Dividend Growth Predictability Research Articles

MIDAS and dividend growth predictability: Revisiting the excess volatility puzzle

AbstractWe examine dividend growth predictability and the excess volatility puzzle across a large sample of international equity markets using a mixed‐frequency data sampling (MIDAS) regression approach. We find that accounting for dividend seasonality under the MIDAS framework significantly improves dividend growth predictability compared to simple regressions with annually aggregated data. Moreover, variance bounds tests that allow for nonstationary dividends consistently fail to reject the market efficiency hypothesis across all countries. Our findings suggest that the common rejection of market efficiency in the literature is most likely driven by the annual aggregation of dividend data as well as by the assumption of stationary dividends.

Local predictability of stock returns and cash flows

Motivated by the present-value framework, this article proposes a novel and flexible semiparametric long-horizon time-varying model to investigate the so-called ‘pockets of predictability’, which refer to local periods in which stock returns or cash flows are significantly predictable. A semiparametric profile method is used to estimate both time-varying and constant parameters. In the empirical studies, the predictive ability of the dividend-price ratio for dividend growth is considerably weaker than its ability to predict stock returns at both short and long horizons. Moreover, dividend smoothing only matters for dividend growth predictability at a low frequency. In addition, localized variance decomposition analysis suggests that the present-value relation is locally valid for most sample periods and that the main driver of the variation in the dividend-price ratio stems from its ability to predict stock returns. Lastly, using the earnings-price ratio produces similar results.

Forecasting dividend growth: The role of adjusted earnings yield

This paper revisits the predictability of dividend growth. Motivated by the dividend partial adjustment model, we decompose the earnings yield into smoothing and residual components. The residual component reflects the variations in the forecast of dividend dynamics and thus forms a powerful predictor of dividend growth. Empirically, the proposed predictor shows significant in-sample predictive power for aggregate dividend growth at both monthly and annual frequencies over several forecast horizons. The regression results are robust to dividend reinvestment strategies and economic status. More importantly, the proposed predictor contains significant out-of-sample predictability, outperforming the historical mean benchmark and a list of popularly used financial and macroeconomic predictors in the literature.

Stock price movements: Evidence from global equity markets

This paper studies how market-level stock price movements respond to changes in expected future aggregate cashflows versus discount rates in individual global equity markets. We find that market-level dividend yields have strong forecasting power for aggregate dividend growth over a short term in most stock markets but their forecasting power becomes weak with investment horizon; their forecasting power for returns tends to exhibit an opposite pattern. The variance decomposition of dividend yields exhibits interesting cross-country heterogeneity. We further find that dividend smoothing and country-level disclosure and investor protection are two important drivers of the diverse predictability patterns across countries. • Short-horizon dividend growth predictability by aggregate dividend yields is generally strong. • Over long horizons aggregate dividend growth predictability goes weak. • Market return predictability by dividend yields exhibits an opposite pattern. • The variance decomposition of dividend yields exhibits cross-country heterogeneity. • Dividend smoothing and disclosure are two important drivers of diverse predictability patterns.

Developing a Regime-Switching Present Value Model: Switching Fundamentals and Bubbles

