2021
DOI: 10.1002/rfe.1126
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What’s really in a deal? Evidence from textual analysis of M&A conference calls

Abstract: Using a sample of 814 transcripts from 2011 to 2018, we examine information within merger and acquisition conference calls. Textual analysis reveals significant differences between the content of M&A call transcripts and both contemporaneous corporate press releases and prior earnings conference calls. We find participation of target executive types in M&A calls occurs more frequently in diversifying acquisitions and is related to payment choice consistent with promoting managerial sectorspecific skills and in… Show more

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Cited by 10 publications
(12 citation statements)
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“…Rabier (2017), for example, categorizes deal motives based on the expected synergies the deal is likely to generate. Another stream of literature uses efficient motive classification framework to categorize deals as financial or strategic (Hu et al, 2021;Lim and Lee, 2016). A third way of inferring acquisition motives was presented by Gubbi and Elango (2016).…”
Section: Theoretical Backgroundmentioning
confidence: 99%
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“…Rabier (2017), for example, categorizes deal motives based on the expected synergies the deal is likely to generate. Another stream of literature uses efficient motive classification framework to categorize deals as financial or strategic (Hu et al, 2021;Lim and Lee, 2016). A third way of inferring acquisition motives was presented by Gubbi and Elango (2016).…”
Section: Theoretical Backgroundmentioning
confidence: 99%
“…As numbers and words send signals about the company's future differently, recent research implies that the amount of numerical or quantitative information relative to the total information in textual disclosures significantly impacts the dissemination of information (Campbell et al, 2021). Quantitative disclosure in press releases provides salient information and additional insight into the decision-making process (Hu et al, 2021). Quantitative or numeric data signals the expected synergies that the deal is likely to create, estimates the growth potential of the acquisition, provides historical information related to sales, asset base, leverage, etc., about the target and the acquirer company, the market position that will be captured if the deal gets completed, and likewise.…”
Section: Quantitative Information and Deal Outcomesmentioning
confidence: 99%
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“…Under the third approach, researchers write NLP rules that target specific events in the text of firm disclosures, such as, for example, M&A-related activity (Hu, Shohfi, and Wang 2021) or backlog disclosures (Feldman, Govindaraj, Livnat, and Suslava 2021).…”
Section: Extraction Of Textual Characteristics Of Cam Disclosuresmentioning
confidence: 99%