Efficient tests of stock return predictability

Conventional tests of the predictability of stock returns could be invalid, that is reject the null too frequently, when the predictor variable is persistent and its innovations are highly correlated with returns. We develop a pretest to determine whether the conventional t-test leads to invalid inference and an efficient test of predictability that corrects this problem. Although the conventional t-test is invalid for the dividend–price and smoothed earnings–price ratios, our test finds evidence for predictability. We also find evidence for predictability with the short rate and the long-short yield spread, for which the conventional t-test leads to valid inference.     

International stock return predictability

We propose a new methodology for predicting international stock returns. Our Bayesian framework performs probabilistic selection of predictors that can shift at multiple unknown structural break dates. The approach generates significantly more accurate forecasts of international stock returns than a range of popular models that are economically meaningful for a risk-averse mean–variance investor. Allowing for regime-specific variable selection reduces considerably the international diversification of an unhedged U.S. investor’s portfolio.     

International stock return predictability: Evidence from new statistical tests

We investigate whether stock returns of international markets are predictable from a range of fundamentals including key financial ratios (dividend-price ratio, dividend-yield, earnings-price ratio, dividend-payout ratio), technical indicators (price pressure, change in volume), and short-term interest rates. We adopt two new alternative testing and estimation methods: the improved augmented regression method and wild bootstrapping of predictive model based on a restricted VAR form. Both methods take explicit account of endogeneity of predictors, providing bias-reduced estimation and improved statistical inference in small samples. From monthly data of 16 Asia-Pacific (including U.S.) and 21 European stock markets from 2000 to 2014, we find that the financial ratios show weak predictive ability with small effect sizes and poor out-of-sample forecasting performances. In contrast, the price pressure and interest rate are found to be strong predictors for stock return with large effect sizes and satisfactory out-of-sample forecasting performance.     

Real-time macroeconomic data and ex ante stock return predictability

We report results on the ex ante predictability of monthly excess stock returns in Germany using real-time and revised macroeconomic data. Our real-time macroeconomic data cover the period 1994-2005. We report that the contribution of real-time macroeconomic data to ex ante stock return predictability is similar to that of revised macroeconomic data. Moreover, the performance of an investor who had to rely on noisy real-time macroeconomic data would have been similar to the performance of an investor who had access to revised macroeconomic data.     

Disagreement and return predictability of stock portfolios

This paper provides evidence that portfolio disagreement measured bottom-up from individual-stock analyst forecast dispersions has a number of asset pricing implications. For the market portfolio, market disagreement mean-reverts and is negatively related to ex post expected market return. Contemporaneously, an increase in market disagreement manifests as a drop in discount rate. For book-to-market sorted portfolios, the value premium is stronger among high disagreement stocks. The underperformance by high disagreement stocks is stronger among growth stocks. Growth stocks are more sensitive to variations in disagreement relative to value stocks. These findings are consistent with asset pricing theory incorporating belief dispersion.     

European business cycles and stock return predictability

This paper finds that the European leading economic indicator, a prime business cycle indicator for the European economies published by the OECD, can strongly predict European stock returns and generate utility gains. Importantly, the predictive power of the European indicator is above and beyond that contained in the country-specific leading indicator. Furthermore, we find that the predictive power of the European indicator is stable.     

Crude oil price volatility and equity return predictability: A comparative out-of-sample study

We evaluate the predictive power afforded by crude oil price volatility relative to widely used variables in the financial literature, such as the dividend yield, earnings-to-price ratio, the default yield spread as well several crude oil price-based variables. From a statistical viewpoint, predictions employing the suggested crude oil price volatility-based measures display a similar pattern as predictions using dividend ratios and interest rates, namely, they have relatively weak out-of-sample power. However, we find that gains in utility for an investor that uses predictions produced under the model employing crude oil price log-realized semivolatilities are statistically significant higher than an investor relying on predictions produced under the competitors as well as the historical average benchmark. We discuss and explain the reasons for our results. Overall, we argue that it is hard not to justify more attention to crude oil price semivolatilities relative to widely used financial and macroeconomic variables.     

