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

Author

Listed:
  • Katsafados, Apostolos G.
  • Androutsopoulos, Ion
  • Chalkidis, Ilias
  • Fergadiotis, Emmanouel
  • Leledakis, George N.
  • Pyrgiotakis, Emmanouil G.

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.

Suggested Citation

  • Katsafados, Apostolos G. & Androutsopoulos, Ion & Chalkidis, Ilias & Fergadiotis, Emmanouel & Leledakis, George N. & Pyrgiotakis, Emmanouil G., 2019. "Using textual analysis to identify merger participants: Evidence from the U.S. banking industry," MPRA Paper 96893, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:96893
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    More about this item

    Keywords

    Textual analysis; text sentiment; bank mergers and acquisitions; acquisition likelihood;

    JEL classification:

    • G00 - Financial Economics - - General - - - General
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance

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