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56
Stock return predictability: Is it there?
, 2001
"... We ask whether stock returns in France, Germany, Japan ... by three instruments: the dividend yield, the earnings yield and the short rate. The predictability regression is suggested by a present value model with earnings growth, payout ratios and the short rate as state variables. We find the short ..."
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Cited by 127 (5 self)
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We ask whether stock returns in France, Germany, Japan ... by three instruments: the dividend yield, the earnings yield and the short rate. The predictability regression is suggested by a present value model with earnings growth, payout ratios and the short rate as state variables. We find the short rate to be the only robust shortrun predictor of excess returns, and find little evidence of excess return predictability by earnings or dividend yields across all countries. There is no evidence of longhorizon return predictability once we account for finite sample influence. Crosscountry predictability is stronger than predictability using local instruments. Finally, dividend and earnings yields predict future cashflow growth
On the importance of measuring payout yield: Implications for empirical asset pricing
 Journal of Finance
, 2006
"... We investigate the empirical implications of using various measures of payout yield rather than dividend yield for asset pricing models. We find statistically and economically significant predictability in the time series when payout (dividends plus repurchases) and net payout (dividends plus repurc ..."
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Cited by 123 (9 self)
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We investigate the empirical implications of using various measures of payout yield rather than dividend yield for asset pricing models. We find statistically and economically significant predictability in the time series when payout (dividends plus repurchases) and net payout (dividends plus repurchases minus issuances) yields are used instead of the dividend yield. Similarly, we find that payout (net payout) yields contains information about the cross section of expected stock returns exceeding that of dividend yields, and that the high minus low payout yield portfolio is a priced factor. WHILE THE IRRELEVANCE THEOREM of Miller and Modigliani (1961) implies that there is no reason to suspect that dividends play a role in determining equity price levels or equity returns, the theorem is silent on the usefulness of dividends in explaining these variables. It is then, perhaps, not surprising that there is a considerable literature exploiting the properties of dividends and dividend yields to better understand the fundamentals of asset pricing both in the time series and in the cross section. Motivation for the former comes from variations of the Gordon growth model in which dividend yields can be written as the return minus the dividend’s growth rate (see, e.g., Fama and French (1988)), from consumptionbased asset pricing models in which the firm’s dividends covary with aggregate consumption (e.g., Lucas (1978) and Shiller (1981)), and so forth. Additional motivation comes from crosssectional heterogeneity in tax, agency, and asymmetric information considerations (e.g.,
Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?
, 2004
"... Goyal and Welch (2006) argue that the historical average excess stock return forecasts future excess stock returns better than regressions of excess returns on predictor variables. In this paper we show that many predictive regressions beat the historical average return, once weak restrictions are i ..."
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Cited by 117 (3 self)
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Goyal and Welch (2006) argue that the historical average excess stock return forecasts future excess stock returns better than regressions of excess returns on predictor variables. In this paper we show that many predictive regressions beat the historical average return, once weak restrictions are imposed on the signs of coefficients and return forecasts. The outofsample explanatory power is small, but nonetheless is economically meaningful for meanvariance investors. Even better results can be obtained by imposing the restrictions of steadystate valuation models, thereby removing the need to estimate the average from a short sample of volatile stock returns. Towards the end of the last century, academic finance economists came to take seriously the view that aggregate stock returns are predictable. During the 1980’s a number of papers studied valuation ratios, such as the dividendprice ratio, earningsprice ratio, or smoothed earningsprice ratio. Valueoriented investors in the tradition of Graham and Dodd (1934) had always asserted that high valuation ratios are an indication of an undervalued stock market and should predict high subsequent returns, but these ideas did not carry much weight in the academic literature until authors such as Rozeff (1984), Fama and French (1988), and Campbell and Shiller (1988a,b) found that valuation ratios are positively correlated with subsequent returns and that the implied predictability of returns is substantial at longer horizons. Around the same time, several papers pointed out that yields on short and longterm Treasury and corporate bonds are correlated with subsequent stock returns [Fama and Schwert
Efficient tests of stock return predictability
, 2004
"... Conventional tests of the predictability of stock returns may be invalid, that is reject the null too frequently, when the predictor variable is persistent and its innovations are highly correlated with returns. We develop a pretest to determine whether the conventional ttest leads to invalid infer ..."
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Cited by 99 (8 self)
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Conventional tests of the predictability of stock returns may be invalid, that is reject the null too frequently, when the predictor variable is persistent and its innovations are highly correlated with returns. We develop a pretest to determine whether the conventional ttest leads to invalid inference and an efficient test of predictability that corrects this problem. Although the conventional ttest is invalid for the dividendprice and smoothed earningsprice ratios, we find evidence for predictability using our test. We also find evidence for predictability with the short rate and the longshort yield spread, for which the conventional ttest leads to valid inference.
THE MYTH OF LONGHORIZON PREDICTABILITY
, 2005
"... The prevailing view in finance is that the evidence for longhorizon stock return predictability is significantly stronger than that for short horizons. We show that for persistent regressors, a characteristic of most of the predictive variables used in the literature, the estimators are almost perf ..."
