Unique Bidder-Target Relatedness and Synergies Creation in Mergers and Acquisitions

68 Pages Posted: 1 Oct 2018 Last revised: 13 Oct 2021

See all articles by Tingting Liu

Tingting Liu

Iowa State University

Zhongjin Lu

University of Georgia - Department of Finance

Tao Shu

The Chinese University of Hong Kong, Shenzhen; Shenzhen Finance Institute

Fengrong Wei

Georgia Institute of Technology

Date Written: March 18, 2019

Abstract

We examine the effect of the uniqueness of bidder-target relation, i.e., the number of firms that share the bidder-target relation, on merger synergies. We use machine learning tools to measure unique bidder-target relatedness and find that unique relatedness is associated with a much larger increase in merger synergies than non-unique relatedness. The measure of unique relatedness mostly captures product relatedness, and the measure dominates alternative product relatedness measures in predicting merger synergies. Analysis of the acquirer’s post-merger operating performance shows that the unique relatedness creates synergies through enhanced operating efficiency rather than an increase in investment or revenue.

Keywords: Distinct Relatedness, Synergies, Mergers and Acquisitions, Conditional Dependence, Lasso, Stock return comovement

JEL Classification: G34, G30

Suggested Citation

Liu, Tingting and Lu, Zhongjin and Shu, Tao and Wei, Fengrong, Unique Bidder-Target Relatedness and Synergies Creation in Mergers and Acquisitions (March 18, 2019). Available at SSRN: https://ssrn.com/abstract=3257994 or http://dx.doi.org/10.2139/ssrn.3257994

Tingting Liu

Iowa State University ( email )

2330 Gerdin Business Building
Ames, IA 50011
United States

Zhongjin Lu

University of Georgia - Department of Finance ( email )

Terry College of Business
Athens, GA 30602-6254
United States

Tao Shu (Contact Author)

The Chinese University of Hong Kong, Shenzhen ( email )

Shenzhen Finance Institute ( email )

Fengrong Wei

Georgia Institute of Technology ( email )

Atlanta, GA 30332
United States

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