Price-dividend Ratio Research Articles

Dividend-Price Ratios and Stock Returns: International Evidence

A widely replicated result, using U.S. data, is that dividend-price ratios predict future returns, not future dividend growth. This is evidence of stock-return predictability, and is contrary to the original interpretation of the efficient-market hypothesis. The author argues that this pre-dictability may be an artifact of the American economy’s remarkably stable real growth. This article examines the relation between dividend yields, future returns, and dividend growth, using current international data. It concludes that, in some countries, dividend-price ratios predict future returns; in other countries, they predict future dividend growth; and in still other countries, they predict a combination of the two. The variation, furthermore, is related to the volatility of real dividend growth.

Expected Returns and Dividend Growth Rates Implied by Derivative Markets

The dividend-price ratio is a noisy proxy for expected returns when expected dividend growth is time-varying. This paper uses a new and forward-looking measure of dividend growth extracted from S&P 500 futures and options to correct the dividend-price ratio for changes in expected dividend growth. Over January 1994 through June 2011, dividend growth implied by derivative markets reliably forecasts future dividend growth, and the corrected dividend-price ratio predicts S&P 500 returns substantially better than the standard dividend-price ratio, in-sample and out-of-sample. Time-varying expected dividend growth is important to explain price movements, especially because it is highly correlated with expected returns.

A BAYESIAN ANALYSIS OF WEAK IDENTIFICATION IN STOCK PRICE DECOMPOSITIONS

This paper employs the state-space model to reexamine the fundamental issue in finance of whether it is the expected returns or the expected dividends growth that is primarily responsible for stock price variations. We use Bayesian methods to show that there is a substantial uncertainty about the contributions of expected returns and expected dividends to fluctuations in the price–dividend ratio when the aggregate returns and dividends data are used. The substantial uncertainty of the contributions results from the model being weakly identified. Our finding challenges the notion long held in the existing literature that it is the expected returns that contribute most to price–dividend variations.

Time-Disaggregated Dividend-Price Ratio and Dividend Growth Predictability in Large Equity Markets

Even in large equity markets, the dividend-price ratio is significantly related with the growth of future dividends. In order to uncover this relationship, we use monthly dividends and a mixed data sampling technique which allows us to cope with within-year seasonality. We reduce the effect of price volatility on the dividend-price ratio by applying a simple smoothing technique, and we identify the component of the smoothed dividend-price ratio that offers predictive power. An empirical analysis using market level data from U.S., U.K., Canada and Japan strongly supports the dividend growth predictability hypothesis, suggesting that time-aggregation of dividends eliminates significant information.

Solving Asset Pricing Models with Stochastic Volatility

This paper provides a closed-form solution for the price-dividend ratio in a standard asset pricing model with stochastic volatility. The solution is useful in allowing comparisons among numerical methods used to approximate the non-trivial closed-form.

Solving Asset Pricing Models with Stochastic Volatility

This paper provides a closed-form solution for the price-dividend ratio in a standard asset pricing model with stochastic volatility. The solution is useful in allowing comparisons among numerical methods used to approximate the non-trivial closed-form.

News Shocks and Asset Prices

We study the importance of anticipated shocks (news) for understanding the comovement between macroeconomic quantities and asset prices. We find that four-quarter anticipated investment shocks are an important source of fluctuations for macroeconomic variables: they account for about half of the variance in hours and investment. However, it is the four-quarter anticipated productivity shock that is driving a large fraction of consumption and most of the price-dividend ratio fluctuations. These productivity news are key for the model to reproduce the empirical tendency for stock-market valuations and excess returns to lead the business cycle. Importantly, a model that does not use asset price information in the estimation would downplay the role of productivity news; in this case, the model implies that return moves (almost) completely contemporaneously with the economic activity, counterfactually with the data.

