used a sample of
4,750 stock swap mergers, cash mergers and cash tender offers during 1963 to 1998 and a
contingent approach – selling uncovered index put options. They found that risk
arbitrage tended to generate an annual excess return of 4%. The annualized return
calculation method, transaction costs6 and a risk premium for deal-failure were attributed
to the higher returns in risk arbitrage.
Baker and Savasoglu  explored risk arbitrage, using 2,088 cash and stock
merger/acquisitions during a period of 1981 to 1996. They applied the return formulas
below to calculate the risk arbitrage returns. Event study methodology was used to test
determinants for excess returns. The risk arbitrage strategy tends to generate a monthly
abnormal return, 8%. Excess returns were found to be positively related to the firm size,
dollar trading volume and two measures of idiosyncratic risk – takeover premium and the
probability of success. And unlike Mitchell and Pulvino , they found that the
transaction costs were not the major determinant of return.
The risk arbitrage literature generally found annualized returns in excess of 100% for a
risk arbitrage strategy applied to the cash tender offers during 1971 to 1985 and 1981 to
1995 (Duke at al.  and Jindra and Walkling ). Karolyi and Shannon 
find an annualized return of 26% in stock mergers in the Canadian market during 1997.
And recently, Mitchell and Pulvino (2000) report that the risk arbitrage in stock merger,
cash merger and cash tender offers during 1963 to 1998 tended to generate annual excess
returns of 4% after controlling for nonlinear return profile and transaction costs. Baker
and Savasoglu  document a monthly abnormal return of 8% in the risk arbitrage
strategy during 1981 to 1996.
The possible explanations that have been suggested in the literature for these high
returns include: an anomaly, the impact of liquidity or transaction costs, and/or a risk
premium. Shleifer and Vishny , using a theoretical model, suggest that there is an
inverse relationship between the arbitrageur’s liquidity and potential arbitrage profits in
the market. Mitchell and Pulvino  suggest transaction costs, other practical
limitations and the risk premium for deal-failure as reasons to expect the higher return for
a risk arbitrage strategy. However, Baker and Savasoglu (2000) find that the transaction
cost was not the major determinant of risk arbitrage returns.
The literature also explores firm/deal-specific factors and economic circumstance
as potential explainers of the initial spread, applying a multivariate regression analysis.
Jindra and Walkling  classify the factors into two groups: known and unknown
factors as of the announcement date. They find the initial spread to be positively related
to the known factors such as bid-premium, target managerial ownership, target
managerial attitude towards the offer, rumors and run-ups and negatively related to the
unknown factors such as revision of exchange ratio and duration. Brown and Ryngaert
 find the tendering rate to be positively related to the bid-premium. And in terms of
economic environment, Moor  argues that economic factors might not influence
risk arbitrage but Mitchell and Pulvino  find risk arbitrage returns to be positively
related to the level of market returns in severely depreciating markets but uncorrelated in
flat or appreciating markets. Baker and Savasoglu  contend that the excess returns
are positively related to the firm size, trading volume, takeover premium and probability
of success. The wealth effect and risk arbitrage literature are summarized in Appendix 1.
Historically, setting up the indices for the underlying markets seemed to receive less
attention than dealing with biases in the current stylized indices. Interestingly, both
indices tend to deal with the same issues in the performance literatures. That is, finding
right indices/time series that reflect the stylized/underlying markets. However, the
stylized indices are likely to be limited in reflecting the markets. These current stylized
indices in the markets are structured to represent the selection and timing skills of the
fund managers, not the underlying stylized markets such as risk arbitrage markets. In
other words, the stylized indices tend to show how the funds (and their managers) are
doing, but not the markets. These characteristics also cause survivor biases in the
Fund Indices and Survivorship Bias
Kalay and Loewnstein  show how to test the survivor biases problem in calculating
abnormal return around the dividend payment announcement, using the sub period
analysis –sensitivity analysis. In exploring the performance of mutual funds, Brown,
Goetzman, Ibbotson and Ross , and Brown and Goetzman  conclude that
surviving funds generated higher returns than all funds, suggesting that there is a
survivorship bias in performance measurement. Malkiel  explored the performance
of equity mutual funds during 1971 to 1991. He tested all equity mutual funds existing
each year, and reported that survivorship bias was substantial. The performance
persistency is likely to be influenced by survivorship bias. However, persistency may not
be robust as it is found that there was strong persistency in the 1970s but not in the 1980s.