We develop a present-value model where the fundamental and non-fundamental components switch between distinct regimes. The non-fundamental component is specified as a periodically collapsing bubble of Balke and Wohar [Balke, N. S., & Wohar, M. E. (2009). Market fundamentals versus rational bubbles in stock prices: A Bayesian perspective. Journal of Applied Econometrics, 24(1), 35–75. https://doi.org/10.1002/jae.1025]. The fundamental component is constructed as in van Binsbergen and Koijen [van Binsbergen, J. H., & Koijen, R. S. J. (2010). Predictive regressions: A present-value approach. The Journal of Finance, 65(4), 1439–1471. https://doi.org/10.1111/j.1540-6261.2010.01575.x], by treating the expectations of market fundamentals as latent variables. Unlike existing methods, e.g. [Zhu, X. (2015). Tug-of-war: Time-varying predictability of stock returns and dividend growth. Review of Finance, 19(6), 2317–2358. https://doi.org/10.1093/rof/rfu047; Choi, K. H., Kim, C., & Park, C. (2017). Regime shifts in price-dividend ratios and expected stock returns: A present-value approach. Journal of Money, Credit and Banking, 49(2–3), 417–441. https://doi.org/10.1111/jmcb.12384; Chan, J. C., & Santi, C. (2021). Speculative bubbles in present-value models: A Bayesian Markov-switching state space approach. Journal of Economic Dynamics and Control, 127, 1–26], ours requires no unnecessary approximations, accommodates flexible forms of regime-switching, and the resulting present-value formula is internally consistent.

International evidence on stock returns and dividend growth predictability using dividend yields

ABSTRACT This paper examines stock returns and dividend growth predictability using dividend yields in seven developed markets: United States of America (US), United Kingdom (UK), Japan, France, Germany, Italy, and Spain. Altogether, these countries account for around 85% of the Morgan Stanley Capital International (MSCI) World Index. The use of the long time series with up-to-date data allows the comparison not only between countries, but also across periods, putting into perspective the existence or not of noticeable changes since the 1980’s. The majority of the literature on this topic is US-centered. This emphasis on the US is even more pronounced when it comes to examining the relationship between the dividend unpredictability and dividend smoothing. There is also the need to know if the relationships already documented for the post-Second World War (WWII) period still hold during the last three decades, when stock markets were subjected to a high level of turbulence worldwide. The relationship between dividend yields and returns and dividend growth is central to understand the functioning of capital markets, and has considerable implications for capital asset pricing and investment strategies. Overall, the results show that even for developed capital markets there is no clear pattern on the predictive ability of dividend yields on stock returns and dividend growth, instead these relationships seem to be time-dependent and country-specific. For each country, the predictive ability of the dividend yield is examined in a first-order structural VAR framework by applying bootstrap significance tests and the degree of dividend smoothing is assessed using four partial-adjustment models for the dividend behavior. Additionally, an out-of-sample analysis is conducted using pseudo-R2 and a normal mean squared prediction error (MSPE) adjusted statistic. For the post-WWII period, returns are predictable, but dividends are unpredictable in the US and the UK, while the opposite pattern is observed in Spain and Italy. In Germany, there is some evidence of short-term predictability for both returns and dividends, while in France only returns are predictable. In Japan, neither variable can be forecasted. The dividend smoothing results show that dividends are more persistent in the US and the UK, however, there is no clear connection between dividend smoothness and predictability for the other countries. An important conclusion to retain from the out-of-sample analysis is that the predictability of returns after the WWII, especially present in the US, appeared to have been missing in the last three decades, most probably due to the turmoil experienced by the stock markets during this last period.

The Predictive Power of the Dividend Risk Premium

AbstractWe show that the dividend growth rate implied by the options market is informative about i) the expected dividend growth rate and ii) the expected dividend risk premium. We model the expected dividend risk premium and explore its implications for the predictability of dividend growth and stock market returns. Correcting for the expected dividend risk premium strengthens the evidence for the predictability of dividend growth and stock market returns both in and out of sample. Economically, a market-timing investor who accounts for the time-varying expected dividend risk premium realizes an additional utility gain of 2.02% per year.

Prices and Returns: What Is the Role of Inflation?

