Earnings and Expected Returns

The aggregate dividend payout ratio forecasts excess returns on both stocks and corporate bonds in postwar U.S. data. High dividends forecast high returns. High earnings forecast low returns. The correlation of earnings with business conditions gives them predictive power for returns; they contain information about future returns that is not captured by other variables. Dividends and earnings contribute substantial explanatory power at short horizons. For forecasting long-horizon returns, however, only (scaled) stock prices matter. Forecasts of low long-horizon stock returns in the mid-1990s are caused not by earnings or dividends, but by high stock prices.     

Do Decomposed Financial Ratios Predict Stock Returns and Fundamentals Better?

We investigate the prediction of excess returns and fundamentals by financial ratios, which include dividend‐price ratios, earnings‐price ratios, and book‐to‐market ratios, by decomposing financial ratios into a cyclical component and a stochastic trend component. We find both components predict excess returns and fundamentals. Cyclical components predict increases in future stock returns, while stochastic trend components predict declines in future stock returns in long horizons. This helps explain previous findings that financial ratios in the absence of decomposition find weak predictive power in short horizons and some predictive power in long horizons. We also find both components predict fundamentals.     

Predicting firm level stock returns: Implications for asset pricing and economic links

We examine the predictive ability of stock price ratios, stock return dispersion and distribution measures for firm level returns. Analysis typically focusses on market level returns, however, for the underlying asset pricing model to hold, firm-level predictability should be present. Additionally, we examine the economic content of predictability by considering whether the predictive coefficient has the theoretically correct sign and whether it is related to future output growth. While stock returns reflect investor expectations regarding future economic conditions, they are often too noisy to act as predictor. We use the time-varying predictive coefficient as it reflects investor confidence in the predictive relation. Results suggest that a subset of stock price ratios have predictive power for individual firm stock returns, exhibit the correct coefficient sign and has predictive power for output growth. Each of these ratios has a measure of fundamentals divided by the stock price and has a positive relation with stock returns and output growth. This implies that as investors expect future economic conditions to improve and earnings and dividends to rise, so expected stock returns will increase. This supports the cash flow channel as the avenue through which stock return predictability arises.     

Intrinsic bubbles and Granger causality in the S&P 500: Evidence from long-term data

Results of research on whether changes in earnings can predict future stock returns are inconclusive. We add to this debate by using long-term data from 1871 to 2004 to examine the predictive power of changes in earnings in periods of intrinsic bubbles and in periods absent intrinsic bubbles. Our results show that accounting for bubbles is important in whether changes in earnings can predict future stock returns. In periods of no bubble, we find that changes in earnings Granger-cause future returns, whereas in periods of bubble, this Granger causality from changes in earnings to future returns cannot be found. We conclude that changes in earnings can predict future stock returns, but only in periods absent bubbles.     

Predicting dividends in log-linear present value models

In a present value model, high dividend yields imply that either future dividend growth must be low, or future discount rates must be high, or both. While previous studies have largely focused on the predictability of future returns from dividend yields, dividend yields also strongly predict future dividends, and the predictability of dividend growth is much stronger than the predictability of returns at a one-year horizon. Inference from annual regressions over the 1927–2000 sample imputes over 85% of the variation of log dividend yields to variations in dividend growth. Point estimates of the predictability of both dividend growth and discount rates are stronger when the 1990–2000 decade is omitted.     

Stock Return Predictability: Is it There?

We examine the predictive power of the dividend yields for forecastingexcess returns, cash flows, and interest rates. Dividend yieldspredict excess returns only at short horizons together withthe short rate and do not have any long-horizon predictive power.At short horizons, the short rate strongly negatively predictsreturns. These results are robust in international data andare not due to lack of power. A present value model that matchesthe data shows that discount rate and short rate movements playa large role in explaining the variation in dividend yields.Finally, we find that earnings yields significantly predictfuture cash flows. (JEL C12, C51, C52, E49, F30, G12)     

Predicting dividends in log-linear present value models

In a present value model, high dividend yields imply that either future dividend growth must be low, or future discount rates must be high, or both. While previous studies have largely focused on the predictability of future returns from dividend yields, dividend yields also strongly predict future dividends, and the predictability of dividend growth is much stronger than the predictability of returns at a one-year horizon. Inference from annual regressions over the 1927–2000 sample imputes over 85% of the variation of log dividend yields to variations in dividend growth. Point estimates of the predictability of both dividend growth and discount rates are stronger when the 1990–2000 decade is omitted.     

