Understanding Initial Public Offering with an Example

In the previous article we looked at the process of initial public offering. Let’s now take an example to understand how the maths and numbers in an IPO work.

Let’s say that a fictitious company Sound Electronics comes out with an IPO in which it raises $300 million by selling 100 million ordinary shares at a price of $3 per ordinary share.

Let’s say that the company has raised money earlier also and after the IPO has total 250 million shares outstanding.

The company receives $50 million in gross proceeds. This means they sold total 16,666,667 shares at the rate of $3 per share. The balance number of shares i.e., 83,333,333 (100,000,000 - 16,666,667) are sold by the founders.

Since the company sold 16,666,667 new shares, there were 233,333,333 (250,000,000 - 16,666,667) outstanding before the IPO. In terms of percentages, the founders sold 83,333,333/233,333,333 = 35.7% of the company.

If the net proceeds were $46,500,000, the company paid $3,500,000 (7%) as cost of placement.

Let’s say when the trading commenced for the stock on the stock exchange on which it was listed, the stock opened at $3.10 and closed at $3.20 by the end of the day.  The average returns that students made on the first day of trading would be ($3.20 - $3)/$3 = 6.67%.

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.