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Review of Quantitative Finance and Accounting

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07.05.2020 | Original Research

Examining the stock performance of acquirers where the acquirer or target hold patents

verfasst von: Kevin H. Kim, Derek K. Oler, Juan Manuel Sanchez

Erschienen in: Review of Quantitative Finance and Accounting | Ausgabe 1/2021

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Abstract

We investigate the stock returns for acquirers of firms holding registered patents (“innovative targets”). We find that acquiring innovative targets is associated with significantly positive stock performance relative to acquisitions of non-innovative targets. Specifically, acquirers of innovative targets enjoy higher announcement and interim period abnormal returns. Acquirers of innovative targets also enjoy higher post-acquisition returns, but only in settings where the acquirer’s and target’s industry is unambiguously close (i.e., they share the same 3-digit primary SIC code), suggesting that when the acquirer has familiarity and expertise in that industry the acquirer is able to better exploit the target firm’s patents. Additionally, we find that an acquirer’s innovation level can be critical to their post-acquisition stock performance; that is, acquirers holding at least one patent of their own prior to the acquisition enjoy significantly higher post-acquisition returns, and this benefit does not depend on the innovativeness of the target firm.

Vorheriger Artikel How reverse merger firms raise capital in PIPEs: search costs and placement agent reputation

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The main determinant of bonus payments and compensation increases to executives is net income (Murphy 1999, 2012). Because R&D reduces earnings, it creates disincentives for managers to invest in these projects (Duru et al. 2002). In addition, executives are constantly pressured to meet earnings benchmarks. Graham et al. (2005) shows survey evidence suggesting that managers curtail R&D and other discretionary spending items to meet earnings expectations. Hence, the incentives not to invest in “organic” innovation are strong.

Our measure of industry relatedness is admittedly crude (see Alhenawi and Stilwell 2018), but is suitable for our purpose of identifying settings where acquirer managers have sufficient experience to exploit the target’s patents.

Another possible disadvantage of buying an innovative target could be that the acquirer may overpay. Moeller et al. (2004) find that larger firms tend to overpay for targets, and firms may also pay an additional premium for the patents of the target firm. We also investigate this possibility.

Our announcement period returns are measured as of days − 2 to + 2 relative to the acquisition announcement, and our interim returns are measured as of day + 3 relative to the announcement date until the acquisition effective date. Our post-acquisition period begins on the day of acquisition effective date and ends 2 years after.

Sevilir and Tian (2012) do show results for three models: a market model, a 3-factor model, and a 4-factor model. They find significant results for only their 4-factor model. Our results suggest significant post-acquisition returns are only realized when the acquirer and innovative target share the same 3-digit primary SIC code.

In contrast, Fong et al (2019) report that greater cultural distance between the acquirer and target results in higher post-acquisition returns enjoyed by the acquirer.

This is an ubiquitous quote; one reference is found at http://www.personal.psu.edu/mrr18/blogs/psel/2012/06/innovation-distinguishes-between-a-leader-and-a-follower—steve-jobs.html.

Kogan et al. (2017) collect details of patents data from google through a special data-hosting arrangement with United States Patent and Trademark Office (USPTO). They download high-quality text files and then extract information from the text files. We appreciate Leonid Kogan, Dimitris Papanikolaou, Amit Seru, and Noah Stoffman for sharing the patent dataset (available at: https://iu.app.box.com/v/patents).

Our calculation follows the recommendations of Barber and Lyon (1997). Lyon et al. (1999) suggest that the use of control firms may have slightly less power than alternative methodologies (which works against our finding of significant results), although their specification tests suggest that it performs approximately as well as other methodologies.

In our calculation of returns, we include delisting returns for any firm delisted before the end of the post-acquisition period; we follow Beaver et al. (2007) by using average delisting returns for firms in the same industry when the delisting returns for a particular firm are missing.

We check our results with two other proxies for innovative target. First, we place target firms into ranks from 0 to 4 based on the number of patents they hold (“innovative target rank”). Second, we calculate the average of the cumulative abnormal returns (CAR) around the date when each target patent was announced (“target innovation level rank”). Our conclusions remain the same.

Using a fully interacted model (i.e., also including the following interactions in model (2): Industry Expertise*Innovative AQ and Innovative Target*Industry Expertise*Innovative AQ) causes undue multicollinearity (e.g., the variance inflation factors (VIF) associated with some interaction variables exceeded 12), which leads to loss of significance in some of our variables of interest. We note that the direction and magnitude of the coefficients of interest remained relatively unchanged.

The average of the number of patents is 1517 highlighting the skewness of the distribution of patents.

Our results hold with our other two innovative target proxies noted in footnote 10. Specifically, “innovative target rank” and “target innovation level rank.”

Our number of observations are only 2882 for interim period returns (vs. 3542 for the announcement and post-acquisition returns) because 996 announced acquisitions were also consummated on the same day, leaving no interim period.

Overpayment may be less likely here because the target’s patents are explicitly documented innovations that may be easier to evaluate (and value) than other “synergies” that are often less rigorously identified (see Sirower 1997).

Because we use both acquirers and non-acquirers in our prediction model, we didn’t label the variables as “AQ XX”. We calculate them as we explain in Appendix for both acquirer firms and non-acquirer firms.

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Titel: Examining the stock performance of acquirers where the acquirer or target hold patents
verfasst von: Kevin H. Kim
Derek K. Oler
Juan Manuel Sanchez
Publikationsdatum: 07.05.2020
Verlag: Springer US
Erschienen in: Review of Quantitative Finance and Accounting / Ausgabe 1/2021
Print ISSN: 0924-865X
Elektronische ISSN: 1573-7179
DOI: https://doi.org/10.1007/s11156-020-00890-0

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