Stock Prices, Earnings and Expected Dividends
By John Y. Campbell, Robert J. Shiller. 1988
Long historical averages of real earnings help forecast present values of future real dividends. With aggregate U.S. stock market data (1871-1986), a vector-autoregressive forecast of the present value of future dividends is, for each year, roughly a weighted average of moving-average earnings and current real price, with between two thirds and three fourths of the weight on the earnings measure. We develop the implications of this for the present-value model of stock prices and for recent results that long-horizon stock returns are highly forecastable.
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Allan G. Timmermann
- P. R. Hansen
- John Y. Campbell
- Tim Bollerslev
- Ralph S. J. Koijen
- David E. Rapach
- Michael W. McCracken
- Sydney C. Ludvigson
Citations in the corpus
- Sufficient Forecasting Using Factor Models (2015, neutral): “Prominent examples include asset return predictability, where we could use the cross section of book-to-market ratios to forecast aggregate market returns (Campbell and Shiller, 1988; Polk et al., 2006; Kelly and Pruitt, 2013).”
- Is there a risk–return trade‐off? Evidence from high‐frequency data (2006, unknown): “(1987), Campbell (1987), Chou (1988), Scruggs (1998), Baillie and DeGennaro (1990), Nelson (1991), Campbell and Hentschel (1992), Chan et al. (1992), Chou et al.”
- Choice of Sample Split in Out-of-Sample Forecast Evaluation (2012, methodology): “It is a long-standing issue whether returns on a broad U.S. stock market portfolio can be predicted using simple regression models, see, e.g., Keim & Stambaugh (1986), Campbell & Shiller (1988), Fama & French (1988), and Campbell & Yogo (2006).”
- Multifactor models and their consistency with the ICAPM (2012, unknown): “We also use the market dividend-to-price ratio (DY) (Fama and French, 1988, 1989; Campbell and Shiller, 1988a), and the aggregate price–earnings ratio (PE) (Campbell and Shiller, 1988b; Campbell and Vuolteenaho, 2004), both for the Standard and Poors (S&P) 500 index.”
- Advances in Forecasting Under Instability (2012, unknown): “Campbell (1987), Campbell and Shiller (1988), Bekaert and Hodrick (1992), Fama and French (1988), Perez-Quiros and Timmermann (2000) and Pesaran and Timmermann (1995) have found in-sample predictability in stock returns.”
- Nominal Exchange Rates and Mon-etary Fundamentals: Evidence from a Small Post-Bretton Woods Sample (2001, unknown): “…short-horizon predictive regression studied by Mark (1995), Berkowitz and Giorgianni (1997), Groen (1997), Kilian (1997), and Berben and van Dijk (1998) in connection with exchange rates and by Fama and French (1988), Campbell and Shiller (1988), and Hodrick (1992) in the study of stock returns.”
- A tale of two option markets: Pricing kernels and volatility risk ☆ (2014, unknown): “By the standard log-linearization approach following Campbell and Shiller (1988), we have rc,t+1 = κ0 + κ1wt+1 − wt +∆ct+1, (28) where the price–wealth ratio wt is conjectured to be affine in the state vector:”
- Robust econometric inference for stock return predictability (2011, unknown): “Following standard notational convention, we de ne the short run and long run covariance matrices associated with the innovations "t and ut in (1), (2) as follows: "" = E ("t" 0 t) ; "u = E ("tu 0 t) ; uu = E (utu 0 t) (6)”
- Econometric Tests of Asset Price Bubbles: Taking Stock (2008, background): “In a later strand of the variance bounds literature, Campbell and Shiller (1988, 1989) provide a log linear approximation to the dividend/price ratio and estimate a vector autoregression system allowing for time-variation in the discount rates.”
- Aggregate Earnings and Asset Prices (2009, methodology): “On the one hand, some volatility studies nd evidence suggesting that cash- ow variation is mostly idiosyncratic and diversi able (e.g., Campbell and Shiller, 1988a, 1988b; Campbell, 1991; and Vuolteenaho, 2002).”
- Robust out-of-sample inference (2000, methodology): “For the second model I follow Campbell and Shiller (1988) and use the earnings}price ratio and a constant to predict excess returns. Shiller (1984) also compares the predictability of dividend yields to the predictability of earnings-price ratios for the S & P 500 composite.”