We document that the market dividend yield can positively predict future inflation across advanced economies after the fall of the Bretton Woods system. The inflation predictability reinforces the return predictability and reduces the dividend growth predictability. For example, dividend yields forecast nominal returns (but not nominal dividend growth), meanwhile, dividend yields forecast real dividend growth (but not real returns). The same results also hold for the earnings yields. We extend Campbell-Vuolteenaho's (2004) analysis to other industrialized countries whose stock markets are highly integrated, to deal with the processes and few independent observations issues. Hypothesis tests (related to future growth prospect, the discount rate, and behavior bias) suggest the high correlation between expected inflation and the dividend yield is almost entirely due to the correlation between expected inflation and the economy's future growth prospects. The results are robust across different future inflation measures including the long-term nominal government bond yields, and strongly support Fama's (1981) inflation acting as expected real activity proxy hypothesis. Therefore we argue the persistent inflation should be regarded as the state variable and be introduced as the second long-run risk (besides the consumption risk) into the long-run risk model. The estimated model can reproduce both the inflation predictability and the documented asset pricing facts.

The Dog that Did Bark: Evidence on Dividend Growth Predictability

We find that a business-cycle component of the aggregate dividend yield strongly predicts short-term aggregate dividend growth and consumption growth, while its low-frequency counterpart significantly forecasts long-horizon market returns. The dividend yield, as the sum of these two components, has difficulty revealing variations in expected cashflow growth, because its low-frequency component tends to disguise such variations. The low-frequency component, on the other hand, has significant forecasting power for multiperiod returns at horizons of several years to as long as around 20 years—longer than the horizons typically exploited in prior studies that provide weak statistical evidence to challenge multiperiod return predictability.

Dividend growth and return predictability: A long-run re-examination of conventional wisdom

Abstract We re-examine dividend growth and return predictability evidence using 165 years of data from the Brussels Stock Exchange. The conventional wisdom holds that time-varying dividend yield is predominately explained by changes in expected returns and that expected dividend growth is only weakly forecastable. However, we find robust dividend growth predictability evidence in every time period. A lack of dividend smoothing is the most important reason for the disconnect with previous evidence. Furthermore, we find return predictability in the post-World War II period when we adjust the dividend yields for changing index composition, business cycle variation and structural breaks. This is explained by a simultaneous increase in equity duration, induced by an increasing importance of growth stocks.

Understanding time-varying short-horizon predictability✰

Time-varying return predictability should stem either from time-varying dividend growth predictability or from time-varying dividend yield autocorrelation. The decomposition results show that the bulk of the variation in return predictability is due to its negative correlation with time-varying dividend yield autocorrelation, which is in turn positively correlated with investor sentiment. Using a linear regression based on these results, we confirm a significantly negative relation between investor sentiment and stock return predictability, after controlling for macroeconomic factors, dividend growth, and structural breaks. These findings suggest that investor sentiment is an important determinant of time-varying short-horizon predictability.

Dividend Growth and Return Predictability: A Long-Run Re-Examination of Conventional Wisdom

We re-examine dividend growth and return predictability evidence using 165 years of data from the Brussels Stock Exchange. The conventional wisdom holds that time-varying dividend yield is predominately explained by changes in expected returns and that expected dividend growth is only weakly forecastable. However, we find robust dividend growth predictability evidence in every time period. A lack of dividend smoothing is the most important reason for the disconnect with previous evidence. Furthermore, we find return predictability in the post–World War II period when we adjust the dividend yields for changing index composition, business cycle variation and structural breaks. This is explained by a simultaneous increase in equity duration, induced by an increasing importance of growth stocks.

Control-ownership disparity and stock market Predictability: Evidence from Korean chaebols

We use Korean firm-level data to examine whether the predictive ability of log dividend yields depends on the disparity between control and ownership rights. We find that dividend growth predictability via the log dividend yield grows as the disparity between control and ownership rights increases. However, we find that log dividend yields have no significant predictive power for stock returns. Our results are generally consistent with the US firm-level results in Vuolteenaho (2002) and provide a further explanation of why the predictability of log dividend yields for dividend growth differs across firms.

Dividend growth and equity premium predictability

This paper studies dividend growth predictability without restricting the conditioning information set to dividend yield alone. We highlight that predictability crucially hinges on how dividend growth is constructed. While there is little predictability in the market-reinvested dividend growth, the pure dividend growth is significantly predictable both in-sample and out-of-sample by a number of economic fundamentals. This strong pure dividend growth predictability leads to improved equity premium prediction under the present-value framework.