Cash-Flow or Discount-Rate Risk? Evidence from the Cross Section of Present Values

Realized returns comprise (ex-ante) expected returns plus (ex-post) innovations, and consequently both expected returns and returns innovations can be broken down into components reflecting fluctuations in cash flow (CF) and discount rate (DR). I use a present-value model to identify the CF and DR risk factors which are latent from the time series and cross sections of price-dividend ratios. This setup accommodates models where CF risk dominates, like Bansal and Yaron (2004), and models where DR risk dominates, like Campbell and Cochrane (1999). I estimate the model on portfolios, which capture several of the most common cross-sectional anomalies, and decompose the expected and unexpected returns into CF and DR components along both time-series and cross-sectional dimensions. I find that (1) the DR risk is more likely to explain the variations of expected returns, (2) the CF risk drives the variations of unexpected returns, and (3) together they account for over 80% of the cross-sectional variance of the average stock returns.

Asset Pricing Under Uncertainty About Shock Propagation

We analyze the equilibrium in a two-tree (sector) economy with two regimes. The output of each tree is driven by a jump-diffusion process, and a downward jump in one sector of the economy can (but need not) trigger a shift to a regime where the likelihood of future jumps is generally higher. Furthermore, the true regime is unobservable, so that the representative Epstein-Zin investor has to extract the probability of being in a certain regime from the data. These two channels help us to match the stylized facts of countercyclical and excessive return volatilities and correlations between sectors. Moreover, the model reproduces the predictability of stock returns in the data without generating consumption growth predictability. The uncertainty about the state also reduces the slope of the term structure of equity. We document that heterogeneity between the two sectors with respect to shock propagation risk can lead to highly persistent aggregate price-dividend ratios. Finally, the possibility of jumps in one sector triggering higher overall jump probabilities boosts jump risk premia while uncertainty about the regime is the reason for sizeable diffusive risk premia.

Tails, Fears, and Equilibrium Option Prices

Recent empirical evidence suggests that the compensation for rare events accounts for a large fraction of the average equity and variance premia. I replicate this fact in a parsimonious consumption-based asset pricing model based on a (generalized) disappointment averse investor and conditionally Gaussian fundamentals. In the model, regime-switches in endowment volatility interact with the investor’s tail aversion to produce large endogenous return jumps and a realistic implied volatility smirk. The presence of multiple shock frequencies in volatility gives the variance premium the ability to predict returns over short horizons and the price-dividend ratio the ability to predict returns over long horizons.

Accounting Ratios and the Cross-Section of Expected Stock Returns

Clean-surplus accounting implies that a firm's stock return can be decomposed into a function of the firm's return on equity, book-to-market equity ratio, and dividend-price ratio. Consequently, the variation in these ratios across firms should be indicative of cross-sectional variation in conditional expected returns. Although this prediction can be tested via cross-sectional regressions, the analysis suggests that ordinary-least-squares estimates of the regression coefficients are sensitive to extreme return observations. To address this issue, I develop an outlier-resistant approach for estimating the regression coefficients. The outlier-resistant estimates provide substantial evidence of the predicted cross-sectional relation between accounting ratios and expected returns.

Net-Net Number: Implications & Conclusions

“Perhaps one could even determine whether the market level was getting too high or too low by counting the number of issues selling below working capital value.” Benjamin Graham.Most are aware of modern market valuation indicators include the trailing, median P/E ratio, Q ratio (market price relative to replacement cost) and the dividend-price ratio among others. Leaving the utility of these leading indicators aside, there is a method which remains altogether ignored and under-appreciated by the vast majority of market participants today. That is, the number of net-nets (companies valued below their net working capital minus all liabilities, ignoring the property and other assets completely) present at any given time on domestic US markets.The modest objective of this paper is to present the implications of this oft-overlooked indicator relative to market over/under valuation as a whole in the past (1929-2011) and therefrom help draw conclusions as to its ultimate utility in the present.

