Dividend Regressions: January 2020
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.
- Market
Debt to Capital = Debt/ (Debt + Market Value of Equity): If you have
market value for debt, use it. If not, use book value of debt and market
value of equity.
US Regression: Dividend Yield
![](../Budimage/USYldRegr1.png)
US Regression Output
![](../Budimage/USYldRegr2.png)
US Regression: Dividend Payout
![](../Budimage/USPayoutRegr1.png)
Regression Output
![](../Budimage/USPayoutRegr2.png)
Global Regression: Dividend Yield
![](../Budimage/GlobalYildRegr1.png)
Regression Output
![](../Budimage/GlobalYldRegr2.png)
Global Regression: Dividend Payout
![](../Budimage/GlobalPayoutRegr1.png)
Regression Output
![](../Budimage/GlobalPayoutRegr2.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 =3.548 - 0.205 (1.20) -12.347 (.10) = 2.06 or 2.06%
- Expected
Dividend payout ratio = 0.949 - .293 (1.20) - 1.69 (.10) = .42 or 42%
If your
predicted value is less than zero, your predicted dividend payout ratio is
zero.