Dividend Regressions: January 2021
Variables used in the regression
- Dividend
Yield = Dividends per share in most recent year/ Current Stock Price
- Dividend
Payout Ratio = Dividends / Net Income
- Beta: Regression or Bottom up beta
- Expected
Growth in EPS over next 5 years = Consensus analyst estimate (or your own)
of expected growth in EPS
. If you don't have an analyst estimate, use your own estimate
of expected growth.
US Regression: Dividend Yield
![](USDivYld1for2021.png)
US Regression Output
![](USDivYld2fo2021.png)
US Regression: Dividend Payout
![](USDiv1for2021.png)
Regression Output
![](USDiv2for2021.png)
Global Regression: Dividend Yield
![](DivYld1for2021.png)
Regression Output
![](DivYld2for2021.png)
Global Regression: Dividend Payout
![](Div1for2021.png)
Regression Output
![](Div2for2021.png)
- How do I use this regression?
Assume
that you want to estimate the dividend payout ratio for a firm with the following
characteristics, using the US regression:
Regression
beta = 1.20
Expected
Growth in EPS over next 5 years = 10%
- Predicted Values
- Expected Dividend Yield =2.02 + 0.208 (1.20) - .059 (10) = 1.6796 or 1.68%
- Expected
Dividend payout ratio = 68.84 - 12.50(1.20) - 1.30(10) = 40.84 or 40.84%
If your
predicted value is less than zero, your predicted dividend payout ratio is
zero.