Proceedings of 4th Global Business and Finance Research Conference
25 - 27 May 2015, Marriott Hotel, Melbourne, Australia
ISBN: 978-1-922069-76-4
Merger Means of Payment and Analyst Recommendation
Change
Yiling Zhang*
We find a strong evidence that compared to pure stock deal in merger and acquisition
(M&A), cash only deal is more likely to lead analysts upgrade their recommendations over
the acquirer stocks within 90 days window of deal announcement date. An event study
within three days window of deal announcement date in the M&A context allows us to
disentangle merger means of payment impact on short term abnormal return of acquirer
stocks from other impacts. We find 1.06%(-1.05%) cumulative abnormal return for the
acquirer stocks of cash only (Pure stock) deals during this time frame. Our findings extend
the merger means of payment hypothesis, suggesting compared to pure stock deals, cash
only deal in a short term will receive more favorableness from analysts to upgrade their
recommendations about the acquirer stocks. Market immediately reacts to this difference
and result in a difference of cumulative abnormal return about acquirer stocks.
Track: Finance
JEL Codes: G34, G14
1. Introduction
Broad literature has done the research on the merger means of payment long term impact
on the cross sectional stock return for the acquirer. Loughran and Vijh(1997) find that with
a cash tender offer merger deal, the acquirer is able to earn a significant positive long run
abnormal return post the merger transaction. But with a stock only merger, the acquirer
earns a significant negative long run abnormal return post the merger transaction. Rau
and Vermaelen(1998) as well as Agrawal and support Loughran and Vijh’s view by
finding the same patterns of returns for acquirer stocks in cash tender offer merger deal
and stock only merger deal after controlling for the size and book-to-market factors as
suggested by Fama and French (1992). In addition, Shleifer and Vishny (2003)
developed a simple model of acquisition to support the empirical evidence listed by
previous scholars that long run returns to acquirers are negative in stock acquisitions and
positive in cash acquisitions. Furthermore, they come up with the means of payment
hypothesis, which states that if acquirer firms’ managers are better informed about the
target’s prospects than the market, managers acquire the target with only stock when the
acquirer stock price is overpriced from a long run perspective and managers will acquire
the target with only cash when the acquirer stock price is underpriced from a long run
perspective. This hypothesis indicates why the stock only merger earns the acquirer a
negative abnormal return in the long run but the cash only merger earns the acquirer a
positive abnormal return in the long run.
______________________________
*Mr. Yiling Zhang, Department of Finance and Real Estate, University of Texas at Arlington, USA.
Email Address: yiling.zhang@mavs.uta.edu
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Proceedings of 4th Global Business and Finance Research Conference
25 - 27 May 2015, Marriott Hotel, Melbourne, Australia
ISBN: 978-1-922069-76-4
As we have seen that merger means of payment have significant impact on the acquirer
stock abnormal return over the long run, would analyst recommendation change about
acquirer stocks react differently to various merger means of payment within a short term
of deal announcement and would market reacts to this short term analyst
recommendation change difference, finally resulting in a difference of cumulative
abnormal return for acquirer stocks for various merger means of payment? This question
is a very important empirical research question. First, because most prior studies, such
as Loughran and Vijh(1997), Jaffee et al. (2001) and Savor et al. (2009), focused on the
merger means of payment play an important role in explaining the long run abnormal
return for the acquirer stock and few literature interpret the merger means of payment
impact on acquirer stocks’ short run abnormal return. This paper complements this field
of research. Second, because this question helps us understand merger means of
payment impact on analyst recommendation change. Our examination of the
informativeness of merger means of payment contributes to extant research on the
information content of analyst’s stock recommendation.
The major contribution of this paper lies in our answer to the research question above,
firstly our answer provides a good extension to the merger means of payment hypothesis
by Shleifer and Vishny (2003). Merger means of payment hypothesis predicts that cash
only deal delivers a positive long run abnormal return and negative long run abnormal
return for acquirer stocks. Our extension lies in that compared to pure stock deals, cash
only deal in a short term will receive more favorableness from analysts to upgrade their
recommendations about the acquirer stocks. Market immediately reacts to this difference
and result in a significant positive cumulative abnormal return for acquirer stocks of cash
only deal and a significant negative cumulative abnormal return for acquirer stocks of pure
stock deal. Second, our empirical finding complements Mitchel et al. (2004). They find
that merger arbitrage short selling causes short run downward price pressure for acquirer
in stock financed mergers around deal announcement period. our finding shows that cash
only deal’s impact on analyst recommendation change over acquirer stock is translated
into 1.06% cumulative abnormal return for the acquirer stock during the three days
window of the deal announcement, suggesting analyst recommendation change because
of cash only impact create an upward price pressure.
