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Using textual analysis to identify merger participants: Evidence from the U.S. banking industry

Katsafados, Apostolos G. and Androutsopoulos, Ion and Chalkidis, Ilias and Fergadiotis, Emmanouel and Leledakis, George N. and Pyrgiotakis, Emmanouil G. (2019): Using textual analysis to identify merger participants: Evidence from the U.S. banking industry.

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Abstract

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.

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