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

We consistently show that in large equity markets, the dividend–price ratio is significantly related to the growth of future dividends. To uncover this relation, we use monthly dividends and a mixed data sampling technique, which allows us to address within-year seasonality. Our approach avoids the use of overlapping observations and at the same time reduces the impact of price volatility on the dividend–price ratio. An empirical analysis using market-level data from the United States, United Kingdom, Canada, and Japan strongly supports the dividend growth predictability hypothesis, suggesting that time aggregation of dividends eliminates significant information.

Dividend cuts and predictability

This study provides a plausible economic interpretation to examine why the dramatic reversal of return and dividend growth predictability by dividend yield (DY), as proposed by Chen (J Financ Econ 92: 128–151, 2009), occurs in the U.S. stock market. Because severe dividend cuts took place mostly in the prewar period and almost disappeared in the postwar period, we argue that abnormally high dividend cuts can drive a threshold effect on log DY, thereby triggering dividend growth predictability when log DY is above the threshold. However, this predictive ability completely disappears when log DY is below the threshold. Empirically, we find the existence of a log DY threshold point, above which future returns, as well as dividend growth, are significantly negatively correlated with log DY, yet below which future returns are significantly positively correlated with log DY—but lacking predictability for dividend growth.

Dividend Growth Predictability and Stock Price Movement

This paper studies dividend growth predictability without restricting conditioning information set to dividend yield alone. We highlight that predictability crucially hinges on how dividend growth is constructed. Dividend growth without reinvestment is significantly predictable both in-sample and out-of-sample by a number of economic fundamentals. The results are robust across subsamples. When dividend growth predictability is properly taken account of, it leads to a different picture of variance decomposition of returns. Contrary to the prevailing views, the cash flow news is important in driving stock price movement in aggregate level after incorporating dividend growth predictability.

The Dog Has Barked for a Long Time: Dividend Growth Is Predictable

The Campbell-Shiller present value identity implies that (i) the dividend-price ratio should forecast returns or dividend growth, and (ii) any other predictor of returns should also forecast dividend growth, and vice versa. Prior literature investigates (i) and finds that dividend growth appears unpredictable based on forecasting regressions with the dividend-price ratio. We investigate (ii) and combine out-of-sample dividend-growth forecasts from 14 individual predictive regressions based on common return predictors. Encompassing and structural break tests show these individual return predictors contribute disparate and unstable univariate forecasts of dividend growth. Combination forecast methods of 14 common return predictors overcome these econometric problems and generate robust out-of sample predictability of dividend growth over the entire post-war period as well as over most sub-periods. The dividend-growth forecasts coupled with the dividend-price ratio also significantly forecast excess returns out-of-sample.

Dividend Yields, Dividend Growth, and Return Predictability in the Cross Section of Stocks

Dividend Yields, Dividend Growth, and Return Predictability in the Cross Section of Stocks

Time-Varying Predictability for Stock Returns, Dividend Growth and Consumption Growth

Using a state-space model, this paper examines time variation in the predictive regressions for stock returns, dividend growth and consumption growth. Moreover, we linked time variation explicitly to movements in economic factors that can account for risk and cash flow. Results support the view that stock return predictability is enhanced when risk is high (negative growth, higher volatility and positive growth/return covariance). In contrast, dividend growth and consumption growth predictability is enhanced during economic expansions. These results are supported by subsample analysis and a vector autoregressive approach. Furthermore, these latter exercises may uncover differences in the stock return predictability relationship when viewed over different time horizons. Overall, the paper contributes to the literature by highlighting the different nature of returns predictability, which arises largely through the risk channel, and dividend and consumption growth predictability, which arise through the cash flow channel. Copyright © 2015 John Wiley & Sons, Ltd.