Overview of Mergers & Acquisitions

Acquisitions: When an acquiring company buys a portion of a target company.

Merger: When an acquiring company buys all of a target company; the acquirer remains and the acquired no longer exists as an independent corporate entity.

Integration Forms

M&A transactions can be segmented by the manners in which the acquired is integrated with the acquirer.

  • Subsidiary Merger: the target becomes a subsidiary of the acquiring company.  The acquiring company may use this form of integration in order to retain the brand recognition of the acquired entity.

  • Statutory Merger: the acquired no longer exists; it becomes part of the acquirer.

  • Consolidation: neither the acquired, nor the acquirer remain, rather both combine to form a new company.

Merger Types

  • Mergers can also be described by the way the business operations of the acquirer and the target relate to one another.

  • Horizontal Mergers: the combination of two companies in the same business line.  For example, one beverage production company may decide to purchase another beverage production company.

  • Vertical Mergers: the purchase of a target company which performs an upstream or downstream function in the acquirer’s industry value chain.

  • Backward Integration: the acquirer purchases a company closer to the raw material extraction phase of the industry value chain.  For example, a natural gas commercial distributer may decide to purchase a natural gas miner.

  • Forward Integration: the acquirer purchases a company closer to the market delivery phase of the industry value chain.  For example, a gold miner may decide to purchase a chain of retail jewelry stores.

  • Conglomerate Merger: this is the case where an acquirer purchases a company in an unrelated line of business.  For example, an airplane manufacturer may decide to purchase a chain of hospitals.

Reasons for M&A

Ideally, mergers are executed with the expectation that the target will increase the equity value of the acquirer.  Below some common merger motivations are described.

  • Cost Synergies: Mergers have the potential to lower costs for the combined companies, either through the elimination of redundant functions or by eliminating profits from “middle-man” points in the value chain.
  • Revenue Synergies: Mergers may provide the combined companies an opportunity to cross sell complementary products.
  • Growth: An acquisition might provide a company with more rapid growth potential than organic growth provided by reinvesting earnings.
  • Pricing Power: A horizontal merger can reduce competition and allow the acquirer to raise its prices.  A vertical merger can allow the acquirer to better control prices downstream or upstream in the value chain. When a merger has the potential to provide an acquirer with too much market power, government regulations may prevent the merger from taking place.
  • Increased Capability: An acquiring company may pursue a target for its in-house technical expertise.
  • Unlocking Value: An acquirer may view a target as underperforming financially and feel confident that it can facilitate the realization of the target’s full potential after taking control.
  • Diversification: Companies themselves are investors who seek to reduce risk and increase returns through the successful deployment of capital.
  • International M&A Concerns: Companies may engage in M&A beyond their domestic borders for multiple financial or strategic reasons.

Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book includes PDFs, explanations, instructions, data files, and R code for all examples.

Get the Bundle for $29 (Regular $57)
JOIN 30,000 DATA PROFESSIONALS

Free Guides - Getting Started with R and Python

Enter your name and email address below and we will email you the guides for R programming and Python.

Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.