Evidence Of Stock Return Predictability Research Articles

Stock Returns and Valuation Ratios at Sector Level in South Africa: The Regime-switch Modelling Approach

There is mounting evidence of stock return predictability based on valuation ratios across various stock markets. Most studies in this regard assume that the link between stock returns and valuation ratios is constant and linear. Yet, return predictability may vary according to the prevailing market regime. Accordingly, this study investigated whether the dividend and price-earnings valuation ratios predict returns on six sector indices on the Johannesburg Stock Exchange and whether that predictability is dependent on the prevailing market regime. The study employed a Markov regime-switching model over a sample period spanning from 1996:01 to 2018:12. The results showed that in most sectors, predictability was present, and its significance was dependent on whether the market was in a bullish or bearish regime. These findings are useful to investors who use valuation ratios to predict returns and adjust portfolios in various sectors across different market regimes on the South African market.

Developed markets’ business cycle dynamics and time-variation in emerging markets’ asset returns

This paper empirically studies the predictability of emerging markets’ stock returns by business cycle variables and the role of developed markets’ business cycle dynamics in this respect. The evidence shows that the link between business cycles and future stock market returns among emerging markets is considerably weaker than among developed markets. By contrast, I find strong evidence of stock return predictability by the respective country’s dividend-price ratio. This latter finding could reflect that variation in dividend-price ratios potentially reflects both the temporary impact of “hot money” inflows on emerging markets’ asset prices and rational expectations of future returns.

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.

A refined consumption–wealth ratio and its role on time-varying consumption risk

This paper takes a deeper look at the measurement of the consumption–wealth ratio and analyzes its ability to capture variations in expected future stock returns. I find evidence of stock return predictability by taking a different approach than predictive regressions.

Reconciling the Return Predictability Evidence

Evidence of stock return predictability by financial ratios is still controversial, as documented by inconsistent results for in-sample and out-of-sample regressions and by substantial parameter instability. This paper 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 forecasting relationship of adjusted price ratios and future returns is statistically significant and stable over time. We also show that shifts in the steady-state are responsible for the parameter instability and poor out-of-sample performance of unadjusted price ratios that are found in the data. 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.

Reconciling the Return Predictability Evidence

Evidence of stock-return predictability by financial ratios is still controversial, as docu- mented by inconsistent results for in-sample and out-of-sample regressions and by substan- tial 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 in-sample 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 in-sample return forecastability hard to exploit out-of-sample. The uncertainty of estimating the size of steady-state 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)

A New Application of Exact Nonparametric Methods to Long-Horizon Predictability Tests

Empirical results from long-horizon regression tests have been influential in the finance literature. Yet, it has come to be understood that traditional long-horizon tests may be unreliable in finite samples when regressors are persistent and when the horizon is long relative to sample size. Recent research has provided valid alternative inference procedures in long-horizon regression in the case for which the regressor follows a near-unit root autoregressive process. However, in small samples, such processes may sometimes be difficult to distinguish with confidence from other persistent data generating processes, such as those displaying long-memory or structural breaks. In this paper, we demonstrate a simple means by which existing nonparametric sign and signed rank tests may be applied to provide exact inference in long-horizon predictive tests, without requiring any modeling assumptions on the regressor. Employing this robust approach, we find evidence of stock return predictability at moderate horizons using short-term interest rates, but little evidence of either short or long-run predictability using dividend-price ratios.

The Myth of Long-Horizon Predictability

The prevailing view in finance is that the evidence for long-horizon 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 the persistence levels of dividend yields, the analytical correlation is 99% between the 1- and 2-year horizon estimators and 94% between the 1- and 5-year horizons. 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. We perform joint tests across horizons for a variety of explanatory variables and provide an alternative view of the existing evidence. (JEL G12, G14, C12) Over the last two decades, the finance literature has produced growing evidence of stock return predictability, though not without substantial debate. The strongest evidence cited so far comes from long-horizon stock returns regressed on variables such as dividend yields, term structure slopes, and credit spreads, among others. A typical view is expressed in Campbell, Lo, and MacKinlay’s (1997, p.268) standard textbook for empirical financial economics, The Econometrics of Financial Markets: At a horizon of 1-month, the regression results are rather unimpressive: The R 2 statistics never exceed 2%, and the t-statistics exceed 2 only in the post-World War II subsample. The striking fact about the table is how much stronger the results become when one increases the horizon. At a 2-year horizon the R 2 statistic is 14% for the full sample ... at a 4-year horizon the R 2 statistic is 26% for the full sample.

Reconciling the Return Predictability Evidence In-Sample Forecasts, Out-of-Sample Forecasts, and Parameter Instability*

Evidence of stock return predictability by financial ratios is still controversial, as documented by inconsistent results for in-sample and out-of-sample regressions and by substantial parameter instability. This paper 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 forecasting relationships of adjusted price ratios and future returns is statistically significant, stable over time, and present in out-of-sample tests. We also show that shifts in the steady-state are responsible for the parameter instability and poor out-of sample performance of unadjusted price ratios that are found in the data. 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.

Cash Distributions and Returns

Discounted cash flow analysis suggests that high cash-flow-to-price ratios should predict high future stock return, low future cash flow growth, or both. Existing studies on the predictive power of the dividend-price ratio, however, produce evidence largely inconsistent with this prediction. In this paper, we address this issue by focusing on the total cash distributions that include both dividends and share repurchases net of seasoned equity offerings. Utilizing a long time series of the total-cash-distributions-to-price (tp) ratio constructed from CRSP data since 1927, we establish strong and persistent evidence of stock return predictability at the annual horizon. Based on a wide variety of evaluation methods, the tp ratio is both statistically and economically significant in predicting future stock market returns, and serves as a pervasive state proxy.