Belief-based momentum indicator and stock market return predictability

Li et al. (2022) propose a new momentum indicator that combines past returns and consistent belief information, and show that the indicator positively predicts cross-sectional stock returns. Based on the momentum indicator of Li et al. (2022), we further develop a conditional past return (CPR) indicator that additionally adds the direction information for the investors' consistent belief. We examine the effectiveness of CPR as a predictor for stock market returns. Our evidence shows that CPR significantly and positively predicts future one-month market returns. And CPR provides unique predictive information that is not related to the other popular predictors. The abundant out-of-sample evidence further supports CPR’s predictive ability. Additionally, we detect the asymmetric role of CPR in predicting market returns and find that much of the predictive ability of CPR is attributed to the interaction between the positive past returns and the positive consistent belief.     

A study of cross-industry return predictability in the Chinese stock market

We investigate cross-industry return predictability for the Shanghai and Shenzhen stock exchanges, by constructing 6- and 26- industry portfolios. The dominance of retail investors in these markets, in conjunction with the gradual diffusion of information hypothesis provide the theoretical background that allows us to employ machine learning methods to test for cross-industry predictability. We find that Oil, Telecommunications and Finance industry portfolio returns are significant predictors of other industries. Our out-of-sample forecasting exercise shows that the OLS post-LASSO estimation outperforms a variety of benchmarks and a long–short trading strategy generates an average annual excess return of 13%.     

The skewness risk premium in equilibrium and stock return predictability

In this study, we investigate the skewness risk premium in the financial market under a general equilibrium setting. Extending the long-run risks (LRR) model proposed by Bansal and Yaron (J Financ 59:1481–1509, 2004) by introducing a stochastic jump intensity for jumps in the LRR factor and the variance of consumption growth rate, we provide an explicit representation for the skewness risk premium, as well as the volatility risk premium, in equilibrium. On the basis of the representation for the skewness risk premium, we propose a possible reason for the empirical facts of time-varying and negative risk-neutral skewness. Moreover, we also provide an equity risk premium representation of a linear factor pricing model with the variance and skewness risk premiums. The empirical results imply that the skewness risk premium, as well as the variance risk premium, has superior predictive power for future aggregate stock market index returns, which are consistent with the theoretical implication derived by our model. Compared with the variance risk premium, the results show that the skewness risk premium plays an independent and essential role for predicting the market index returns.     

Option trading after the opening bell and intraday stock return predictability

Prior literature finds that information is reflected in option markets before stock markets, but no study has explored whether option volume soon after market open has predictive power for intraday stock returns. Using novel intraday signed option-to-stock volume data, we find that a composite option trading score (OTS) in the first 30 min of market open predicts stock returns during the rest of the trading day. Such return predictability is greater for smaller stocks, stocks with higher idiosyncratic volatility, and stocks with higher bid–ask spreads relative to their options’ bid–ask spreads. Moreover, OTS is a significantly stronger predictor of intraday stock returns after overnight earnings announcements. The evidence suggests that option trading in the 30 min after the opening bell has predictive power for intraday stock returns.     

A closer look at return predictability of the US stock market: evidence from new panel variance ratio tests

This paper examines the return predictability of the US stock market using portfolios sorted by size, book-to-market ratio and industry. We use novel panel variance ratio tests, based on the wild bootstrap proposed in this paper, which exhibit desirable size and power properties in small samples. We have found evidence that stock returns have been highly predictable from 1964 to 1996, except for a period leading to the 1987 crash and its aftermath. After 1997, stock returns have been unpredictable overall. At a disaggregated level, we find evidence that large-cap portfolios have been priced more efficiently than small- or medium-cap portfolios; and that the stock returns from high-tech industries are far less predictable than those from non-high-tech industries.     

Time varying stock return predictability: Evidence from US sectors

This paper argues that dividend yield stock return predictability is time-varying. We conjecture that such time-variation is linked to the business cycle. Employing monthly data for US sector portfolios we estimate 5-year rolling fixed window predictive regressions. The resulting series of time-varying predictive coefficients is regressed on industrial production growth and a recession dummy. Our results support the view of a negative relationship between predictability and output growth. That is the strength of the predictive relationship between returns and the dividend yield is stronger during contractionary periods, while during expansions the magnitude of the relationship declines.     

