Abstract
Small acquirers enjoy announcement period returns that are significantly higher than announcement returns for larger acquirers, but small acquirers significantly underperform after the acquisition is consummated. We investigate why the market appears to “get it wrong” at the announcement of an acquisition by a small firm. We provide evidence consistent with an initial optimistic overreaction, followed by a correction as updated information is revealed. Overreaction is clustered in small acquirers offering stock and acquiring relatively larger targets. Low post-acquisition returns and poor fundamental performance are clustered in small acquirers offering stock and diversifying.
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Notes
We define a small acquirer as having a market capitalization below the 25th percentile of NYSE firms in the year the acquisition is announced.
Hubris is generally defined as an overestimation of managers’ ability to manage the acquisition (Roll 1986). Managers with hubris are more likely to pursue a poor acquisition target and/or more likely to overpay.
The market’s assessment of the acquisition need not be perfect, but if it is unbiased then average interim and post-acquisition returns will be zero.
Along this line, our paper corroborates the findings of Drake et al. (2015), who show that market efficiency in general is improved when EDGAR filings are accessed more frequently.
Small acquirers have less acquisition experience than larger acquirers; small acquirers have a mean of 4.23 prior acquisitions versus 13.46 prior acquisitions for larger acquirers.
As we explain later, our results are robust to defining diversification using the Fama and French (1997) industry classifications.
Prior research suggests that small firms operate in a less rich information environment; for example, the press is less likely to cover small firms (Miller 2006). Small acquirers, in general, also have lower analyst coverage. These factors lead to greater market inefficiency for smaller firms (Loughran and Ritter 2000). For example, Bernard and Thomas (1989) find that post-earnings announcement drift is stronger in smaller firms, also suggesting less market efficiency for those firms.
MSS’s sample period begins with 1980, however, we begin our sample with 1984 as recent research evaluating the completeness and accuracy of the SDC merger database finds that coverage is poor to moderate before 1984 (Barnes et al. 2014).
Consummation can occur at any date before the first post-acquisition year-end (year + 1), and accordingly we examine years + 2 to + 4 in order to ensure that we examine fiscal years that are clearly attributable to post-acquisition performance. Year + 1 also reflects the first annual financial report that investors see after consummation. Even if the “year + 1” financial statements do not fully reflect the acquisition’s performance, many investors may believe that it does. Willengborg et al. (2015) use average total assets instead of end-of-year total assets; however, in an acquisition setting beginning-of-year total assets would include only the acquirer’s assets without the target’s, deflating the denominator and inflating ROA for year + 1. However, our conclusions are very similar if we use average assets.
Results are similar if we use performance as of year − 1 as our control.
Acquirer market capitalization and book-to-market are also common controls; however, they are controlled for with our selection of matching firms. To be consistent with MSS, we exclude them from our multivariate analysis.
Small (large) acquirers experience average abnormal announcement period returns of 2.3% (0.08%) in the MSS study.
This lack of experience is especially prominent in small acquirers offering stock (average prior acquisitions are 2.75 for small stock acquirers), purchasing relatively larger targets (3.52), and diversifying (4.02).
For brevity, we will refer to clustered p-values hereafter unless explicitly noted otherwise.
As our interest is in small acquirers in general, we do not exclude 3805 cross-border acquisitions. However, our conclusions are unchanged if we exclude these observations.
We note that some of our median p-values (e.g., medians for Panel B, pre-acquisition analyst coverage) reflect statistical significance when the medians themselves are exactly the same (e.g., median coverage of 1 for Panel B). This is because the Wilcoxon test we use is a rank-sum test (i.e., all observations are ranked, the ranks are added, and then the rank-sums are compared), and this procedure can sometimes result in statistically significant results even when the medians themselves are the same because the rank-sums are different.
We also note that mean trading volume figures are exceptionally high, while medians are not quite as inflated. This suggests there are still some significant outliers, and that some small acquirers were thinly traded prior to the announcement. Further, the median announcement volume for small acquirers is lower than for larger acquirers (109 vs. 123%), and this appears to be because trading volume for non-stock small acquirers, non-large target small acquirers, and non-diversifying small acquirers is low.
Although the results for the first year-end after consummation may not be a suitable reflection of post-acquisition performance (for example, if the acquisition is consummated on December 30 and the fiscal year-end is December 31), those financial statements will still be the first post-acquisition financial statements investors will receive. Even if incorrect, the perception of many investors will likely be that those financial statements reflect, in some measure, the performance of the acquisition.
One difference between our use of unadjusted ROA as opposed to abnormal ROA is that, with unadjusted ROA, the small acquirer dummy alone has a significantly negative coefficient.
Our use of ROA from 3 years prior to confirmation ensures that we do not have contamination in our control from operating decisions made in anticipation of the acquisition.
We thank an anonymous reviewer for this robustness suggestion. Overall, a more refined measure of relatedness may be an interesting avenue of exploration for future research; see Alhenawi and Stilwell (2019).
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The authors thank participants at the 2012 BYU Accounting Research Symposium, workshop participants at the University of Mississippi, Utah State University, participants at the 2013 AAA SW Regional Meeting, and Fei Xie (at University of Delaware) for helpful comments and suggestions.
Appendix: Variable definitions and calculations
Appendix: Variable definitions and calculations
Stock price and shares outstanding are taken from the CRSP database. All financial statement information is taken from the combined CRSP/Compustat (annual) database provided by Wharton Research Data Services (WRDS). Information is taken as at the most recent month-end that is at least 30 days before the announcement of the acquisition. We assume a 3-month lag between a firm’s year-end and when financial statements are publicly available.
Our multivariate BHARs are calculated as follows:
- Ri,t:
-
Returns for firm i over the period beginning with day s and ending with day e, where s = day − 2 and e = + 2 relative to announcement for announcement period returns, s = + 3 and e = deal consummation date for interim period returns, and s = day + 1 relative to deal consummation date and e = end of month + 24 for post-acquisition returns, and
- Rmp,t:
-
Mean portfolio returns (from four peer firms) over the same period
Table 9 provides details on calculations of our independent variables.
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Harp, N.L., Kim, K.H. & Oler, D.K. A bold move or biting off more than they can chew: examining the performance of small acquirers. Rev Quant Finan Acc 56, 393–422 (2021). https://doi.org/10.1007/s11156-020-00893-x
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DOI: https://doi.org/10.1007/s11156-020-00893-x