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Author: Eugene F. Fama
Publisher:
ISBN:
Category :
Languages : en
Pages : 32
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Author: Eugene F. Fama
Publisher:
ISBN:
Category :
Languages : en
Pages : 32
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Author: Robert J. Hodrick
Publisher:
ISBN:
Category : Dividends
Languages : en
Pages : 41
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Book Description
Alternative ways of conducting inference and measurement for long-horizon forecasting are explored with an application to dividend yields as predictors of stock returns. Monte Carlo analysis indicates that the Hansen and Hodrick (1980) procedure is biased at long horizons, but the alternatives perform better. These include an estimator derived under the null hypothesis as in Richardson and Smith (1989), a reformulation of the regression as in Jegadeesh (1990), and a vector autoregression (VAR) as in Campbell and Shiller (1988), Kandel and Stambaugh (1988), and Campbell (1991). The statistical properties of long-horizon statistics generated from the VAR indicate interesting patterns in expected stock returns.
Author: Robert J. Hodrick
Publisher:
ISBN:
Category :
Languages : en
Pages : 55
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Book Description
Alternative ways of conducting inference and measurement for long-horizon forecasting are explored with an application to dividend yields as predictors of stock returns. Monte Carlo analysis indicates that the Hansen and Hodrick (1980) procedure is biased at long horizons, but the alternatives perform better. These include an estimator derived under the null hypothesis as in Richardson and Smith (1989), a reformulation of the regression as in Jegadeesh (1990), and a vector autoregression (VAR) as in Campbell and Shiller (1988), Kandel and Stambaugh (1988), and Campbell (1991). The statistical properties of long-horizon statistics generated from the VAR indicate interesting patterns in expected stock returns.
Author: Zhi Da
Publisher:
ISBN:
Category : Dividends
Languages : en
Pages : 57
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According to the dynamic version of the Gordon growth model, the long-run expected return on stocks, stock yield, is the sum of the dividend yield on stocks plus some weighted average of expected future growth rates in dividends. We construct a measure of stock yield based on sell-side analysts' near-term earnings forecasts that predicts US stock index returns well, with an out-of-sample R-squared that is consistently above 2% at monthly frequency over our sample period. Stock yield also predicts future stock index returns in the US and other G7 countries and returns of US stock portfolios formed by sorting stocks based on firm characteristics, at various horizons. The findings are consistent with a single dominant factor driving expected returns on stocks over different holding periods. That single factor extracted from the cross section of stock yields using the Kelly and Pruitt (2013) partial regressions method predicts stock index returns better. The performance of the Binsbergen and Koijen (2010) latent factor model for forecasting stock returns improves significantly when stock yield is included as an imperfect observation of expected return on stocks. Consistent with folk wisdom, stock returns are more predictable coming out of a recession. Our measure performs as well in predicting stock returns as the implied cost of capital, another common stock yield measure that uses additional information.
Author:
Publisher:
ISBN:
Category : Investments
Languages : en
Pages : 596
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Author: Sharon Wai Man Wong
Publisher:
ISBN:
Category : Dividends
Languages : en
Pages : 56
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Author: Allan G. Timmermann
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Author: Allan G. Timmermann
Publisher:
ISBN:
Category : Finance
Languages : en
Pages : 9
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Author: Paulo F. Maio
Publisher:
ISBN:
Category :
Languages : en
Pages : 46
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There is a generalized conviction that variation in dividend yields is exclusively related to expected returns and not to expected dividend growth - e.g. Cochrane's presidential address (Cochrane (2011)). We show that this pattern, although valid for the aggregate stock market, is not true for portfolios of small and value stocks, where dividend yields are related mainly to future dividend changes. Thus, the variance decomposition associated with aggregate dividend yield has important heterogeneity in the cross-section of equities. Our results are robust to different forecasting horizons, econometric methodology used (long-horizon regressions or first-order VAR), and an alternative decomposition based on excess returns.
Author: Charles Henry Dow
Publisher:
ISBN:
Category : Speculation
Languages : en
Pages : 108
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