2. Data and Variable Descriptions
M & A Deals
We obtain U.S. domestic M&A transaction data from Securities Data Corporation (SDC)
Platinum for years 1993 to 2013. Our sample is only consisted of statutory mergers and
acquisitions of assets. We include cash only, stock only and cash & stock combination
completed unconditional deals in our sample. We exclude from our sample buybacks,
acquisitions of certain assets, acquisitions of partial interest, recapitalizations, spin-offs,
split-offs, exchange offers and acquisitions of remaining interest. We require target and
acquirer are both public trading companies and at least one advisor has been retained by
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Proceedings of 4th Global Business and Finance Research Conference
25 - 27 May 2015, Marriott Hotel, Melbourne, Australia
ISBN: 978-1-922069-76-4
the target or the acquirer. Finally, to make sure the merger and acquisition is a significant
deal, we exclude that those deals that its target market value is less than 5% of combined
acquirer and target market value. After applying all these criteria, we are left with 11,863
deals.
Merging deals with CRSP
To obtain the full 9 digit cusip codes for the acquirer stocks, we start to obtain 6,973
unique acquirer 6 digit Ncusip codes from those 11,863 deals in SDC platinum database.
Then use those unique Ncusip codes to merge with the CRSP monthly stock entire
database which dated from December 1925 to December 2013. From this step above,
we can obtain 3,594 unique full 9 digit acquirer stocks cusip codes which cover the 8,071
out of original 11,863 deals.
Merging deals with analyst recommendation changes
We upload those 3,594 unique full cusip codes into the I/B/E/S recommendation detail
database, select the database period from December 1992 to June 2014, we are left
2,751 unique full acquirer stock cusip codes which cover 5,978 out of original 11,863
deals. We are emphasizing on the analyst recommendation change instead of
recommendation levels because Womack (1996) suggested the analyst recommendation
change is economic meaningful. For each analyst, we obtain all available current analyst
recommendation scores (ranged from 1 to 5, 1 indicates strong buy and 5 indicates strong
sell) about acquirers issued within + 90 days of the M&A deal announcement date and
take the average of those scores for the current analyst recommendation score. Then,
we obtain last available recommendation scores issued within -90 days of the M&A deal
announcement date and take the average of those scores for the last analyst
recommendation score. We define a dummy variable, Upgrade, and set it equal to 1 if the
current recommendation score is less than last recommendation score improved and 0 if
current recommendation score is greater or equal to last recommendation score. We
cannot compute Upgrade variable if the we are lack of last analyst recommendation score,
then we discard this observation from the sample due to lack of last analyst
recommendation score. The above criteria leaves 5,978 deals in the sample of
recommendation changes.
Merging deals with analyst forecasts
We upload those 2751 unique full acquirer stock cusip codes in the previous step into
I/B/E/S detail history database and select the entire database period from January 1970
to June 2014, we choose the observations with long term growth forecast. This criteria
leaves us only 1541 unique full acquirer stock cusip codes which covers 4,028 out of
11,863 original deals. We focus on analysts long term growth forecasts because lin
and McNichols (1998) indicated analysts long term growth forecasts plays an important
role in influencing on the investment recommendation.
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Proceedings of 4th Global Business and Finance Research Conference
25 - 27 May 2015, Marriott Hotel, Melbourne, Australia
ISBN: 978-1-922069-76-4
M & A descriptive statistics
Table 1 presents descriptive statistics on the value and number of the M&A deals from
year 1993 to year 2013 in the full sample as described in I A. We define the VALUE as
the total nominal amount of consideration paid by the acquirer. Those deals are
categorized into three methods of payment: Cash only, pure stock and Mixed. The mixed
subset includes all the acquisitions in which payment is stock and cash combination. We
tend to see that stock deals are usually larger in size than Cash only deals. The number
of cash only deals is greater than that of stocks financed deals.
Table 1 Descriptive statistics on deal value (billions of dollars)
N
Cash only 6584
Stock
3025
Mixed
2254
Mean
0.38
0.87
1.23
Std Dev
Min
25% Pctl
1.22 0.0008 0.0318
5.27 0.0004 0.0281
4.67 0.0002 0.0383
Median 75%Pctl
Max
0.1000 0.2950
41.0050
0.0785 0.2869 164.7240
0.1370 0.6149
72.6710
Table 2 presents the descriptive statistics on the number of acquisitions by calendar year.
