5. Contenidos
5.1. Fases para construir una marca
2.3.1 Methodology
In order to throw light on the role played by active investors, or to be more precise, on the role that markets believe these investors have, I evaluate the effect of the stake acquisition on the market value of the target company. To this end, I provide evidence mainly based on event studies. As it is widely known, such a methodology allows to measure the effect of an event on the value of the firm.
I report results over several time intervals: [-1,0], [-30,1], [-30,5], [-30,10], [-30,30], [-30,100], [-10,-2]. The event window [-1,0] stems from the fact that some announcement data are from daily newspapers. Daily newspapers report the purchase the day after the news is released. Since it is possible that at least some market participants are able to get information about the deal before the public announcement, event windows starting from day t = −30 are also used. Both Bethel, Liebeskind, and Opler (1998) and Banerjee, Leleux, and Vermaelen (1997) use an event window starting from day t = −30. These event windows take into consideration the possibility of an information leakage over a longer in-terval. Event window [-10, -2] tests for an anticipative run-up in price before the event becomes publicly known.
I estimated the simple market model with OLS technique to adjust for systematic risk:
Rit= αi+ βiRmt+ eit (2.1)
5Obviously, some hypotheses are simply incompatible, e.g. raiding hypothesis and price pressure because the first requires both purchases and negative returns while the second associates purchases with price increases.
where Rit is the return to firm i at time t, Rmt is the market return at time t, and eit is an i.i.d. error. α and β are the parameters to be estimated. The estimation period is a 300-day interval from day -349 to day -50 with respect to the event day (day 0). I followed the procedure described in Campbell, Lo, and MacKinlay (1997) in order to compute CARs and related statistics.
Since thin trade could generate biases in the estimation of ˆβi, a market model with betas from Dimson (1979) aggregate coefficient method is also computed and presented. In particular, I use the specification of the aggregate coefficient method with three lags and one lead. Thus, the regression equation is
Ri,t= αi+ X1 i=−3
βiRm,t+i+ ei,t. (2.2)
According to Dimson (1979), a consistent estimate of β is obtained aggregating the slope coefficients from Equation 2.2. The estimated β is given by:
βˆD = X1 i=−3
βˆi. (2.3)
The standard procedure I used estimates the variance of the aggregate CARs with past returns. This could lead to ignore the so-called event-induced variance problem discussed by B¨ohmer, Musumeci, and Poulsen (1991), that is the given event is accompanied by increases in the cross-sectional dispersion of stock returns. To address this issue, t-statistics using both the ordinary cross-sectional method and the standardized cross sectional method are computed for event window [-1,0].
Clustering6 is generally not an issue with daily price, as Brown and Warner (1985) point out. In addition, B¨ohmer, Musumeci, and Poulsen (1991)’s method is robust with respect to clustering. Furthermore, my sample does not present clear proof of clustering.
These considerations lead me to the conclusion that clustering is not a relevant problem.
Therefore, I do not take into account clustering in the following analysis.
2.3.2 Results
The average initial stake purchased by active investors at the time of their first public announcement is 5.71 percent7. In Banerjee, Leleux, and Vermaelen (1997) the average percentage of shares acquired is 11.3, while Holderness and Sheehan (1985) find that 90 percent of the initial holdings were for less than 12 percent. However, these papers take into consideration acquisitions of more than 5 percent of the outstanding class of one security.
In my sample, smaller acquisitions are included as well.
The average cumulative abnormal return to shareholders in target firms over the pe-riod [-30,100] is plotted in Figure 2.1 and the CARs over the different event windows are presented in Table 2.1.
6Clustering is present when the event windows of the included securities overlap in calendar time. Clus-tering prevents that abnormal returns on individual securities are uncorrelated in the cross section (see Campbell, Lo, and MacKinlay (1997), chapter 4).
7The median stake is 4.57 percent, the minimum stake is 0.2 percent and the maximum is 39.3 percent.