Learning, large deviations and rare events

We examine the role of generalized stochastic gradient constant gain (SGCG) learning in generating large deviations of an endogenous variable from its rational expectations value. We show analytically that these large deviations can occur with a frequency associated with a fat-tailed distribution even though the model is driven by thin-tailed exogenous stochastic processes. We characterize these large deviations, driven by sequences of consistently low or consistently high shocks and then apply our model to the canonical asset pricing framework. We demonstrate that the tails of the stationary distribution of the price–dividend ratio will follow a power law.

Dividend sensitivity to economic factors, stock valuation, and long-run risk

In this paper, we develop a theoretical stock valuation model that takes into account the long-run sensitivity of dividends to various economic factors. Our valuation process integrates the multidimensionality of uncertainty, as well as the long-run concept of risk (recently proposed in the literature). More precisely, we demonstrate that a stock’s long-run dividend growth is negatively related to its current dividend–price ratio and linearly related to N sensitivity coefficients, given by the long-run sensitivity between dividends and economic factors. Then, we show that the equilibrium price of a stock is a function of its current dividend, long-run dividend growth, and N risk parameters.

Disappearing Dividends: Implications for the Dividend–Price Ratio and Return Predictability

The conventional dividend–price ratio is highly persistent, and the literature reports mixed evidence on its role in predicting stock returns. We argue that the decreasing number of firms with a traditional dividend‐payout policy is responsible for these results, and develop a model in which the long‐run relationship between the dividends and stock price is time varying. An adjusted dividend–price ratio that accounts for the time‐varying long‐run relationship is considerably less persistent. Furthermore, the predictive regression model that employs the adjusted dividend–price ratio as a regressor outperforms the random‐walk model. These results are robust with respect to the firm size.

Arbitrage Theory with State-Price Deflators

The aim of this article is to develop some mathematical results for the existence of asset price bubbles, which is consistent with the martingale analysis of financial markets. More specifically, this article studies the relation between the divergence of the sum of dividend-price ratios and the absence of bubbles. The framework used describes a contemporary model of a securities market built in an environment with both uncertainty and a countable number of trading dates. The market allows trading of a finite number of corporate securities. In this context, no arbitrage condition is characterized by the existence of a state-price deflator across an infinite time horizon.

Predictability in the Long Run Risks Model

I analyse predictability of returns by the dividend-price ratio in the long-run risks model of Bansal and Yaron (2004). I find that the model does not generate predictability patterns consistently with the data. I connect this shortcoming to specific features of the long-run risks processes.

Dividend-Price Ratios and Stock Returns: Another Look at the History

A critical question for investors is the extent to which the expected returns on common stock are predictable. One of the prime pieces of evidence supporting the hypothesis that returns are predictable is that regressions of future returns on dividend-price ratios are highly significant, but future dividend growth is unrelated to the ratio. This article presents an alternate interpretation of these regression results that is consistent with the original version of the efficient market hypothesis, which holds that expected returns are unpredictable. The analysis is based on the economic history of the United States. The historical analysis not only provides an alternative interpretation of the regression results, but also highlights the importance of analyzing the specific historical events responsible for generating financial data.

Composition Changes of Publicly Traded Firms: Implications for the Dividend-Price Ratio and Return Predictability

This article documents how the changing composition of U.S. publicly traded firms has prompted a decline in the long-run mean of the aggregate dividend-price ratio, most notably since the 1970s. Adjusting the dividend–price ratio for such changes resolves several issues with respect to the predictability of stock market returns: The adjusted dividend-price ratio is less persistent, in-sample evidence for predictability is more pronounced, there is greater parameter stability in the predictive regression (particularly during the 1990s), and there is evidence of out-of-sample predictability.

Dividend Growth Predictability: Isn't It There?

We re-visit a puzzling result that in U.S. post-WW II data the dividend price ratio can predict aggregate returns but not dividend growth. We find that predictive regressions are sensitive to the method used to aggregate firm-level data. Using value weighted firm-level data we find strong evidence for dividend growth predictability in the post-WW II period. We explore the reasons behind the differences in predictability due to different weighting methods. We find that these differences in predictability are related to the fact, in the data, that it is not always the largest firms that pay the largest dollar dividends or earnings.