Negative earnings,positive earnings and stock return predictability: An empirical examination of market timing

We examine the predictive ability of earnings-price ratios or yields for the S&P 500 index. We decompose the aggregate earnings-price ratio into its positive and negative components (“winners” vs “losers”) and find that the negative component has the most predictive ability. We also find that the earnings-price measures forecast both future returns and earnings growth. Our models display substantial variation in explanatory power over time with forecast power resurfacing in the latter 1990s. We conclude that to the extent that earnings-price yields predict future S&P 500 returns, the negative earnings component is the driving factor.     

Forecasting Japanese Stock Returns with Financial Ratios and Other Variables

This paper extends the previous analyses of the forecastability of Japanese stock market returns in two directions. First, we carefully construct smoothed market price–earnings ratios and examine their predictive ability. We find that the empirical performance of the price–earnings ratio in forecasting stock returns in Japan is generally weaker than both the price–earnings ratio in comparable US studies and the price dividend ratio. Second, we also examine the performance of several other forecasting variables, including lagged stock returns and interest rates. We find that both variables are useful in predicting aggregate stock returns when using Japanese data. However, while we find that the interest rate variable is useful in early subsamples in this regard, it loses its predictive ability in more recent subsamples. This is because of the extremely limited variability in interest rates associated with operation of the Bank of Japan’s zero interest policy since the late 1990s. In contrast, the importance of lagged returns increases in subsamples starting from the 2000s. Overall, a combination of logged price dividend ratios, lagged stock returns, and interest rates yield the most stable performance when forecasting Japanese stock market returns.     

Expected returns and expected dividend growth

We investigate a consumption-based present-value relation that is a function of future dividend growth and find that changing forecasts of dividend growth are an important feature of the post-war U.S. stock market, despite the failure of the dividend–price ratio to uncover such variation. In addition, dividend forecasts are found to covary with changing forecasts of excess stock returns over business cycle frequencies. This covariation is important because positively correlated fluctuations in expected dividend growth and expected returns have offsetting effects on the log dividend–price ratio. The market risk premium and expected dividend growth thus vary considerably more than is apparent using the log divided–price ratio alone as a predictive variable.     

The information content of implied skewness and kurtosis changes prior to earnings announcements for stock and option returns

We use option prices to examine whether changes in stock return skewness and kurtosis preceding earnings announcements provide information about subsequent stock and option returns. We demonstrate that changes in jump risk premiums can lead to changes in implied skewness and kurtosis and are also associated with the mean and variability of the stock price response to the earnings announcement. We find that changes in both moments have strong predictive power for future stock returns, even after controlling for implied volatility. Additionally, changes in both moments predict call returns, while put return predictability is primarily linked to changes in skewness.     

Modelling Time‐Variation in the Stock Return‐Dividend Yield Predictive Equation

Using data for forty markets, this paper examines the nature and possible causes of time‐variation within the stock return‐dividend yield predictive regression. The results in this paper show that there is significant time‐variation in the predictive equation for returns and that such variation is linked to economic and market factors. Furthermore, the strength and nature of those links are themselves time‐varying. The inclusion of this time‐variation in the predictive equation increases the predictive power compared to the standard constant parameter predictive model. Evidence is also reported for time‐varying dividend growth predictability. Long‐horizon predictability is also examined with evidence reported that the nature of the factors affecting time‐varying predictability changes with horizon. The results here, while directly contributing to the returns predictability debate, in particular regarding its existence and source, may also inform the discussion that links time‐varying expected returns (and risk premium) to economic factors.     

Consumption growth and time-varying expected stock returns

When the consumption growth rate is measured based upon fourth quarter data, it tracks predictable variation in future excess stock returns. Low fourth quarter consumption growth rates predict high future excess stock returns such that expected returns are high at business cycle troughs and low at business cycle peaks. The consumption growth rate loses predictive power when it is measured based upon other quarters. This is consistent with the insight of Jagannathan and Wang [2007. Journal of Finance 62, 1623–1661] that investors tend to review their consumption and investment plans during the end of each calendar year, and at possibly random times in between. The consumption growth rate measured based upon fourth quarter data is a much stronger predictive variable than benchmark predictive variables such as the dividend–price ratio, the term spread, and the default spread.     

Inflation Illusion and Post-Earnings-Announcement Drift

This paper examines the cross‐sectional implications of the inflation illusion hypothesis for the post‐earnings‐announcement drift. The inflation illusion hypothesis suggests that stock market investors fail to incorporate inflation in forecasting future earnings growth rates, and this causes firms whose earnings growths are positively (negatively) related to inflation to be undervalued (overvalued). We argue and show that the sensitivity of earnings growth to inflation varies monotonically across stocks sorted on standardized unexpected earnings (SUE) and, consistent with the inflation illusion hypothesis, show that lagged inflation predicts future earnings growth, abnormal returns, and earnings announcement returns of SUE‐sorted stocks. Interestingly, controlling for the return predictive ability of inflation weakens the ability of lagged SUE to predict future returns of SUE‐sorted stocks.     