−40 −20 0 20 40 60 80 100
−0.02 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14
Time
Cumulative Return
CUMULATIVE ABNORMAL RETURNS FROM DAY −30 TO DAY 100
Active Investors Random Sample No Further Purchases
Figure 2.1: CARs from 30 Days Before to 100 Days After the First Public An-nouncement of an Investor’s Stockholding
Cumulative average daily abnormal returns from 30 days before to 100 days after the first public announce-ment of an investor’s stockholding for the active investors’ targets (No. Obs. 136), for the random sample (No. Obs. 137), and for the sub-sample of active investors’ targets when there is no further purchase in the 120 days following the initial purchase (No. Obs. 91).
Table 2.1: CARs
Cumulative average daily abnormal returns in percent for various event windows for the active investor’s target firms, the firms targeted by the random sample of investors, and for the sub-sample of active investors’
targets when there is no further purchase in the 120 days following the initial purchase (t-stats are given in parentheses).
Event Window Active Investors Random Sample No Purchases
[-1, 0] 2.44 2.61 2.30
(6.91) (5.19) (5.61)
[-30, 1] 8.77 6.85 5.16
(5.59) (2.93) (2.81)
[-30, 5] 9.12 7.36 5.14
(5.41) (2.91) (2.61)
[-30, 10] 8.70 6.85 4.40
(4.76) (2.48) (2.06)
[-30, 30] 9.30 9.31 3.58
(3.95) (2.58) (1.30)
[-30, 100] 13.65 10.24 1.95
(3.40) (1.58) (0.41)
[-10, -2] 2.98 0.42 2.31
(3.88) (0.37) (2.58)
No. Obs. 136 137 91
The findings in Table 2.1 show that on the days before and the day of the first public announcement there is a positive abnormal return of 2.44 percent earned on average by the stockholders in target firms. The abnormal return is highly significant from a statistical point of view. This return is higher than the one reported by Holderness and Sheehan (1985) (2.44 percent vs 1.77 percent). On the other hand, the abnormal return is considerably lower than the CAR reported in Barclay and Holderness (1989) for NYSE- or AMEX-listed corporations that experienced a negotiated block trade of at least 5 percent of the common stock (5.1 percent on [-1, 0], where day 0 is the initial public announcement of the block trade). However, the difference largely disappears when Barclay and Holderness (1989) consider only firms remaining independent one year after the block-trade announcement.
Barclay, Holderness, and Sheehan (2001) find an abnormal return of 5.9 percent from day -1 to day 1 for the announcement of block investments.
Abnormal returns around the announcement day of a raider’s stockholding are surpris-ingly low when compared to the changes in share price after block share purchases by an activist investors for the firms studied by Bethel, Liebeskind, and Opler (1998). When an activist investor announces the block purchase, the target firm’s share price reports an increase of 15.7 percent over the event-time interval [-30,5] and of 14.2 percent over [-30,30]. Conversely, firms targeted by raiders show CARs of 9.12 percent and 9.30 percent in the two event-time intervals considered by Bethel, Liebeskind, and Opler (1998). This difference is hard to explain. One possible explanation concerns the time period. Bethel, Liebeskind, and Opler (1998) analyze block purchases in the U.S. during the 1980s, a period characterized by the hostile takeover wave. Thus, the higher returns of Bethel, Liebeskind, and Opler (1998) can be explained by the bigger increase in the probability of becoming a target of a hostile takeover bid8. To support this view, it is worth noting that firms tar-geted by the activist shareholders of Bethel, Liebeskind, and Opler (1998) experienced both more takeovers and LBOs than other firms in the two years following the block purchase9. Strangely enough, Bethel, Liebeskind, and Opler (1998) do not provide the average of the stake purchased. However, it is possible to compute the average stake from their dataset available on the Journal of Finance World Wide Web site. The average is 11.73 percent for the block share purchases recorded for activist shareholder (213 observations)10, roughly twice the average purchase of the raiders studied here. Since the CARs are positive in any of the event windows considered, this event study gives no support to the raiding hypothesis.
