Voting Systems: Statutory Voting and Cumulative Voting

Common shares provide voting rights to the shareholders which provide the shareholders the ability to participate in major corporate decisions such as election of directors, mergers and acquisitions, selection of auditors, etc. When electing the members of the board of directors, there are two commonly used methods of voting: Statutory Voting and Cumulative Voting.

Under the statutory voting system, directors are elected one at a time. Each director is voted on one at a time. Therefore, a shareholder may give any one candidate, as a maximum, only a number of votes equal to the number of shares owned. Statutory voting favors majority shareholders.

Under cumulative voting system, total number of votes each shareholder may cast = (# of shares owned) x (# of directors to be elected). With cumulative voting, a shareholder may give all the votes he/she holds to a single candidate. Cumulative voting favors minority shareholders.

Example

  • A company has two shareholders: “A” (owns 50 shares); “B” (owns 249 shares). There are 5 directors to be elected and 7 candidates running (T, U, V, W, X, Y, Z). “A” wants candidate Z to be on the board. B wants candidates T, U, V, W, and Y.
  • Using statutory voting: “A” has 50 votes and “B” has 249 votes. Since each director is voted on one at a time “B” will be able to vote in all his candidates and “A” will not be able to vote in his candidate.
  • Using cumulative voting:

“A” has 50 x 5 = 250 votes (all for Z)

“B” has 249 x 5 = 1,245 votes (÷ 5 = 249 for T, U, V, W, and Y)

  • Therefore, Z wins the most votes. “B” cannot arrange votes to block Z.

Related Downloads

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 $39 (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.