Four centuries of return predictability

We combine annual stock market data for the most important equity markets of the last four centuries: the Netherlands and UK (1629–1812), UK (1813–1870), and US (1871–2015). We show that dividend yields are stationary and consistently forecast returns. The documented predictability holds for annual and multi-annual horizons and works both in- and out-of-sample, providing strong evidence that expected returns in stock markets are time-varying. In part, this variation is related to the business cycle, with expected returns increasing in recessions. We also find that, except for the period after 1945, dividend yields predict dividend growth rates.     

The predictive power of investment and accruals

We test whether investment explains the accrual anomaly by splitting total accruals into investment-related and “nontransaction” accruals, items such as depreciation and asset write-downs that do not represent new investment expenditures. The two types of accruals have very different predictive power for firm performance, not just for future earnings but also for future cash flow and stock returns. Most importantly, nontransaction accruals have the strongest negative predictive slopes for earnings and stock returns, contrary to the predictions of the investment hypothesis. A long-short portfolio based on nontransaction accruals has a significant average return of 0.71 % monthly from 1972 to 2010 and remains profitable at the end of the sample when returns on other accrual strategies decline. Our results suggest that nontransaction accruals are the least reliable component of accruals and show that a significant portion of the accrual anomaly cannot be explained by investment.     

When does the dividend–price ratio predict stock returns?

If the dividend–price ratio becomes I(1) while stock returns are I(0), the unbalanced predictive regression makes the predictability test more likely to indicate that the dividend–price ratio has no predictive power. This might explain why the dividend–price ratio evidences strong predictive power during one period, while it exhibits weak or no predictive power at other times. Using international data, this paper demonstrates that the dividend–price ratio generally has predictive power for stock returns when both are I(0). However, this paper also shows that the dividend–price ratio loses its predictive power when it becomes I(1). The results are shown to be robust across countries.     

Using earnings forecasts to simultaneously estimate firm-specific cost of equity and long-term growth

A growing body of literature in accounting and finance relies on implied cost of equity (COE) measures. Such measures are sensitive to assumptions about terminal earnings growth rates. In this paper we develop a new COE measure that is more accurate than existing measures because it incorporates endogenously estimated long-term growth in earnings. Our method extends Easton et al. (J Account Res, 40, 657–676, 2002) method of simultaneously estimating sample average COE and growth. Our method delivers COE (growth) estimates that are significantly positively associated with future realized stock returns (future realized earnings growth). Moreover, the predictive ability of our COE measure subsumes that of other commonly used COE measures and is incremental to commonly used risk characteristics. Our implied growth measure fills the void in the earnings forecasting literature by robustly predicting earnings growth beyond the five-year horizon.     

The Gilt-Equity Yield Ratio and the Predictability of UK and US Equity Returns

A number of financial variables have been shown to be effective in explaining the time-series of aggregate equity returns in both the UK and the US. These include, inter alia , the equity dividend yield, the spread between the yields on long and short government bonds, and the lagged equity return. Recently, however, the ratio between the long government bond yield and the equity dividend yield – the gilt-equity yield ratio – has emerged as a variable that has considerable explanatory power for UK equity returns. This paper compares the predictive ability of the gilt-equity yield ratio with these other variables for UK and US equity returns, providing evidence on both in-sample and out-of-sample performance. For UK monthly returns, it is shown that while the dividend yield has substantial in-sample explanatory power, this is not matched by out-of sample forecast accuracy. The gilt-equity yield ratio, in contrast, performs well both in-sample and out-of-sample. Although the predictability of US monthly equity returns is much lower than for the UK, a similar result emerges, with the gilt-equity yield ratio dominating the other variables in terms of both in-sample explanatory power and out-of-sample forecast performance. The gilt-equity yield ratio is also shown to have substantial predictive ability for long horizon returns.     

What do dividend reductions signal?

Dividend reductions have long been considered a “last resort” action for firm managers. Managerial reluctance to reduce dividends emanates from the view that dividend drops signal managerial pessimism regarding future earnings. Contrary to expectations, studies show that earnings rebound significantly following a dividend reduction; yet investors react negatively to the dividend-drop announcement. We present an explanation for the anomalous behavior of earnings and returns around the time of a dividend drop. Our evidence suggests that a reduction in a firm's established dividend coincides with a decrease in the value of the firm's real options. Earnings rebound following the dividend reduction due to the savings that result as the firm allows growth options to expire; however, announcement period returns suggest that investors recognize the lost value associated with the forthcoming expiration of growth options.