Both Figure 2.1 and Table 2.1 document a run-up in stock prices before the event. This may be due to the fact that the vast majority of the transactions is carried out through open-market purchases. It can take some months to accumulate a stake for which an official notification is required. Anecdotal evidence supports this explanation11. However, it is worth stressing that a run-up in price is perfectly consistent both with the price-pressure hypothesis and with a long-run downward sloping demand curve if the stake accumulation
8It is worth noting that the activist investors of Bethel, Liebeskind, and Opler (1998) include the U.S.
corporate raiders, who were well-known for launching hostile bids.
9See Bethel, Liebeskind, and Opler (1998), Table III, page 616. I will come back on this point in Section 2.3.5.
10Bethel, Liebeskind, and Opler (1998) use only 244 block purchases for their analysis. The average stake for the other investors is roughly similar, 10.41 percent for financial investor and 12.31 for strategic investor.
11It is easy to read on the newspapers after the official announcement of a raider’s stockholding that the stake was accumulated slowly over a period of weeks or even months.
takes place over a long time interval. One relevant feature of Figure 2.1 is that, after the purchase is made, there is no significant increase in cumulative returns. CARs from day 1 to day 100 are only 4.88 percent, not significantly different from 0 over a 99 days period.
Indeed, the plot for CARs after the announcement date shows a weak upward drift. The absence of a price reversal is also a warning against the price-pressure hypothesis.
Figure 2.1 plots also the CARs of the random sample, whose relevant CARS and t-stats are shown in Table 2.1, too. The random sample consists of 137 observations of announcements of the initial stake purchase made by investors not included in my raider list in Europe during the period 1993-2001. The random sample includes purchases by industrial firms, institutional investors, as well as individual investors who do not adopt a public activist position. Further details about the composition and selection criteria of the random sample are in Appendix B.
The average stake purchased in the firms included in the Random Sample is 7.59 percent.
A standard two-tails t-test for the difference in means between firms targeted by the Active Investors and the Random Sample is highly significant (p-value 0.00).
On the event window [-1,0], the random sample has an average abnormal return of 2.61 percent that is higher than the one for firms included in the Active Investors’ sample.
However, over longer intervals, the Active Investor sample generally dominates (see Figure 2.1). Interestingly, the CARs for the two samples are remarkably similar from day 30 to day 60. Random Sample’s CARs are not statistically different from zero in the time interval [-30, 100] (return 10.24 percent). The findings show that there is no run-up in [-10, -2] for Random Sample’s firms.
Despite this difference in average returns, a standard t-test fails to detect a significant difference between Active Investors and Random Sample over any interval considered as Table 2.2 shows.
The results support Holderness and Sheehan (1985)’s finding that these raiders are not driven by the pure raiders hypothesis, i.e. the investors do not want, at least initially, simply to exploit the target firms. However, these results also indicate that the market is not particularly interested in the identity of the stockholder. If confirmed, this is a serious blow to the information-based hypotheses.
I cannot exclude that an active investor buys further stakes after the initial public announcement. These additional purchases might have an impact on the abnormal return after day 0 and explain the absence of a price reversal.
The continuous line in Figure 2.1 presents the cumulative returns for firms in the Active Investors’ Sample that did not experience further purchases by these investors over the 120 days following the initial announcement of stockholding. 91 observations fulfill this requirement. When the initial stockholding is not increased, the mean stake purchased at event date is similar to the one for the sample as a whole (5.49 percent vs 5.71 percent)12. This difference is not statistically significant. Conversely, the test is statistically highly significant when this subsample is compared to the Random Sample13.
The results are shown in Table 2.1, Column 3. These results seem to provide support for the hypothesis that an initial stake purchase does not increase target firm value through time if not supported by other actions. Although on the event window [-1,0] the abnormal
12The median is 4.02 percent.