Fung and Hsieh  explored the survivorship bias in CTAs during 1980 to 1995. The
survivorship measurement was defined as the difference in average returns between
surviving funds and all funds. They find that the style analysis is not influenced by the
survivorship bias. Ackermann et al.  examined the performance of 906 hedge
funds during 1988 to 1995. They find that hedge funds tend to outperform mutual funds.
Hedge funds tended to be more volatile than mutual funds and market indices. In a
subsection, they explored data conditioning biases such as survivorship bias, liquidation
bias, backfilling bias and multi-period sampling bias, etc. They found no systematic bias
in their conclusions.
Risk arbitrage indices/time series from the underlying assets
In the risk arbitrage literature, research on how to set up time series data that truly
represent the risk arbitrage market is sparse. Jindra and Walkling  and Baker and
Savasoglu  used cross-sectional data to analyze the initial spread, while Mitchell
and Pulvino  developed time series indices: passive risk arbitrage portfolio
(PRAM) and calendar time value weighted average of returns (VWRA). Both are
monthly indices. PRAM includes the transaction costs – brokerage fee and price impact
from illiquidity – and trading constraints. PRAM seems to simulate a risk arbitrage
portfolio. The portfolio starts with $1 million in 1963. The investment for $1 million has
three constraints: 1) any investment on a merger can’t exceed 10% of the total portfolio’s
value. 2) the amounts invested in any single deal are decided such that the price impact
on stocks is less than 5%7. 3) PRAM doesn’t allow leverage in investments. In VWRA,
monthly returns are obtained by calculating a weighted average of each monthly return of
deals. And the weight was the total market value of each target. VWRA assumes that
risk arbitrage will be set up for every merger transactions. Also, no transaction costs are
assumed. They find empirical results from using PRAM similar to those from using
actual risk arbitrage hedge funds during 1990 to 1998.
The empirical results are, on average, influenced by the characteristics of data.
Especially if the data are rare or hard to be taken, the empirical results will be dominated
by available data. The stylized investment markets seem to have the similar situation.
Though some stylized indices are available in the markets, they, as active indices, tend to
represent the selection and timing skills of the fund managers rather than the underlying
stylized markets. Also, the haunting bias problems in the existing indices have been
known to cause other problems in testing hypotheses.
Ackermann. C, R. Mckenally and D. Ravenscraft , 1999 “ The Performance of Hedge
Funds: Risks, Return and Incentives.” Journal of Finance, Vol.54, No.2, pp. 833-874
Amihud. Y, Lev. B and N. G Travlos, 1990 “ Corporate control and the choice of
investment financing: the case of corporate acquisition” Journal of Finance Vol.1990,
Asquith. P 1983 “Merger bids, Uncertainty and Stockholder Return” Journal of Financial
Economics Vol 11, pp.51 – 83.
Baker. M and Savasoglu. S, 2000 “ Limited arbitrage in mergers and acquisitions”
Working paper, Havard University.
Bhagat. S, J Brickley and U. Loewenstein, 1987 “ The Pricing Effects of Interfirm Cash
Tender Offers” The Journal of Finance Vol 42, pp.965 – 986.
Bradley. M , 1980 “ Interfirm tender offers and the market for corporate control” Journal
of business Vol.53, No.4, pp. 345 –376.
Bradley. M, A.Desai and E.H. Kim, 1988 “Synergistic gains from corporate acquisitions
and their division between the stockholders of target and acquiring firms” Journal of
Financial Economics Vol.21., pp. 3-40.
Breen. W, L.S. Hodrick and R.Korajczyk, 1999 “ The determinants of equity illiquidity,
Working paper, Northwestern University
Brown, Keith and Raymond, Mitchael, 1986 “ Risk Arbitrage and the Prediction of the
successful Corporate Takeovers” Financial Management, Autumn, pp.54.