The sample consists of 11,863 U.S. domestic completed deals described as in the section
I A. Panel A describes the number of acquisitions and aggregate value of all deals by
calendar year. Panel B describes the mean deal value of Categorized payments (cash
only, stocks and mixed) deals by calendar year.
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Proceedings of 4th Global Business and Finance Research Conference
25 - 27 May 2015, Marriott Hotel, Melbourne, Australia
ISBN: 978-1-922069-76-4
Table 2 Panel A: Number of Acquisitions by Calendar Year
Year
Number of
Number of
Number of
Aggregate value
Total
number of
Cash deals
Stock deals
Mixed deals of all deals (billions $) all deals
1993
204
136
59
94.3
399
1994
235
250
91
137.7
576
1995
259
259
81
204.8
599
1996
293
267
116
285.4
676
1997
344
367
192
475.2
903
1998
333
382
157
854.3
872
1999
306
337
155
748.8
798
2000
293
327
141
836.7
761
2001
279
150
139
396.4
568
2002
306
63
114
188.4
483
2003
383
56
97
225.9
536
2004
355
67
102
326.7
524
2005
377
58
135
499.5
570
2006
454
49
142
465.9
645
2007
395
44
110
335.4
549
2008
271
30
73
308.6
374
2009
210
49
58
334.2
317
2010
334
34
60
275.6
428
2011
326
38
61
343.3
425
2012
333
30
87
242.8
450
2013
294
32
84
300.0
410
Total
6584
3025
2254
7879.9
11863
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Proceedings of 4th Global Business and Finance Research Conference
25 - 27 May 2015, Marriott Hotel, Melbourne, Australia
ISBN: 978-1-922069-76-4
Panel B: Mean Deal Value of Categorized Payments by Calendar Year (billions $)
Year
of
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Mean value of
Cash deals
0.118
0.285
0.220
0.243
0.326
0.322
0.384
0.382
0.309
0.236
0.241
0.445
0.361
0.398
0.542
0.629
0.332
0.441
0.537
0.431
0.668
Mean value of
Stock deals
0.257
0.159
0.423
0.470
0.525
1.308
0.968
1.541
0.676
1.307
1.320
1.917
1.658
1.659
0.508
2.594
0.448
1.181
0.884
0.594
0.797
Mean value
Mixed deals
0.596
0.340
0.473
0.765
0.888
1.576
1.968
1.567
1.502
0.298
0.617
0.747
1.979
1.436
0.899
0.828
4.181
1.471
2.205
0.937
0.931
Descriptive Statistics on Analyst Recommendation and Forecast
Because we are more interesting to see whether cash only deal has more favorableness
over pure stocks in analyst recommendation upgrade within the 90 days window of deal
announcement date as described in the section I C, we exclude the mixed subsample in
our final sample described in the section ID. Table 3 presents the analyst
recommendation change on our final sample, we present analyst recommendation
change on our final cash only subsample and pure stock subsample in this table.
Table 3 Descriptive statistics on analyst recommendation change
N
Final sample 25,601
Cash Only
16,133
Stocks
9,441
% Upgrade
35.03%
35.97%
33.39%
%Flat
32.07%
30.38%
35.01%
%Downgrade
32.90%
33.65%
31.63%
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Proceedings of 4th Global Business and Finance Research Conference
25 - 27 May 2015, Marriott Hotel, Melbourne, Australia
ISBN: 978-1-922069-76-4
3. Probit Analysis of Analyst Recommendation Change
In this section, we use probit model to analyze short term dynamic link between merger
means of payment and analyst recommendation changes over the acquirer stocks around
the M&A deal announcement date. We use the probit analysis instead of ordinary least
squares regression because recommendation changes are discrete and ordinal. In all
cases, we compute standard errors by clustering on calendar month to ensure the
robustness to heteroscedasticity and make sure there exists arbitrary cross sectional and
intra month serial correlation error.
our first probit model tests whether cash only deal are more likely than pure stock deals
to lead analysts to upgrade their recommendations about the acquirer stocks, as opposed
to downgrade their recommendations about them or leaving their recommendations
unchanged.
