Stock Splits and Reverse Stock Splits

A stock split refers to a situation where a company decides to split each share into multiple shares. A 3-for-1 stock split means each old stock is split into 3 new stocks. The impact is that the total outstanding shares increase, but the value of each share declines proportionately.

Important Points

  • Similar to stock dividends, stock splits have no impact on the total shareholder value or the shareholders’ wealth.
  • Two-for-one and three-for-one are the most commonly used stock splits, although a company may decide any fraction.
  • Companies generally go for stock splits in order to keep their stocks in a certain price range ($20 to $80 is preferred).
  • Theoretically, the price of the stock will fall proportionately after the stock split. However, the academic research shows that the stock splits have a positive impact on the company and the actual stock price may be more than its theoretical value.
  • Stock splits reduce market liquidity of stocks because the stock prices are now low which makes the percentage brokerage high.

Reverse Stock Splits

Reverse stock splits are exactly the opposite of stock splits. In this case multiple shares are combined into fewer shares. Here also the key motive is to keep the stock prices within the optimal price band of $20 to $80. So, if a company’s stock price is below this level, the company may go for reverse stock split to increase the stock price.

Impact on Financial Ratios

Stock splits and reverse stock splits have no impact on liquidity ratios, financial leverage ratios, as there is no change in the company’s assets or equity.

Learn the skills required to excel in data science and data analytics covering R, Python, machine learning, and AI.

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.

Saylient AI Logo

Take the Next Step in Your Data Career

Join our membership for lifetime unlimited access to all our data analytics and data science learning content and resources.