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.     

Credit conditions and stock return predictability

U.S. stock return predictability is analyzed using a measure of credit standards (Standards) derived from the Federal Reserve Board׳s Senior Loan Officer Opinion Survey on Bank Lending Practices. Standards is a strong predictor of stock returns at a business cycle frequency, especially in the post-1990 data period. Empirically, a tightening of Standards predicts lower future stock returns. Standards performs well both in-sample and out-of-sample and is robust to a host of consistency checks. Standards captures stock return predictability at a business cycle frequency and is driven primarily by the ability of Standards to predict cash flow news.     

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.     

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.     

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.     

Interest rate level and stock return predictability

We employ a novel interest rate‐determined model‐switching strategy to forecast stock returns and find persistent predictive ability among a number of economic fundamentals. This strategy switches predictive models based on whether a real‐time interest rate is higher than the mean level interest rate of a look‐back period. The robustly better predictive ability of the new strategy relative to the original OLS regressions suggests that stock returns react more rationally to the variation in economic fundamentals if the contemporaneous interest rates are high. This pattern is consistent with prior literature demonstrating that a high interest rate attenuates speculative demand (Keynes, The general theory of employment, interest, and money, Harcourt Brace, London, 1936), while speculative trading drives stock prices away from their valuation founded on economic fundamentals (Scheinkman & Xiong, Journal of Political Economy, 111, 1183, 2003).     

The financial conglomerate discount: Insights from stock return skewness

Diversified banks (i.e. financial conglomerates) trade often at a discount compared to matched portfolios of specialized stand-alone banks. The existing research explains this evidence primarily with inefficiencies in the cash flow management of banks. This article analyzes the financial conglomerate discount by focusing on the role of expected returns approximated by measures of stock return skewness. Our empirical findings support the hypothesis that diversified banks have less skewed stock returns, i.e. they are more likely to perform badly than non-diversified banks. Due to the lower skewness exposure investors demand higher future returns, thereby lowering corporate value. Although the conglomerate puzzle is observed across industries, the previous literature examines banks separately, as the financial industry is hardly comparable to other sectors. We follow this field of research and show that huge banks quote at a discount as diversification into investment banking activities affects negatively the corporate performance.     

International stock return predictability under model uncertainty

This paper examines return predictability when the investor is uncertain about the right state variables. A novel feature of the model averaging approach used in this paper is to account for finite-sample bias of the coefficients in the predictive regressions. Drawing on an extensive international dataset, we find that interest-rate related variables are usually among the most prominent predictive variables, whereas valuation ratios perform rather poorly. Yet, predictability of market excess returns weakens substantially, once model uncertainty is accounted for. We document notable differences in the degree of in-sample and out-of-sample predictability across different stock markets. Overall, these findings suggest that return predictability is neither a uniform, nor a universal feature across international capital markets.     

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.     

Firm uncertainty and corporate policies: The role of stock return skewness

We study the interaction between firm uncertainty and corporate policies, emphasizing the role of skewness in the distribution of performance shocks reflected in stock returns. Conditional on volatility and other characteristics, firms with more negatively skewed performance shocks adopt more conservative policies, including greater cash holdings, a lower likelihood of dividend payments and increases in payout levels, and less financial leverage. These relationships are significant and robust for asymmetry proxies constructed from stock return innovations, in contrast to results for measures based on accounting performance shocks. This disparity highlights the importance of asymmetries in long-run performance shocks for corporate policy choices.     

Implied volatility skews and stock return skewness and kurtosis implied by stock option prices

The Black-Scholes* option pricing model is commonly applied to value a wide range of option contracts. However, the model often inconsistently prices deep in-the-money and deep out-of-the-money options. Options professionals refer to this well-known phenomenon as a volatility ‘skew’ or ‘smile’. In this paper, we examine an extension of the Black-Scholes model developed by Corrado and Su that suggests skewness and kurtosis in the option-implied distributions of stock returns as the source of volatility skews. Adapting their methodology, we estimate option-implied coefficients of skewness and kurtosis for four actively traded stock options. We find significantly nonnormal skewness and kurtosis in the option-implied distributions of stock returns.     

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.     

The high-volume return premium: evidence from the Chinese stock market

Extreme trading activity contains valuable information about the future evolution of stock prices in the Chinese stock market. Over the next 30 trading days after the initial volume shocks, a high-low volume portfolio earns a net average cumulate return of 2.08% and a high-low volume and size portfolio earns 3.37%, suggesting that there exists a high-volume return premium and that Chinese investors favor high-volume small-size stocks. However, a volume momentum portfolio earns a −1.65% net average cumulative return, indicating that Chinese stocks exhibit a short-run reversal. Portfolio construction, market risk, and firm size do not seem to explain the results.     

Investor attention,psychological anchors,and stock return predictability

Motivated by psychological evidence on limited investor attention and anchoring, we propose two proxies for the degree to which traders under- and overreact to news, namely, the nearness to the Dow 52-week high and the nearness to the Dow historical high, respectively. We find that nearness to the 52-week high positively predicts future aggregate market returns, while nearness to the historical high negatively predicts future market returns. We further show that our proxies contain information about future market returns that is not captured by traditional macroeconomic variables and that our results are robust across G7 countries. Comprehensive Monte Carlo simulations and comparisons with the NYSE/Amex market cap index confirm the significance of these findings.     

Category-specific EPU indices,macroeconomic variables and stock market return predictability

This paper mainly investigates whether the category-specific EPU indices have predictability for stock market returns. Empirical results show that the content of category-specific EPU can significantly predict the stock market return, no matter the individual category-specific EPU index or the principal component of category-specific EPU indices. In addition, the information of category-specific EPU indices can also have higher economic gains than traditional macroeconomic variables, even considering the trading cost and different investor risk aversion coefficients. During different forecasting windows, multi-period forecast horizons and the COVID-19 pandemic, we find the information contained in category-specific EPU indices can have better performances than that of the macroeconomic variables. Our paper tries to provide new evidence for stock market returns based on category-specific EPU indices.     

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.     

The Danish stock and bond markets: comovement,return predictability and variance decomposition

VAR models of the kind developed by Shiller and Beltratti [J. Monetary Econ. 30 (1992) 25] and Campbell and Ammer [J. Finance 48 (1993) 3] are used to analyze the Danish stock and bond markets and their comovement. In contrast to these papers, however, VAR parameter estimates are bias-adjusted and VAR generated statistics, including their standard errors and confidence intervals, are computed using bootstrap simulation. In addition, we modify the Campbell–Ammer variance decomposition such that it can handle returns from a long-term coupon bond. Some parts of the results for the Danish stock and bond markets are quite similar to the US results reported by Shiller and Beltratti and Campbell and Ammer, but other parts stand in sharp contrast to the results for the US. The most important differences between the US and Denmark are that in Denmark news about higher future inflation lead to an increase in expected future stock returns, and that excess stock return news and excess bond return news are negatively correlated.     

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.     

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 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%.