Our first null hypothesis is that compared to pure stock deal, cash only deal will more
likely lead the analysts to immediately leave their recommendations about the acquirer
stocks unchanged or downgrade their recommendation about the acquirer stocks within
90 days window of the deal announcement date. According to Kolasinski and Kothari
(2008), variables deal value, days between analyst recommendation change date and
deal announcement date, analysts experience covering stocks, and market size for the
acquirer stocks are key controlled variables for the analyst recommendation change.
According to Luo et al. (2010), analyst’s previous recommendations dispersion has
played an important role in influencing on the analyst recommendation changes.
Combining the key controlled variables from the analyst recommendation change
literatures, we have come up with the probit model as the following model M (1)
𝑝(𝑢𝑝𝑔𝑟𝑎𝑑𝑒)𝑖 = 𝛽0 + 𝛽1 × 𝐷𝑖 + 𝛽2 × ln⁡(𝑉𝑎𝑙𝑢𝑒𝑖 ) + 𝛽3 × ln⁡(𝑝𝑟𝑒𝑑𝑖𝑠𝑝𝑒𝑟𝑠𝑖𝑜𝑛𝑗 ) + 𝛽4 ×
ln⁡(𝑆𝑖𝑧𝑒𝑖 ) + 𝛽5 × ln⁡(𝐸𝑥𝑝𝑒𝑟𝑖𝑒𝑛𝑐𝑒𝑗 ) + 𝛽6 × ln⁡(𝐹𝑜𝑙𝑙𝑜𝑤𝑖𝑛𝑔𝑗 ) + 𝛽7 × ln⁡(𝐷𝑎𝑦𝑠𝑗 ) + 𝜀𝑖 …M (1)
Variable Upgrade is a variable that takes on one of two values: 1 if the analyst upgrade
the acquirer stock 0 if the analyst downgrade or leave the recommendation unchanged.
The process of determining value of Upgrade is described in the section I C. 𝐷𝑖 is a
dummy variable for the acquirer stock i on deal announcement date if the merger deal is
paid by cash only, then 𝐷𝑖 = 1, otherwise𝐷𝑖 =0. 𝑉𝑎𝑙𝑢𝑒𝑖 is the total nominal consideration
the acquirer i paid for the transaction, including all cash, securities, and assumed debt on
deal announcement date. ⁡𝑝𝑟𝑒𝑑𝑖𝑠𝑝𝑒𝑟𝑠𝑖𝑜𝑛𝑗 measures the analyst j ‘s recommendation
dispersion about the acquirer stock within -90 days of deal announcement date. 𝑆𝑖𝑧𝑒𝑖
values the nominal market capitalization of the acquirer i on deal announcement date.
𝐸𝑥𝑝𝑒𝑟𝑖𝑒𝑛𝑐𝑒𝑗 is the number of years between the deal announcement date and the analyst
j’s first recommendation date in I/B/E/S;⁡𝐹𝑜𝑙𝑙𝑜𝑤𝑖𝑛𝑔𝑗 is the number of analysts j either
recommending or issuing forecast about the acquirer in the same calendar month as deal
announcement month. 𝐷𝑎𝑦𝑠𝑗 is number of days between the date of the first
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Proceedings of 4th Global Business and Finance Research Conference
25 - 27 May 2015, Marriott Hotel, Melbourne, Australia
ISBN: 978-1-922069-76-4
recommendation date after deal announcement and an deal announcement date and 𝜀𝑖 ⁡is
the cross sectional error term. Table 4 provides the descriptive statistics as well as the on
the variable definitions.
Table 4: Variable Definitions and Descriptive statistics
Upgrade
1 if the analyst upgrade the acquirer stock 0 if the analyst
downgrade or leave the recommendation unchanged. Used as an
dependent variable in model M(1) and table 5.
𝐷𝑖
Indicates whether deal is cash only deal or pure stock deal.
𝑉𝑎𝑙𝑢𝑒𝑖
Total nominal consideration the acquirer i paid for the transaction.
𝑝𝑟𝑒𝑑𝑖𝑠𝑝𝑒𝑟𝑠𝑖𝑜𝑛𝑗 Analyst j ‘s recommendation dispersion about the acquirer stock
⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡ within -90 days of deal announcement date.
𝑆𝑖𝑧𝑒𝑖
Nominal market capitalization of the acquirer i on deal
announcement date.
𝐸𝑥𝑝𝑒𝑟𝑖𝑒𝑛𝑐𝑒𝑗
Number of years between the deal announcement date and the
analyst j’s first recommendation date in I/B/E/S.