Chang.S and D.Suk 1998 “Failed takeover, method of payment and bidder returns” The
Financial Review Vol.33, pp.77-84.
Choe. H, R.W Masulis and V. Nanda, 1993 “ Common stock offerings across the
business cycle” , Journal of empirical finance Vol.1, pp. 21-33.
Cosh, Andy, 1990 “ Predicting Success; Pre-Merger Characteristics and Post-Merger
Performance” Working paper 6 of University of Cambridge Small Business Research
Centre. pp. 24, August.
Cosh,Andy, Hugh,Alan and Kambhampati, Uma, 1993 “ Takeover Success or Failure?
The Experience of Large and Small U.K.Companies” Working paper 10 of University of
Cambridge Small Business Research Centre. pp. 10, August
Cornelli, F and Li, D, 1998 “ Risk Arbitrage in Takeovers” Rodney L. White Center for
Financial Research. The Wharton School, University of Pennsylvania
Dodd. P and R. Ruback, 1977 “ Tender offers and stockholder returns” Journal of
Financial Economics Vol(5) No 4, pp. 351-373.
Dodd. P , 1980, “ Merger proposals, Management discretion and Stockholder Wealth”
Journal of Financial Economics. Vol. 8 No 2, pp.105 –138.
Duke, William, Cheryl, Frohlich and Ma, Christopher, 1992 “ Risk Arbitrage in Tender
offers” Journal of Portfolio Management, Vol. 18, pp. 47-55.
Ebeid, Fred Joseph “ The Inetr-firm corporate cash tender offer: operating, marker and
bid characteristics of target firms. Ph.D Dissertation. University of Illinois at Urbana-
Fung. W and D. Hsieh, 1997, “ Empirical Characteristics of Dynamic Trading Strategies:
The case of hedge funds” Review of financial studies, Vol.10, pp. 275-302.
Fung, William and David Hsieh, 1999 “ A Risk neutral approach to valuing trend
following strategies” Review of Financial Review.
Glosten, L and R, Jagannathan, 1994 “ A contingent claim approach to performance
evaluation” Journal of Empirical Finance, Vol.1, pp. 133-160.
Hansen. R, 1987 “ A theoty for the choice of exchange medium in mergers and
acquisition” Journal of Business. Vol. 60, pp. 75 –95.
Hoffmeister, J. Ronard and Edward A Dyl, 1980 “ Predicting outcomes of cash tender
offers” Financial Management. Vol.9, pp. 50-58.
Jennings R H and M A Mazeo 1993 “ Competing Bids, Target Management Resistance
and the structure of Takeover Bids” Review of Financial Studies Vol 6 (4), pp. 883-909.
Jensen. M and W. Meckling, 1976 “ The theory of firm: Managerial Behavior, Agency
costs and Ownership structure” Journal of Financial Economics. (October), pp. 305-360.
Jensen. M, 1986 “ Agency costs of free cash flow, corporate finance and market for
takeovers, American Economic Review Vol. 76, pp. 323-329.
Jindra, Jan and Walkling Ralph, 1998 “ Arbitrage Spreads and the Market Pricing of
Proposed Acquisitions”, Working paper, The Ohio State University
Jung. K, Y. Kim and R. Stulz, 1995 “ Investment opportunities, managerial discretion
and the security issue decision, Working paper. The Ohio State University
Kalay Avner and Uri Loewenstein , 1985 “ Predictable Events and Excess Returns: The
Case of Dividend Payment Announcements” Journal of Financial Economics, Vol 14 pp.
Karolyi G A and J Shannon, 1998 “ Where’s the Risk Arbitrage?” Working paper, The
Ohio State University.
Larker, David and Lys, Thomas, 1987 “An empirical analysis of the incentives to engage
in costly information acquisition: The case of risk arbitrage” The Journal of Financial
Economics Vol. 18, pp.111-126.
Leland Hayne, 1999 “ Beyond mean-variance: Performance measurement in a
nonsymmetrical world” Financial Analysts Journal. Jan/Feb
Malkiel. B , 1995 “ Returns from investing in equity mutual funds 1971 to 1991” Journal
of Finance Vol.L(50) No(2), pp. 549 – 572.
