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279
The Dog That Did Not Bark: A Defense of Return Predictability", Review of financial Studies
, 2008
"... If returns are not predictable, dividend growth must be predictable, to generate the observed variation in divided yields. I find that the absence of dividend growth predictability gives stronger evidence than does the presence of return predictability. Longhorizon return forecasts give the same st ..."
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Cited by 169 (11 self)
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If returns are not predictable, dividend growth must be predictable, to generate the observed variation in divided yields. I find that the absence of dividend growth predictability gives stronger evidence than does the presence of return predictability. Longhorizon return forecasts give the same strong evidence. These tests exploit the negative correlation of return forecasts with dividendyield autocorrelation across samples, together with sensible upper bounds on dividendyield autocorrelation, to deliver more powerful statistics. I reconcile my findings with the literature that finds poor power in longhorizon return forecasts, and with the literature that notes the poor outofsample R2 of returnforecasting regressions. (JEL G12, G14, C22) Are stock returns predictable? Table 1 presents regressions of the real and excess valueweighted stock return on its dividendprice ratio, in annual data. In contrast to the simple random walk view, stock returns do seem predictable. Similar or stronger forecasts result from many variations of the variables and data sets. Economic significance
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
The empirical riskreturn relation: a factor analysis approach
, 2007
"... Existing empirical literature on the riskreturn relation uses a relatively small amount of conditioning information to model the conditional mean and conditional volatility of excess stock market returns. We use dynamic factor analysis for large datasets to summarize a large amount of economic info ..."
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Cited by 82 (12 self)
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Existing empirical literature on the riskreturn relation uses a relatively small amount of conditioning information to model the conditional mean and conditional volatility of excess stock market returns. We use dynamic factor analysis for large datasets to summarize a large amount of economic information by few estimated factors, and find that three new factors termed “volatility,” “risk premium,” and “real” factors contain important information about onequarterahead excess returns and volatility not contained in commonly used predictor variables. Our specifications predict 1620 % of the onequarterahead variation in excess stock market returns, and exhibit stable and statistically significant outofsample forecasting power. We also find a positive conditional riskreturn correlation.
Presidential Address: Discount Rates
 Journal of Finance
, 2011
"... Discountrate variation is the central organizing question of current assetpricing research. I survey facts, theories, and applications. Previously, we thought returns were unpredictable, with variation in pricedividend ratios due to variation in expected cashflows. Now it seems all pricedividend ..."
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Cited by 79 (2 self)
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Discountrate variation is the central organizing question of current assetpricing research. I survey facts, theories, and applications. Previously, we thought returns were unpredictable, with variation in pricedividend ratios due to variation in expected cashflows. Now it seems all pricedividend variation corresponds to discountrate variation. We also thought that the crosssection of expected returns came from the CAPM. Now we have a zoo of new factors. I categorize discountrate theories based on central ingredients and data sources. Incorporating discountrate variation affects finance applications, including portfolio theory, accounting, cost of capital, capital structure, compensation, and macroeconomics. ASSET PRICES SHOULD EQUAL expected discounted cashflows. Forty years ago, Eugene Fama (1970) argued that the expected part, “testing market efficiency,” provided the framework for organizing assetpricing research in that era. I argue that the “discounted ” part better organizes our research today. I start with facts: how discount rates vary over time and across assets. I turn
Nieuwerburgh, “Reconciling the Return Predictability Evidence
 InSample Forecasts, OutofSample Forecasts, and Parameter Instability”, Review of Financial Studies, forthcoming
, 2006
"... Evidence of stockreturn predictability by financial ratios is still controversial, as documented by inconsistent results for insample and outofsample regressions and by substantial parameter instability. This article shows that these seemingly incompatible results can be reconciled if the assu ..."
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Cited by 56 (2 self)
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Evidence of stockreturn predictability by financial ratios is still controversial, as documented by inconsistent results for insample and outofsample regressions and by substantial parameter instability. This article shows that these seemingly incompatible results can be reconciled if the assumption of a fixed steady state mean of the economy is relaxed. We find strong empirical evidence in support of shifts in the steady state and propose simple methods to adjust financial ratios for such shifts. The insample forecasting relationship of adjusted price ratios and future returns is statistically significant and stable over time. In real time, however, changes in the steady state make the insample return forecastability hard to exploit outofsample. The uncertainty of estimating the size of steadystate shifts rather than the estimation of their dates is responsible for the difficulty of forecasting stock returns in real time. Our conclusions hold for a variety of financial ratios and are robust to changes in the econometric technique used to estimate shifts in the steady state. (JEL 12, 14) 1.
Financial Markets and the Real Economy
, 2006
"... I survey work on the intersection between macroeconomics and finance. The challenge is to find the right measure of “bad times,” rises in the marginal value of wealth, so that we can understand high average returns or low prices as compensation for assets’ tendency to pay off poorly in “bad times.” ..."
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Cited by 44 (4 self)
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I survey work on the intersection between macroeconomics and finance. The challenge is to find the right measure of “bad times,” rises in the marginal value of wealth, so that we can understand high average returns or low prices as compensation for assets’ tendency to pay off poorly in “bad times.” I survey the literature, covering the timeseries and crosssectional facts, the equity premium, consumptionbased models, general equilibrium models, and labor income/idiosyncratic risk approaches.
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.