𝐹𝑜𝑙𝑙𝑜𝑤𝑖𝑛𝑔𝑗 Number of analysts j either recommending or issuing forecast about
the acquirer in the same deal announcement calendar month.
𝐷𝑎𝑦𝑠𝑗
Number of days between the first recommendation date
after deal announcement and an deal announcement date
Mean
Upgrade
𝐷𝑖
ln⁡(𝑉𝑎𝑙𝑢𝑒𝑖 )
0.350
0.631
5.648
ln⁡(𝑝𝑟𝑒𝑑𝑖𝑠𝑝𝑒𝑟𝑠𝑖𝑜𝑛𝑗 ) -0.233
ln⁡(𝑆𝑖𝑧𝑒𝑖 )
16.543
ln⁡(𝐸𝑥𝑝𝑒𝑟𝑖𝑒𝑛𝑐𝑒𝑗 ) 7.125
ln⁡(𝐹𝑜𝑙𝑙𝑜𝑤𝑖𝑛𝑔𝑗 ) 3.634
ln⁡(𝐷𝑎𝑦𝑠𝑗 )
3.229
Std Dev Min
0.477
0.483
1.661
0.181
1.825
1.061
1.061
1.031
25% Pctl
0.000
0.000
0.000 0.000
-2.590 4.544
-1.903
-0.306
10.731 15.204
1.099
6.494
0.000
2.944
0.000
2.639
Median 75%Pctl
0.000
1.000
5.561
-0.235
16.634
7.286
3.829
3.526
Max
1.000
1.000
1.000
1.000
6.798
11.398
-0.132
1.039
18.110 20.025
7.964
8.907
4.554
4.984
4.060
4.499
Table 5 presents the results for M(1) model. We model the probability that an analyst will
upgrade the acquirer stock recommendation within 90 days window of the deal
announcement date as a function of the merger means of payment and other controlled
variables exhibited in table 4.
Table 5: Merger means of payment on Analyst Recommendation Change
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Proceedings of 4th Global Business and Finance Research Conference
25 - 27 May 2015, Marriott Hotel, Melbourne, Australia
ISBN: 978-1-922069-76-4
(Dependent Variable: 𝑝(𝑢𝑝𝑔𝑟𝑎𝑑𝑒)𝑖 )
Constant
0.2433
(6.21)***
𝐷𝑖
0.0199
(2.85)***
ln⁡(𝑉𝑎𝑙𝑢𝑒𝑖 )
0.0049
(2.22)**
ln⁡(𝑝𝑟𝑒𝑑𝑖𝑠𝑝𝑒𝑟𝑠𝑖𝑜𝑛𝑗 )
-0.0997
(-5.60)***
ln⁡(𝑆𝑖𝑧𝑒𝑖 )
-0.0048
(-1.87)*
ln⁡(𝐸𝑥𝑝𝑒𝑟𝑖𝑒𝑛𝑐𝑒𝑗 )
0.0227
(7.43)***
ln⁡(𝐹𝑜𝑙𝑙𝑜𝑤𝑖𝑛𝑔𝑗 )
0.0142
(3.43)***
ln⁡(𝐷𝑎𝑦𝑠𝑗 )
-0.0221
(-6.96)***
Notes: *** indicates standard error is significant at 1% significance level
** indicates standard error is significant at 5% significance level
*indicates standard error is significant at 10% significance level
Table 5 shows that compared to pure stock deals, the cash only deals will have 2% more
chance to lead analysts to upgrade their recommendations about acquirer stocks within
90 days of deal announcement date. This strongly indicates that merger means of
payment has a significant impact on the analyst recommendation change within 90 days
of deal announcement date. We see cash only deal gains more favorableness than pure
stocks deal over the analyst recommendation upgrade about the acquirer stocks.
According to Kolasinski and Kothari (2008), analyst recommendation change is sensitive
to the length of the time between deal announcement date and the analyst’s first
recommendation after the deal announcement date. It is very interesting to examine day
length impact, cash dummy impact and their interaction impact on the analyst
recommendation change. Therefore, we carry out the M(2) model to examine those
impacts. M(2) model is identical to M(1) model except M(2) model includes the day
dummy and interaction between daydummy and cash dummy.