March. P, 1982 “ The choice between equity and debt: An empirical study” Journal of
Finance. Vol. 37, pp. 121-144.
Martin. K , 1996 “ the method of payment in corporate acquisitions, investment
opportunities and managerial ownership” Journal of Finance Vol.51 No.4 , pp. 1227 –
Mitchell, Mark and Pulvino, Todd, 2000 “ Characteristics of Risk in Risk Arbitrage ”
Moore, Keith M, 1999 “Risk Arbitrage: An Investor’s Guide” Wiley
Myer. S, 1984 “ The capital structure puzzle” Journal of Finance Vol. 39, pp. 575 –592.
Myer. S and N. Majiluf, 1984 “ Corporate financing and investment decisions when firms
have information that investor doesn’t have , Journal of Financial Economics Vol.13.,
Pelligrino, Joseph Charles, 1972 “ Causes of Inter-Firm tender offers: An Empirical
study, 1962-1968,” Ph.D Dissertation, Northwestern University
Raad E, R. Ryan and J.F.Sinkey, 1999 “ Leverage , Ownership Structure and Returns to
Shareholders of Target and Bidding firms” Quarterly Journal of Business and Economics,
Vol 38. No.2, pp. 37 –53.
Roll.R , 1986 “ The hubris hypothesis of corporate takeovers” Journal of Business.
Vol59, pp. 197-216.
Samuelson, William and Rosenthal, Leonard, 1986 “ Price Movements as indicators of
tender offer success” The Journal of Finance, Vol. 41, pp. 481-510.
Sanders. Ralph W and John S. Zdanowicz, 1992 “ Target firm abnormal rerturns and
trading volume around the initiation of change in control transactions” Journal of
Financial And Quantitative Analysis Vol 27 No.1
Shleifer, Andrei and Vishny, Robert, 1997 “ The Limit of Arbitrage,” Journal of Finance,
Vol. 52, pp. 35-55.
Sullivan. M.J, M.R. Jensen and C. D Hudson, 1994 “ The Role of Medium of Exchange
in Merger Offers: Examination of Terminated Merger Proposals” Financial Management,
Vol. 23, No(3), pp. 51-62.
Song.M and Ralph. A Walkling, 1993 “ The impact of Managerial Ownership on
Acquisition Attempts and Target Shareholder Wealth” Journal of Financial and
Quantatitive Analysis Vol 28 No.4.
Stulz R M, R A Walkling and M H Song, 1990 “ The distribution of Target Ownership
and Division of Gains in Successful Takeovers” Journal of Finance. Vol 45, pp. 817 –
Suk. D.Y and Sung H. M, 1997 “ The effect of the method of payment and the type of
offer on target returns in merger and tender offer” Financial Review Vol.32 No.3, pp.
Travlos.N.G, 1987 “ Corporate takeover bids, method of payment and bidding firms’
stock return,” Journal of Finance, Vol. XLII, No4, pp. 943 – 963.
Walkling Ralph, 1985 “ Predicting tender offer success: A Logistic Analysis” Journal of
Financial and Quantitative Analysis, Vol. 20(4), pp. 461-478.
Wansley. J.W, William. R.L and H.C Yang, 1983 “Abnormal returns to acquired firms by
type of acquisition and method of payment” Financial Management Vol.12, pp. 16-22.
Summary Table for Literature Reviewed
a) On the Abnormal Returns During a Merger Period
1. Synergy hypothesis.
Authors Subject Data, Model and tested Results & Supporting
Asquith  To test abnormal 1).211 targets and 196 bidders in 1).CER (cumulative excess
returns around an successful mergers and 91 return) during a period from one
announcement date. targets and 89 bidders in day after the press day until two
unsuccessful mergers during days before the outcome day.
1962 to 1976
- Successful target: Positive
2).Market model (daily).
- Successful bidder:
- Unsuccessful target: Negative
- Unsuccessful bidder: Negative.
2) Supporting the synergy
Bradley, Desai To the information 1). 241 successful targets, 112 1). Abnormal returns of target
and Kim  and synergy unsuccessful targets and 94 and bidders on the
hypotheses to explain unsuccessful bidders during announcement date of
the wealth effect of 1963 to 1980 termination.
offers 2). Market model (monthly) - Target: Continuously positive.