13p-value 0.00 for a standard two-tail t-test.
Table 2.2: Differences in Means and Associated T-stats
Differences in means and associated t-stats for differences in means between the CARs for the active investors’
targets (No. Obs. 136) and for the random sample (No. Obs. 137), and between the CARs for the subsample of active investors’ targets when there is no further purchase in the 120 days following the initial purchase (No. Obs. 91) and for the random sample (t-stats in parentheses).
Event Window Act. Inv.- RS No Further Purchases-RS
[-1, 0] -0.17 -0.31
(-0.21) (-0.34)
[-30, 1] 1.93 -1.68
(0.77) (-0.60)
[-30, 5] 1.76 -2.22
(0.65) (-0.73)
[-30, 10] 1.85 -2.45
(0.65) (-0.76)
[-30, 30] -0.02 -5.73
(0.00) (-1.29)
[-30, 100] (3.42) (-8.29)
0.46 -1.00
return is highly significant and close to 2.44 percent, target firms that did not experience further purchases show a sort of reversion effect. The cumulative returns over the event window [-30, 1] are more than one-third less than those of the sample as a whole, too14.
CARs for Active Investors’ subsample oscillate between 3 and 4 percent most of the time and exhibit a late reversion towards zero. A similar pattern is found in Barclay and Holderness (1991) for firms remaining independent public entities after a negotiated block trade. As Barclay and Holderness (1991) point out, the initial increase reflects an increased expectation that minority investors’ shares will be acquired. When the market observes that this expectation has not come true, stock prices drift down.
Following this interpretation, the return around the announcement date reflects the probability that a raider may engage in further purchases leading to further increases in value. When no additional purchase takes place, the market adjusts its valuation and the share price declines in response to the limited purchase15. Alternatively, the decrease in prices might also be explained by the fact that the market is somewhat fooled by these investors on the public announcement day. Subsequently, the market punishes the target firms if it does not observe further purchases. The initial purchase by one of these raiders is not seen by the market as a credible commitment to improve target firm performance.
Table 2.2, Column 2, shows the results of simple t-tests for differences in means between this sub-sample and the Random Sample. When only target firms without further buys are considered, the Active Investors’s Sample underperforms the Random Sample. The maximum difference between the CARs of the two series is 8.00 percent at day 57. The t-stats for differences in means are not significant. Therefore, the evidence rejects the pure raiding hypothesis and confirms that markets do not seem to be interested in the stockholder’s identity.
2.3.3 Additional Tests
Although the values of the t-stats and the associated p-values give clear results concern-ing the rejection of the null hypothesis that the CAR is zero, performconcern-ing additional non-parametric tests can further strengthen the findings in Section 2.3.2.
To begin with, Table 2.3 shows the number of CARs that turns out to be positive in the time intervals considered. Roughly 70 percent of the firms targeted by corporate raiders have an abnormal return greater than zero (69 percent) on [-1,0]. As event windows become longer, the percentage slightly decreases but it remains well above one half16. The p-value of the sign test is highly significant in any interval. The results are consistent with Table 2.1 leading to the rejection of the raiding hypothesis.
The evidence for the random sample is also consistent with Table 2.1 with the only exception of [-30, 5] where only 57 percent of the observations present a positive CAR.
Results for firms in which no purchase is made in the period following the announcement date are weaker than in Table 2.1 apart from in [-30, 30] where the sign test is significant and
14Given the results of the event studies, it comes as no surprise that the coefficient of a dummy for additional purchases is always highly significant when the CARs for the 136 announcements of raiders’
stockholding are regressed on this dummy variable and a constant. The only exception is when the dependent variable is the CAR over the period (-1,0).
15I wish to thank Michel Habib for suggesting this line of thought to me.
1665 percent over [-30,100].
Table 2.3: Sign Test
Number of positive CARs in the various time intervals considered for the active investors’ targets (No.