𝑝(𝑢𝑝𝑔𝑟𝑎𝑑𝑒)𝑖 = 𝛽0 + 𝛽1 × 𝐷𝑎𝑦𝑑𝑢𝑚𝑚𝑦𝑖 + 𝛽2 × 𝐷𝑖 + 𝛽3 × (𝐷𝑖 × 𝐷𝑎𝑦𝑑𝑢𝑚𝑚𝑦𝑖 ) + 𝛽4 ×
ln⁡(𝑉𝑎𝑙𝑢𝑒𝑖 ) + 𝛽5 × ln⁡(𝑝𝑟𝑒𝑑𝑖𝑠𝑝𝑒𝑟𝑠𝑖𝑜𝑛𝑖 ) + 𝛽6 × ln⁡(𝑆𝑖𝑧𝑒𝑖 ) + 𝛽7 × ln⁡(𝐸𝑥𝑝𝑒𝑟𝑖𝑒𝑛𝑐𝑒𝑗 ) + 𝛽8 ×
ln⁡(𝐹𝑜𝑙𝑙𝑜𝑤𝑖𝑛𝑔𝑗 ) + 𝜀𝑖 …M (2)
We define daydummy in two cases. In a 7 day case, we require daydummy=1 if 𝐷𝑎𝑦𝑠𝑗 ≤
7, otherwise daydummy=0. In a 30 day case, we require daydummy=1 if 𝐷𝑎𝑦𝑠𝑗 ≤ 30,
otherwise daydummy=0. All other variables are defined in the table 5.
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Proceedings of 4th Global Business and Finance Research Conference
25 - 27 May 2015, Marriott Hotel, Melbourne, Australia
ISBN: 978-1-922069-76-4
As table 6 shows the impact of cash only deal on analyst recommendation change is
sensitive to the length of time between the first recommendation date after deal
announcement and its deal announcement date.
Table 6 days length impact on Analyst Recommendation Change
(Dependent Variable: 𝑝(𝑢𝑝𝑔𝑟𝑎𝑑𝑒)𝑖 )
7days
30days
Constant
𝐷𝑖
𝐷𝑎𝑦𝑑𝑢𝑚𝑚𝑦𝑖
𝐷𝑎𝑦𝑑𝑢𝑚𝑚𝑦𝑖 × 𝐷𝑖
ln⁡(𝑉𝑎𝑙𝑢𝑒𝑖 )
ln⁡(𝑝𝑟𝑒𝑑𝑖𝑠𝑝𝑒𝑟𝑠𝑖𝑜𝑛𝑗 )
ln⁡(𝑆𝑖𝑧𝑒𝑖 )
ln⁡(𝐸𝑥𝑝𝑒𝑟𝑖𝑒𝑛𝑐𝑒𝑗 )
ln⁡(𝐹𝑜𝑙𝑙𝑜𝑤𝑖𝑛𝑔𝑗 )
0.1255
(3.46)***
0.0157
(2.09)**
0.0152
(1.16)
0.0313
(1.87)**
0.0041
(1.91)*
-0.1114
(-6.33)***
-0.0031
(-1.22)
0.0250
(8.36)***
0.0145
(3.61)***
0.121
(3.32)***
0.0083
(0.89)
0.0346
(3.32)***
0.0274
(2.10)**
0.0041
(1.90)*
-0.1112
(-6.30)***
-0.0019
(-0.77)
0.0243
(8.15)***
0.0114
(2.81)***
According to Loh and Stulz(2011), recommendation changes are more likely to be
influential when experiencing a high forecast dispersion firm. Therefore, it is interesting
to examine the previous dispersion impact, cash dummy impact and their interaction
impact on the analyst recommendation change. Therefore, we carry out the M(3) model
to examine those impacts. M(3) model is identical to M(1) model except M(3) model
includes the predispersiondummy and interaction between predispersion dummy and
cash dummy.
