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Keywords

textual analysis, mergers and acquisitions, m&a, sentiment analysis, diction, defm, shareholder voting proxy letters

Abstract

Modern corporations utilize mergers and acquisitions as strategies to develop shareholder value today more than ever before, yet the need for understanding firms’ rationale and strategy is critical in predicting post-merger stock performance for all investors. I apply the interpretive power of textual analysis and regression to a corpus of SEC mergers and acquisitions public company filings between 1994-2017. Not only do I challenge the statistically significant correlation between word content and post-transaction abnormal stock returns, but I also characterize the effects of time segments, transaction size, and industry variation across time. As a final application, I consider sentiment analysis using Diction software packages across the corpus, and measure correlation across economic cycles to assess post-filing stock performance.

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Marriott Student Review is a student journal created and published as a project for the Writing for Business Communications course at Brigham Young University (BYU). The views expressed in Marriott Student Review are not necessarily endorsed by BYU or The Church of Jesus Christ of Latter-day Saints.

 

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