- Equity Analysis Part 2 - Introduction
- Porter’s Five Competitive Forces
- Industry Analysis
- Supply and Demand Analysis
- Financial Projections in Emerging Markets
- Cost of Capital in Emerging Markets
- Cash Flows: Dividends vs. Free Cash Flows vs. Residual Income
- Dividend Discount Model (DDM)
- Gordon Growth Model (GGM)
- Present Value of Growth Opportunities (PVGO)
- GGM, Leading P/E Ratio, and Trailing P/E Ratio
- Multi-Stage Dividend Discount Models
- H-Model for Valuing Growth
- Sustainable Growth Rate
Cash Flows: Dividends vs. Free Cash Flows vs. Residual Income
When calculating the present value of a company, an analyst can choose between dividends, free cash flows, and residual income to derive the stock’s intrinsic price. Each of these cash flows has advantages and drawbacks.
Dividends
These direct cash payments are a key component of an investor’s returns.
Dividend Advantages: Typically more stable than earnings; small individual shareholders cannot influence dividends, so dividend based valuation may be most appropriate from their perspective.
Dividend Disadvantages: A lot of companies do not pay dividends, but opt to reinvest 100% of earnings; different countries have different dividend cultures and dividend tax policies, so dividend valuation presents some inconsistencies in an international context.
Free Cash Flows
CFA focuses on two types of free cash flows for valuation – free cash flow to the firm and free cash flow to equity.
Free cash flows are appropriate when the company pays no dividend, pays an unsustainable dividend, cash flows track company profits, and/or the investor is large and wants the perspective of a controlling interest.
Residual Income (RI)
RI attempts to capture the extra value that an investor can receive beyond opportunity cost.
RI = Net Income – (rce * Book Value of Equity beginning of period)
Data Science in Finance: 9-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)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.