𝑝(𝑢𝑝𝑔𝑟𝑎𝑑𝑒)𝑖 = 𝛽0 + 𝛽1 × 𝑝𝑟𝑒𝑣𝑖𝑜𝑢𝑠𝑑𝑖𝑠𝑝𝑒𝑟𝑠𝑖𝑜𝑛𝑑𝑢𝑚𝑚𝑦𝑖 + 𝛽2 × 𝐷𝑖 + 𝛽3 × (𝐷𝑖 ×
𝐷𝑎𝑦𝑑𝑢𝑚𝑚𝑦𝑖 ) + 𝛽4 × ln⁡(𝑉𝑎𝑙𝑢𝑒𝑖 ) + 𝛽5 × ln⁡(𝑝𝑟𝑒𝑑𝑖𝑠𝑝𝑒𝑟𝑠𝑖𝑜𝑛𝑖 ) + 𝛽6 × ln⁡(𝑆𝑖𝑧𝑒𝑖 ) + 𝛽7 ×
ln⁡(𝐸𝑥𝑝𝑒𝑟𝑖𝑒𝑛𝑐𝑒𝑗 ) + 𝛽8 × ln⁡(𝐹𝑜𝑙𝑙𝑜𝑤𝑖𝑛𝑔𝑗 ) + 𝜀𝑖 …M (3)
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Proceedings of 4th Global Business and Finance Research Conference
25 - 27 May 2015, Marriott Hotel, Melbourne, Australia
ISBN: 978-1-922069-76-4
According to Jegadeesh and Kim (2009), 0.75 is a roughly the average dispersion in a
general sample. Therefore, we define predispersiondummy=1 if 𝑝𝑟𝑒𝑑𝑖𝑠𝑝𝑒𝑟𝑠𝑖𝑜𝑛𝑗 > 0.75,
otherwise predispersiondummy =0.
Table 7 presents analyst previous dispersion impact on analyst recommendation change.
As table 7 shows that the pure stock deal group with their analyst previous dispersion
within -90 days of deal announcement date greater than 0.75 will have 3.16% negative
impact on analyst recommendation change. This indicates that for pure stock deals,
analysts are less likely to upgrade the recommendation about the acquirer stocks when
there was above average dispersion across the analyst opinions. This is consistent with
Jegadeesh and Kim (2009)’s finding that analysts are less likely to herd when there is a
large dispersion across analysts’ opinion. In addition, the impact of cash dummy variable
on analyst recommendation change is 5.08%-4.69%×predispersiondummy. In this case,
we can see as the predispersiondummy varies from 0 to 1, impact of cash dummy on
analyst recommendation change varies from 5.08% to 0.39%. Therefore, the impact of
cash only deal on analyst recommendation change is sensitive to the previous analyst
recommendation dispersion about the acquirer stocks within -90 days of deal
announcement date.
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Proceedings of 4th Global Business and Finance Research Conference
25 - 27 May 2015, Marriott Hotel, Melbourne, Australia
ISBN: 978-1-922069-76-4
Table 7 days Analysts Previous Dispersion Impact on Analyst Recommendation Change
(Dependent Variable: 𝑝(𝑢𝑝𝑔𝑟𝑎𝑑𝑒)𝑖 )
Constant
0.3088
(7.79)***
𝐷𝑖
0.0508
(4.17)***
𝑝𝑟𝑒𝑑𝑖𝑠𝑝𝑒𝑟𝑠𝑖𝑜𝑛𝑑𝑢𝑚𝑚𝑦𝑖
-0.0316
(-2.73)***
𝑝𝑟𝑒𝑑𝑖𝑠𝑝𝑒𝑟𝑠𝑖𝑜𝑛𝑑𝑢𝑚𝑚𝑦𝑖 × 𝐷𝑖
-0.0469
(-3.23)***
ln⁡(𝑉𝑎𝑙𝑢𝑒𝑖 )
0.0048
(2.19)**
ln⁡(𝑆𝑖𝑧𝑒𝑖 )
-0.0059
(-2.29)**
ln⁡(𝐸𝑥𝑝𝑒𝑟𝑖𝑒𝑛𝑐𝑒𝑗 )
0.0222
(7.28)***
ln⁡(𝐹𝑜𝑙𝑙𝑜𝑤𝑖𝑛𝑔𝑗 )
0.0166
(4.00)***
ln⁡(𝑑𝑎𝑦𝑠𝑗 )
-0.0234
(-7.40)***
4. Event Study and Instrumental Analysis of Cumulative Abnormal
Return
As table 5 show us that within 90 days of deal announcement date, cash only deal will
have a higher chance than pure stocks to lead analysts to upgrade their
recommendations about acquirer stocks We are interesting to examine whether this
recommendation change difference is caused by different merger means of payment will
be reflected in a short term market reaction. Therefore, we conduct an event study to
examine the short term cumulative abnormal return of cash only deal and that of pure
stock deal separately within three days window of deal announcement.
