Dividend Regressions: January 2022
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
![](../Budimage/divyldUS1.jpg)
Regression Output
![](../Budimage/divyldUS2.jpg)
US Regression: Dividend Payout
![](../Budimage/divPayoutUS1.jpg)
Regression Output
![](../Budimage/divPayoutUS2.jpg)
Global Regression: Dividend Yield
![](../Budimage/divuldGlobal1.jpg)
Regression Output
![](../Budimage/divyldGlobal2.jpg)
Global Regression: Dividend Payout
![](../Budimage/divPayoutGlobal1.jpg)
Regression Output
![](../Budimage/divPayoutGlobal2.jpg)
- 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 =1.76 -0.024 (10) - .17 (1.20) = 1.32 or 1.32%
- Expected
Dividend payout ratio = 54.10 - 0.72 (10) - 10.91 (1.20)= 33.80 or 33.80%
If your
predicted value is less than zero, your predicted dividend payout ratio is
zero.