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Cited by 35 (0 self)
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The prevailing view in finance is that the evidence for longhorizon stock return predictability is significantly stronger than that for short horizons. We show that for persistent regressors, a characteristic of most of the predictive variables used in the literature, the estimators are almost perfectly correlated across horizons under the null hypothesis of no predictability. For example, for the persistence levels of dividend yields, the analytical correlation is 99% between the 1 and 2year horizon estimators and 94 % between the 1 and 5year horizons, due to the combined effects of overlapping returns and the persistence of the predictive variable. Common sampling error across equations leads to ordinary least squares coefficient estimates and R 2 s that are roughly proportional to the horizon under the null hypothesis. This is the precise pattern found in the data. The asymptotic theory is corroborated, and the analysis extended by extensive simulation evidence. We perform joint tests across horizons for a variety of explanatory variables, and provide an alternative view of the existing evidence. I.
Hybrid and SizeCorrected Subsample Methods
, 2007
"... This paper considers the problem of constructing tests and confidence intervals (CIs) that have correct asymptotic size in a broad class of nonregular models. The models considered are nonregular in the sense that standard test statistics have asymptotic distributions that are discontinuous in so ..."
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Cited by 31 (12 self)
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This paper considers the problem of constructing tests and confidence intervals (CIs) that have correct asymptotic size in a broad class of nonregular models. The models considered are nonregular in the sense that standard test statistics have asymptotic distributions that are discontinuous in some parameters. It is shown in Andrews and Guggenberger (2005a) that standard fixed critical value, subsample, and b<n bootstrap methods often have incorrect size in such models. This paper introduces general methods of constructing tests and CIs that have correct size. First, procedures are introduced that are a hybrid of subsample and fixed critical value methods. The resulting hybrid procedures are easy to compute and have correct size asymptotically in many, but not all, cases of interest. Second, the paper introduces sizecorrection and “plugin” sizecorrection methods for fixed critical value, subsample, and hybrid tests. The paper also introduces finitesample adjustments to the asymptotic results of Andrews and Guggenberger (2005a) for subsample and hybrid methods and employs these
Filtering Out Expected Dividends and Expected Returns
, 2007
"... This paper suggests a new state space approach to analysis of stock return predictability. Acknowledging that expected returns and expected dividends are unobservable, the Kalman filter technique is used to extract them from the observed history of realized dividends and returns. This approach expli ..."
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Cited by 19 (0 self)
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This paper suggests a new state space approach to analysis of stock return predictability. Acknowledging that expected returns and expected dividends are unobservable, the Kalman filter technique is used to extract them from the observed history of realized dividends and returns. This approach explicitly accounts for the variation in expected dividend growth and allows to make estimates more robust to structural breaks in the means of dividend growth and returns. The constructed predictor outperforms the dividendprice ratio both in and out of sample, providing statistically and economically significant forecasts. The finite sample likelihood ratio test reliably rejects the hypothesis of constant expected returns.
Optimal Median Unbiased Estimation of Coefficients on Highly Persistent Regressors.
, 2005
"... ABSTRACT. This paper derives an optimal estimator for the slope coefficient on highly persistent and predetermined regressors in an otherwise standard linear regression. Optimality pertains to the class of procedures that are median unbiased irrespectively of the degree of persistence. It holds for ..."
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Cited by 12 (0 self)
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ABSTRACT. This paper derives an optimal estimator for the slope coefficient on highly persistent and predetermined regressors in an otherwise standard linear regression. Optimality pertains to the class of procedures that are median unbiased irrespectively of the degree of persistence. It holds for a wide class of monotone loss functions. The optimality statement generalizes to confidence sets. The estimator, which is based on inversion of the JanssonMoreira
Covariancebased Orthogonality Tests for Regressors with Unknown Persistence. Econometric Theory,
, 2007
"... Abstract This paper develops a new test of orthogonality based on a zero restriction on the covariance between the dependent variable and the predictor. The test provides a useful alternative to regressionbased tests when conditioning variables have roots close or equal to unity. In this case stan ..."
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Cited by 10 (1 self)
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Abstract This paper develops a new test of orthogonality based on a zero restriction on the covariance between the dependent variable and the predictor. The test provides a useful alternative to regressionbased tests when conditioning variables have roots close or equal to unity. In this case standard predictive regression tests can suffer from welldocumented size distortion. Moreover, under the alternative hypothesis, they force the dependent variable to share the same order of integration as the predictor, whereas in practice the dependent variable is often stationary while the predictor may be nearnonstationary. By contrast, the new test does not enforce the same orders of integration and is therefore capable of detecting alternatives to orthogonality that are excluded by the standard predictive regression model. Moreover, the test statistic has a standard normal limit distribution for both unit root and localtounity conditioning variables, without prior knowledge of the localtounity parameter. If the conditioning variable is stationary, the test remains conservative and consistent. Thus the new test requires neither size correction nor unit root pretest. Simulations suggest good small sample performance. As an empirical application, we test for the predictability of stock returns using two persistent predictors, the dividendpriceratio and shortterm interest rate. JEL Classification: C12,C22