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The Significance of Dividend Yield: Understanding Risk Premiums and Market Forecastability

This analysis explores the relevance of dividend yield (DivY) in evaluating stock market risk premiums and forecasting prices. It discusses the formula for stock pricing based on dividends, underlying growth rates, and risk-free rates. The paper critiques the efficiency of market theories while suggesting that DivY may adhere to bounds, impacting long-term price and dividend forecasting. The implications of share buybacks, intangible investments, demographic shifts, and inflation on market valuations further examine how dividends inform market insights and investor behavior.

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The Significance of Dividend Yield: Understanding Risk Premiums and Market Forecastability

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  1. Dividend yield, does it matter? Based on Fast Forward case.

  2. What is risk premia? • P(t)=Div(t+1)/(r-g)=Div(t) (1+g)/(r-g) • P(t+1)=Div(t+2)/(r-g)=P(t)*(1+g) • Thus, Exp. Returns = DivY *(1+g) +g • Risk premia = DivY *(1+g) +g –Rf • But g Rf => Risk premia  DivY *(1+ Rf)

  3. Another argument: valuation ratios shold be within some bound • Conventional efficient market theory: prices are random walk. • Thus, neither D/P nor P/E ratios should not have any forecasting power. • But if we will accept that for whatever reason DivY should be within some bound, then either numerator or denominator should move in a way that makes market variables forecastable. Then what moves?

  4. Long-term Mean DivY=4.65%

  5. Till next mean crossing...(a bit of cheating...) • Poor job for Div growth forecasting, R2=0.25% • Good job for price growth forecasting R2>30% • Thus, it is DENOMINATOR that brings back DivY within ”decent” range

  6. One year horizon • Div growth is fairly predictable, R2=13% • Price changes are almost not predictable, R2 is about 1%

  7. Ten years Horizon • R2=1% for DivG and 16% for PriceG. • Note that DivG results are not really explainable within eff. Mkt theory at all. • Based on that, within next 10 yrs we should expect 55% drop in S&P

  8. P/MA10(E)

  9. R2 for price growth regression is high (40%) Superior to DivY Forecast is really bad.. Forecasting from P/smoothed E ratio

  10. We cannot forecast productivity growth....

  11. Anything new happened within the last 30 years? Share buybacks • Share repurchases have tax advantages w.r.t. paying simple dividends. • Part of earnings that can be used for dividend payout is now smaller and DivY is underestimated w.r.t. similar number 50 years ago • What difference does it make?

  12. Cole, Helwege & Laster,FAJ 96 Assuming both buybacks and new issues are done at market prices, significant adjustment for DivY is necessary

  13. Adjustment of 0.8% in 96. Problem: most of options are issued at below mkt price. Liang and Sharpe: for 144 S&P500 firms in 97 adjustment is 1.39%, in 98 0.75% Cole, Helwege & Laster,FAJ 96 (2)

  14. Hard assets and financial claims diverge

  15. Intangible investmenst (1) • ”New economy” involves substantial investments in intangibles. • Accounting procedures do count activity to promote web site as expenses but ”...they are really investments”. Hall (2000) called it e-capital. • McGrattan &Prescott : understatement in earnings are about 26%

  16. Intangible investmenst • McGrattan &Prescott : • understatement in earnings are about 26% • Fits only last couple of years • Bond & Cummins: if intangibles are counted as R&D and marketing, then for 459 industrial firms 82-98 still there is no explanation of overvaluation.

  17. Demographic changes • Affluent society is formed • Baby boomers are educated, have money to invest and need to save for retirement (uncertainties related to Social Securities, etc. ) • Thus, one-time shift in risk premium.

  18. Inflation • Responce to inflation is not always rational. Modigliani & Cohn 79: People discount dividends not at real, but at nominal rate. Thus, when inflation is high, stock market is undervalued, and when it is low, stock mkt is overvalued. • Now CPI is low...

  19. International Evidence: Mixed

  20. What else Dividends can tell us? • Let us consider 2 variables: Prices and dividends. • Gordon/Shapiro says, that • P(t)=E(k D(t+k) *(1+r)-k)P*(t) • P*(t)=P(t)+e(t), assume E(e(t)| P(t))=0 • =>cov(P,P*)=cov(P,P)+cov(P, e)=var(P) • -1<Cov(P,P*)/(StdPStdP*)<1 • => Std(P)/Std(P*)<1=> std(P)<Std(P*) • Volatility of forecast (prices) should be smaller than volatility of payouts (dividends). But the relationship is exactly opposite!!!!

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