Calculation of Diluted EPS (Convertible Debt)

We have the following data for a company:

  • Net income= $12,000
  • Preferred dividend= $2,000
  • Weighted Average Shares Outstanding= 10,000
  • Preferred Stock Outstanding = 1,000
  • 50 convertible bonds, $1,000 par, 6%. Each bond is convertible into 100 shares

Basic EPS = (12,000 – 2,000)/10,000 = 1

If the convertible bonds are converted into shares, the total new shares issued will be:

\= 50*100 = 5,000

If the convertible bonds are converted into shares, there will be no interest expense. Therefore the net income will increase by = 50*1000*0.06(1-0.40) = 1,800

Diluted EPS = (12,000 – 2,000+1,800)/(10,000+5,000) = 0.78

We should check whether the diluted EPS is less than basic EPS. Only if it is less, the convertible bonds will be considered to be dilutive and will be included in the calculation of dilutive EPS.

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 $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.