3) Synergy and information - Target without the subsequent
hypothese. offer: Decreasing abnormal
- Bidder lost competition:
Bhagat, To test the wealth 1).295 interfirm cash tenders 1).Abnormal returns
Brickley and effect for interfirm offers during 1962 to 1980
Loewenstein cash tender offer Market model (daily) - Target : Positive
2).B/S option model 2).Supporting synergy
hypothesis, not wealth transfer
Bradly, Desai To examine 1). 263 successful tender offer 1). The average synergistic gain
and Kim  synergistic gains to contests during 1963 to 1984 in samples is $117 million
target and acquirer dollar, 7.4% increase in the
stock holders 2). Market model combined wealth of the
stockholders of the target and
3). Dollar synergistic gain (-5 to acquirer
2) Supporting the synergy
4) Weighted least square hypothesis
5). Variables: two periods,
multiple bidders, fraction of
target purchased by bidder
2. Taxation hypothesis in the payment method
Huang and To test the influence 1).204 target firms during 1977 1).The cumulative abnormal
Walkling  of payment, to 1982. return declines 1.8% over the
acquisition form and 50day post announcement
managerial resistance 2).Market model (daily) period.
on the target
abnormal returns 3).Regression 2).A tender offer generates
higher yield than a merger
4).Variables: tender offer,
undisclosed, cash, mixed, 3).Cash offer generates higher
neutral/undisclosed, resistance return.
4) Supporting the taxation
5) Hypotheses: personal tax, hypothesis to explain 3).
compensation effects, agency
effect, regulation effect.
3. Asymmetric information hypothesis in the payment method
Travlos (1987) To explore the 1).167 successful mergers and 1) Abnormal returns.
method of payment in tender offers during 1972 to
explaining the 1981. - Bidder with stock payment:
abnormal return of Negative
bidders 2).Market model and
multivariate regression - Bidder with cash payment:
3).Variables: payment method,
bid premium, relative size of the - Successful bidders with stock
acquisition and type of exchange: Negative during one
acquisition or two days after an
4) Hypotheses: asymmetric
information, taxation and co- 2) Supporting the asymmetric
insurance information hypothesis
Sullivan, Jensen To examine the 1).84 targets and 123 bidding 1).CARs during a period
and Hudson relationship between firms during 1980 to 1988 between a day following the
 the medium of merger announcement and two
exchange and 2).Market model trading days prior to the
valuation effect with termination date.
terminated merger 3).Multivariate regression
proposal - Targets with cash offers have
4).Variables: medium exchange, higher CARs than those with
occurrence of subsequent bid, stock offers.
the party terminating the bid,
occurrence of acquisition - Bidders with cash offers were
program, foothold in the target, found to have higher CARs than
relative size of the acquisition those with stock offers
and presence of competing bid
2).Stock payment is negatively
5) Hypothesis: Synergy, taxation related to the abnormal return
and financing and investment.
hypothesis and synergy
Chang and Suk To examine the 1). 279 failed takeovers during 1) CARs around the termination
 abnormal returns of 1982 to 1990 date.
bidders around the
announcement of 2).Market model - Bidders with the stock
merger termination (- payment: Positive.
1 to 0) and explaining 3).Weighted least square
hypotheses regression - Bidders with cash payment:
- Bidders initiating termination:
5) Variables: Stock offer, Stock Positive.
termination, Stock*Target 2) Supporting the asymmetric
initiated termination, Stock information hypothesis.
offer*other termination, Merger,
size),Multiple bidder, Hostile
bidder, Bidder managerial
ownership, long term
debt/market value of equity,
log(market value of equity)
4. Ownership hypothesis in the payment method
Stulz, Walkling To test relationship 1). 104 successful tender offers 1).If multiple bidders exist, the
and Song between the during 1968 to 1986. target gain increases with target
 distribution of target managerial ownership and
ownership and 2).CAR/Synergistic gains with a decrease with institutional
division of the market model ownership.