To better measure the short term abnormal return, we employ the common technique of
calculating cumulative abnormal return relative to a beta benchmark. To calculate
abnormal returns based on market beta, we use the procedures documented in Boehmer
et al (2002, P44). According to Mitchel et al. (2004), to disentangle price pressure and
information effects, we will use 3 day cumulative abnormal return around deal
announcement date t. To be consistent with Mitchel et al. (2004), market model
parameters are estimated over a 150 day window beginning 21 days after deal
announcement date, where value weighted CRSP included dividends index proxies for
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Proceedings of 4th Global Business and Finance Research Conference
25 - 27 May 2015, Marriott Hotel, Melbourne, Australia
ISBN: 978-1-922069-76-4
market portfolio. After a deal announcement date for acquirer stock I, we compute 3 day
buy-and-hold abnormal returns ABRi (t-1, t +1) as model M(4)
𝑡+1
𝑡+171
𝐴𝐵𝑅𝑖 (𝑡 − 1, 𝑡 + 1) = ∏ (1 + 𝑅𝑖,𝜏 ) − ∏ (1 + 𝑅𝑚,𝜏 )
𝜏=𝑡−1
𝜏=𝑡+21
𝐶𝐴𝑅𝑖 (𝑡 − 1, 𝑡 + 1) = ∑𝑡+1
𝑡−1 𝑎𝑣𝑒𝑟𝑎𝑔𝑒(𝐴𝐵𝑅𝑖 )....M (4)
Where 𝑅𝑖,𝜏 and 𝑅𝑚,𝜏 are the return on acquirer stock i and the value-weighted index return,
respectively.
We choose the [-1 1] or from one day prior to one day after deal announcement date for
the event window. We choose the [21 171] or from 21 days to 171 days after deal
announcement date as our market estimation window. Market portfolio returns are
collected from value weighted CRSP included dividends index proxies returns from CRSP.
These returns within [21 171] are then used as benchmarks to calculate the abnormal
performance. Abnormal returns are calculated for each firm relative to its beta benchmark
in [-1 1] time frame. Cumulative abnormal returns are calculated by averaging across
acquirer firms every day and then summing those averages over time.
Table 8 reports cumulative abnormal returns for cash only deal and pure stock deal within
3 days window of deal announcement date [-1 1]. 3 days window can disentangle merger
means of payment impact on short term abnormal return of acquirer stocks from other
impacts. As presented in table 8, we can clearly see cash only deal delivers a significant
positive cumulative abnormal return or 1.06% for acquirer stocks and pure stock deal
delivers a significant negative cumulative abnormal return or -1.05% for acquirer stocks.
This cumulative abnormal return difference reflect market prefers a cash only deal to a
pure stock deal during short time after the deal announcement. But would their respective
abnormal return explained by the analyst recommendation change? If find the answer is
yes, then we can see merger means of payment impact on analyst recommendation
change will be translated into a short term abnormal return for acquirer stocks.
Table 8 Cumulative Abnormal Returns for Cash Only and Stocks Deals
Period
[−1⁡1]
Cash only
(N=2,700)
1.06%
(8.97)***
Stocks
(N=1,213)
-1.05%
(-3.84)***
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Proceedings of 4th Global Business and Finance Research Conference
25 - 27 May 2015, Marriott Hotel, Melbourne, Australia
ISBN: 978-1-922069-76-4
5. Summary and Conclusions
We find that compared to pure stock deals, cash only deal will receive more favorableness
from analysts to upgrade their recommendations about the acquirer stocks within 90 days
window of deal announcement date. In particular, compared to pure stock deals, the cash
only deals will have 2% more chance to lead analysts to upgrade their recommendations
about acquirer stocks within 90 days of deal announcement date. In addition, we find that
the impact of cash only deal on analyst recommendation change is sensitive to the length
of time between the first recommendation date after deal announcement and its deal
announcement date. The impact of cash only deal on analyst recommendation change is
sensitive to the previous analyst recommendation dispersion about the acquirer stocks
within -90 days of deal announcement date.
We also find that analyst recommendation change will have a significant positive impact
on the short term cumulative abnormal return for the acquirer stocks within 3 days of deal
announcement date. As event study enables us to show that cash only deal delivers a
significant positive cumulative abnormal return or 1.06% for acquirer stocks and pure
stock deal delivers a significant negative cumulative abnormal return or -1.05% for
acquirer stocks.
Our key results above indicate that merger means of payment has a direct impact on
analyst recommendation change and market immediately reacts to this impact, resulting
different cumulative abnormal returns for acquirer stocks by various merger means of
payment.
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