Adjusted dividend-price ratios and stock return predictability: Evidence from China

This paper examines the predictive ability of dividend-price ratios on stock returns in the Chinese A-share market. The results show that in both the in-sample and out-of-sample settings, stock returns are positively predicted by the raw dividend-price ratio and multiple adjusted dividend-price ratios over the 2002–2018 period, especially for the pre-2008 period. However, this predictive power disappeared after the China Securities Regulatory Commission (CSRC) released the unique Semi-Mandatory Dividend Rule (the Rule) in 2008, and this sudden decrease in predictive ability has shown no signs of reversing. Tests using the event-study methodology show a reduction in the positive relation between dividend-price ratios and stock returns in the short term, indicating that the Rule has an adverse impact on the signaling effect of dividend announcements. We further demonstrate that the interference of the Rule with the information conveyed by the dividends explains the disappearance of the predictive power of dividend-price ratios. For firms with insufficient cash flow, dividends provide a negative signal of the firms' value after the enactment of the Rule instead of a positive signal of strong future cash flows. Consequently, the Rule has a negative impact on the efficiency of the cash-flow channel for predicting returns and buries the predictive power of dividend-price ratios.     

Out‐of‐sample stock return predictability in emerging markets

This article builds on the widely debated issue of stock return predictability by applying a broad range of predictor variables and comprehensively considering the in‐sample and out‐of‐sample stock return predictability of ten advanced emerging markets. It compares forecasts from models with a single predictor variable, multiple predictor variables and a combination forecast approach. The results confirm the findings of Welch and Goyal (2008) for US data that only a limited number of individual predictor variables are able to deliver significant out‐of‐sample forecasts. However, a combination forecast approach provides statistically and economically significant out‐of‐sample forecast results.     

Stock return predictability and the adaptive markets hypothesis: Evidence from century-long U.S. data

This paper provides strong evidence of time-varying return predictability of the Dow Jones Industrial Average index from 1900 to 2009. Return predictability is found to be driven by changing market conditions, consistent with the implication of the adaptive markets hypothesis. During market crashes, no statistically significant return predictability is observed, but return predictability is associated with a high degree of uncertainty. In times of economic or political crises, stock returns have been highly predictable with a moderate degree of uncertainty in predictability. We find that return predictability has been smaller during economic bubbles than in normal times. We also find evidence that return predictability is associated with stock market volatility and economic fundamentals.     

On the predictability of Chinese stock returns

We examine stock return predictability in China. We take 18 firm-specific variables that have been documented to predict cross-sectional stock returns in the U.S. and examine their relation with stock returns in China for the sample period from 1995 to 2007. We find relatively weak predictability for Chinese stocks. Only five firm-specific variables predict returns in the Chinese market. Tests on U.S. stock returns find that more predictors can explain cross-sectional stock return variation. We test two explanations for the cause of weak returns predictability in China. First, perhaps return predictors in China are less heterogeneously distributed than they are in the U.S. Second, stock prices are less informative in China than they are in the U.S. We find support for both explanations.     

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.     

Profitable predictability in the cross section of stock returns

Haugen and Baker (1996) report that a long-short stock selection strategy based on more than 50 measures of accounting information and past return behavior would have generated excess returns of approximately 3% per month. We find that the Haugen and Baker strategies do not provide attractive returns after transaction costs if an investor already has access to strategy portfolios based on book-to-market and momentum. We also provide an extensive analysis of transaction costs over a long sample and we report results of independent interest to researchers in market microstructure.     

Commonality in the time-variation of stock–stock and stock–bond return comovements

We jointly investigate time-varying comovements between stock returns across countries and between long-term government bond and stock returns within countries. Our focus is on how daily return comovements vary with stock uncertainty, as measured by the implied volatility (IV) from equity index options. Cross-country stock return comovements tend to be stronger (weaker) following high (low) IV days and on days with large (small) changes in IV. Stock–bond return comovements tend to be substantially positive (negative) following low (high) IV days and on days with small (large) changes in IV. A regime-switching analysis also indicates a striking temporal commonality in the stock–stock and stock–bond comovement variations. Our findings bear on understanding the influence of time-varying uncertainty on price formation and the diversification benefits of stock–bond and cross-country stock holdings.