Using Textual Analysis to Identify Merger Participants: Evidence from the U.S. Banking Industry
15 Pages Posted: 3 Nov 2019 Last revised: 21 Sep 2021
Date Written: October 23, 2019
In this paper, we use the sentiment of annual reports to gauge the likelihood of a bank to participate in a merger transaction. We conduct our analysis on a sample of annual reports of listed U.S. banks over the period 1997 to 2015, using the Loughran and McDonald’s lists of positive and negative words for our textual analysis. We find that a higher frequency of positive (negative) words in a bank’s annual report relates to a higher probability of becoming a bidder (target). Our results remain robust to the inclusion of bank-specific control variables in our logistic regressions.
Keywords: Textual analysis, text sentiment, bank mergers and acquisitions, acquisition likelihood
JEL Classification: G14, G21, G34, G40
Suggested Citation: Suggested Citation