3).Multivariate regression 2).The gains to value weighted
portfolio of the bidder and target
4).Variables: market value of the have nothing to do with the
target, market value of the bidder, target ownership distribution.
bidder acquiring percentage,
managerial ownership, institutiona 3) Supporting the ownership
ownership, bidder ownership and hypothesis
5) Hypothesis: Ownership
Song and To examine the 1).112 firms during 1977 to 1).The cumulative abnormal
Walkling impact of managerial 1986. return (-5 to +5) to the target is
. ownership on target higher in successful acquisition
shareholder’s wealth 2).Market model (29.5%) than in unsuccessful
2).The target shareholder returns
4).Variables: Contested, are positively and significantly
successfully acquired, related to managerial ownership
contested*acquired, managerial in contested but successful
ownership, 3) Supporting the ownership
5) Hypothesis: Ownership
Raad, Ryan and To test for the effects 1).81 targets and 81 bidders in 1).Total gains of target shares
Sinkey  of leverage and successful takeovers during 1980 increase with leverage and
ownership structure to 1990 institutional ownership in the
in target firms on target firms.
returns to 2).Market model (Weighted
shareholders of target Average Excess Return –dollar 2).Debt ratios of target firms are
and bidders gains) associated with positive
abnormal returns for target firms
3). Multivariate regression and negative abnormal returns
4).Variables: total dollar gains to
targets and bidders, debt ratio, 3).Institutional ownership in
log(target size), log(managerial targets has positive effects on
ownership) and log(percentage the excess dollar return.
owned by financial institution)
4).Managerial ownership in
target firms has no effect on
5).Size of target firm has
nothing to do with gains
6) Indirectly supporting
5.Regulation (Mode) and Investment opportunities hypothesis in the payment method.
Martin , To examine the 1).846 corporate acquisitions 1).The higher the acquirer’s
examine the underlying motives during 1978 to 1988. growth opportunities, the more
underlying for the payment likely the acquirer is to use stock
motives for the method. 2).A logistic regression analysis to finance an acquisition.
method in 3) To test 7 hypotheses: 2) Only middle range of
acquisition Investment opportunities, Risk ownership is negatively related
sharing, Control, Cash to the probability of stock
availability, Outside monitoring, financing.
Mode of acquisition and
Business cycle hypotheses. 3)The likelihood of stock
financing increases with higher
pre-acquisition market and
acquiring stock returns but
decrease with higher cash
availability, higher institutional
shareholdings and block-
4) Supporting the Mode and
6. Competition hypothesis.
Suk and Sung To re-examine the tax 1).205 successful tender offers 1).Cash offers yield higher
. hypothesis, the during 1974 to 1987. target return(33.9%) than stock
information exchange offers(19.6%).
asymmetry effect 2).Market model with CRSP
hypothesis and equally weighted market index 2).Institutional ownership has
competition nothing to do with the abnormal
hypothesis, 3).Weighted least square return in cash offers
incorporating the regression
institutional 3).Supporting the competition
ownership of the 4) Hypotheses: Tax, Asymmetry expectation hypothesis, which
target firms to information and Competition suggests that the likelihood of
explain the target hypotheses. future competition might be
cumulative abnormal greater in tender offer than in
returns (-5 to 5) 5) Variables: cash payment, mergers
tender offer, two periods,
institutional holding, net
operating loss + unused
investment + foreign tax credit.
Stock payment and depreciation
Larcker and Lys To calculate excess 1). 111 13-D filings during 1977 1). Average excess return for an
 return of firms owned to 1983 arbitrageur is 3.75% during a
by arbitrageurs merger period.
2).Market model (daily).
2). Arbitrageur has superior
Fabozzi, Ferri, To test failed targets’ 1).21 targets in failed tender 1). The average weekly excess
and Tucker weekly returns during offers which don’t receive returns of unsuccessful targets
 an announcement another offer after the failure during that period are not
date to the withdrawn statistically different from zero
date 2).Market model (daily)
Jennings and To examine the 1). 647 acquisitions during 1979 1). The successful acquisitions
Mazeo  structure of initial to 1987 have much higher return to
takeover bids, targets than unsuccessful
competing bid and 2).Equally weighted average of acquisition during an
management the compounded returns announcement date to the date
resistance. of outcome
2). Returns to targets on the
resisted offers are, regardless of
outcomes, higher than those on
the unresisted offers
Walker  To investigate the 1).278 acquisitions during 1980 1).Diversification strategy with
strategic objectives to 1996 potential overlap generated
and stock price negative impact on the bidder
performance of 2).Cumulative market adjusted stock price
acquiring firms return (CAR) and matched firm
around the adjusted return
announcement date (-
5 to +5) 3) Strategies tested: Geographic
expansion, production line,
increase market share, vertical
integration and diversification.
