How Do Analysts Select an Equity Valuation Model?

While valuing a stock, the analysts will need to make a choice about which valuation model should they use.

This is a difficult but important choice for arriving at the correct valuation. Some analysts will in fact value a stock using multiple models to arrive at a range of stock value.

Provided below are a few simple guidelines than an analyst can use while selecting a valuation model:

  1. As we know, the Gordon Growth model assumes a constant growth rate for dividends. This model is suitable for companies that are fairly stable and mature, and pay regular dividends. Also, these businesses should be non-cyclical in nature.
  2. For companies that are currently exhibiting a high growth rate for dividends, but expect to provide a more sustainable constant growth rate in the future should be valued using the multi-stage dividend discount models. In the multi-stage model, there can be many variations. For example, some companies may initially have high growth rate of dividends, followed by a low growth rate, followed by constant growth rate (three phases). The valuation model can be adjusted according to the requirements.
  3. For companies that do not pay dividends, the analysts will have to rely on Free Cash flow to Equity (FCFE) for valuation. In this case, analysts need to ascertain the growth rate for earnings instead of dividends.
  4. Analysts can also use valuation models based on price multiples in other cases.

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.