Obs. 136), for the random sample (No. Obs. 137), and for the sample of active investors’ targets without purchases in the 120-day interval following the announcement date (No. Obs. 91). The p-values of the associated sign tests are reported.
[-0,1] [-30,1] [-30,5] [-30,10] [-30,30] [-30,100] Total
A. I. 94 91 92 92 90 89 136
0.00 0.00 0.00 0.00 0.00 0.00
R. S. 84 85 78 82 83 77 137
0.01 0.01 0.12 0.03 0.02 0.17
No P. 57 56 55 56 55 50 91
0.02 0.04 0.06 0.04 0.06 0.40
the t-test is not. The hypothesis that the median is zero is tested also with the Wilcoxon signed-rank test. The results are substantially identical to the ones obtained with the standard t-test and therefore omitted for the sake of brevity17.
The tests for differences in means carried out in Section 2.3.2 do not provide any strong evidence supporting the three hypotheses of Holderness and Sheehan (1985). Additional tests are performed to check the robustness of the results.
Table 2.4, Panel A reports the median CARs over the different time intervals considered for both the firms targeted by raiders, the random sample, and firms targeted by raiders that did not experience any additional purchase in the 120 days following the initial an-nouncement. Moreover, Table 2.4, Panel B reports also the p-values of the tests for equality of medians between the samples (Wilcoxon/Mann-Whitney test).
Two facts stand out from the comparison of the results of the test between firms targeted by corporate raiders and those included in the Random sample (Table 2.4, Panel B, Column
“Ac. Inv. vs RS”) and the findings of Table 2.2. First, the difference on the event date most closely related with the announcement [-1,0] is no longer negative. However, the equality between the two medians is not rejected at conventional level. Second, the medians are not statistically different at conventional levels. Hence, the broad picture is remarkably similar to that of Table 2.2. In fact, while firms targeted by raiders earn larger returns, they are generally not significant from a statistical point of view.
Differently from Table 2.2, firms targeted by raiders that did not experience any addi-tional purchase in the 120 days following the initial announcement do not have always a smaller median than the firms in the random sample. However, the hypothesis that medians are equal for the two groups of firms is not rejected in any time intervals considered.
17Results are available from the author.
Table 2.4: Medians
Panel A shows the median CARs for the active investors’ targets (No. Obs. 136), for the random sample (No. Obs. 137), and for the sample of active investors’ targets without purchases in the 120-day interval following the announcement date (No. Obs. 91). Panel B reports the p-values for the Wilcoxon/Mann-Whitney tests for equality of medians between the CARs of the active investors’ targets (Ac. Inv.) and the CARs of the random sample (RS) (Column Ac. Inv. vs. RS) and between the CARs of the active investors’
targets without purchases in the 120-day interval following the announcement date and those of the random sample (Column No Purch. vs Rs).
Panel A: Median CARs
Event Window Active Investors Random Sample No further Purchases
[-1, 0] 2.01 0.89 1.62
[-30, 1] 6.17 3.31 4.17
[-30, 5] 7.89 2.75 3.92
[-30, 10] 7.24 5.34 4.18
[-30, 30] 5.44 5.27 2.34
[-30, 100] 11.00 3.36 2.76
Panel B: Wilcoxon/Mann-Whitney Tests
Event Window Ac. Inv. vs RS No Purch. vs RS
[-1, 0] 0.13 0.55
[-30, 1] 0.29 0.75
[-30, 5] 0.19 0.86
[-30, 10] 0.32 0.62
[-30, 30] 0.56 0.33
[-30, 100] 0.19 0.72
Table 2.5: Kolmogorov-Smirnov Test
P-values of the Two-sample Kolmogorov-Smirnov goodness-of-fit hypothesis test. In Column I, the test determines whether CARs from the Active Investors and the Random Sample are drawn from the same
P-values of the Two-sample Kolmogorov-Smirnov goodness-of-fit hypothesis test. In Column I, the test determines whether CARs from the Active Investors and the Random Sample are drawn from the same