b) On Risk Arbitrage Returns
Duke et al. To examine the 761 1) The average abnormal return
 cash tender offers was 24.6% for 52.4 days,
during 1971 to 1985 corresponding annualized
abnormal return of 171%
Shleifer and To examine 1). The investors’ control over
Vishny  theoretically limits of arbitrageurs’ liquidity produces
arbitrage limitations in taking advantage
of an arbitrage.
Karolyi and To examine the 1) 1.37Canadian acquisitions 1) Risk arbitrage generates
Shannon  profitability of risk with over $50 million during 4.78% in excess of the TSE 300
measured the arbitrage and risk 1997 and multivariate stock index during average 57
return of risk measure. regression analysis days and annualized excess
arbitrage return 33.9%.
dividends, using 2) The spread may be
the 3) Variables: market significantly related to target
capitalization (logarithm), beta, size and pre-announcement run-
price to sale ratio, price to book up (2 week)
ratio, oil & gas dummy, days to
close, cash offer dummy, pre- 3) The return has nothing to do
announcement run-up(2 weeks) with the likelihood of success
and pre-announcement run-up(1 (days to close), target size, beta,
year) price to sale ratio, price to book
ratio, payment method, pre-
announcement run-up or
Jindra and To test profitability 1)362 cash tender offers in 1) An arbitrageur was found to
Walkling  of risk arbitrage and which a bidder looks for 100% earn an excess return of 1.42 to
measured the determinants to the of target shares and the 1.54% or an annualized return of
excess return of initial spread transaction value exceeds $10 102 to 115%, if she or he takes a
risk arbitrage million during 1981 to 1995 long position on a target during
without one week following the
dividends, using 2) Multivariate regression announcement.
a sample of
3) Variables: Log (market 2) An arbitrageur buying the
capitalization), ownership, target and shorting the acquirer
friendly acquisition, hostile during one week following the
acquisition, blockholders, announcement earned an excess
premium, toeholders, attitude, return of 1.88% or the
rumor, run-up, abnormal volume corresponding annualized return
growth rate, option on target, of 156%.
experienced bidder and multi- 3) The arbitrage spread8 is found
financial advisors to be positively related to the
size of bid premium, friendly
managerial attitude about the
offer and existence of rumors
about the offer but negatively
related to the target size and pre-
offer run up.
4) The managerial ownership is
found to be only significant in
hostile takeover and bidder’s
acquisition experience to be
5) The spread is positively
related to the duration of the
offer and negatively related to
the revision of the offer.
Mitchell and To examine the risk 1).4750 stock swap mergers, 1).Risk arbitrage generated the
Pulvino  of risk arbitrage, cash mergers and cash tender annual excess return of 4%.
using a contingent offers during 1963 to 1998 and a
approach. contingent approach 2).Return is correlated with
market return only during
2).Piecewise linear regression market downs
The locked-up initial spread refers to the price difference between the offered price and the actual market
price on the announcement date. Here, however, we start with the spread on the day after the
Taxation was researched in Dertouzos and Thorpe . They find that the increase of depreciable
assets tended to lead to the bidding competition.
These hypotheses related to the payment method were well summarized in Martin . We shall
follow his hypothesis classification in this review article.
They followed Lakonishok and Vermaelen  and Schwert  to examine the abnormal trading
volume for the targets around the tender offer announcements.
It was defined as the percentage difference between the initial bid price and the target’s closing price after
the acquisition announcement
Their transaction costs are calculated, using brokerage commissions and the price impact associated with
trading illiquid securities.
Price impact model from Breen et al.  was used.
It was defined as the percentage difference between the initial bid price and the target’s closing price after
the acquisition announcement