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.     

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.     

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.     

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.     

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.     

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.     

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.     

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).     

Liquidity and short-run predictability: Evidence from international stock markets

This study investigates the determinants of short-run predictability in international stock markets, where predictability is defined as the accuracy of the best-combined daily forecasts. Contrary to popular belief, illiquid markets, characterized by high transaction costs and large price impact, are not necessarily highly predictable. Instead, markets with larger trading volume are more predictable, especially after the global financial crisis and in emerging markets. Those with larger market capitalization, steeper upward trends, and positively skewed returns are less predictable. Company financial strength has limited influence. During the COVID-19 pandemic the markets have become more predictable, with stronger price trends. Emerging markets are less predictable when relatively over- or undervalued.     

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.     

In-sample vs. out-of-sample tests of stock return predictability in the context of data mining

We undertake an extensive analysis of in-sample and out-of-sample tests of stock return predictability in an effort to better understand the nature of the empirical evidence on return predictability. We find that a number of financial variables appearing in the literature display both in-sample and out-of-sample predictive ability with respect to stock returns in annual data covering most of the twentieth century. In contrast to the extant literature, we demonstrate that there is little discrepancy between in-sample and out-of-sample test results once we employ out-of-sample tests with good power. While conventional wisdom holds that out-of-sample tests help guard against data mining, Inoue and Kilian [Inoue, A., Kilian, L., 2004. In-sample or out-of-sample tests of predictability: which one should we use? Econometric Reviews 23, 371–402.] recently argue that in-sample and out-of-sample tests are equally susceptible to data mining biases. Using a bootstrap procedure that explicitly accounts for data mining, we still find that certain financial variables display significant in-sample and out-of-sample predictive ability with respect to stock returns.     

Credible reforms and stock return volatility: Evidence from privatization

In this paper we investigate how privatization affects stock return volatility. A credible privatization builds investors’ confidence through a reduction in political risk. In particular, a privatization program that is maintained over time signals credibility, which reduces political risk and in turn volatility. We further show that privatization is associated with lower idiosyncratic volatility mainly among developed markets, while it is associated with lower systematic volatility in developing markets. Additional tests suggest that the reduction in volatility is greater when privatization sales are carried out through the stock market than through asset sales.     

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.     

Innovation links,information diffusion,and return predictability: Evidence from China

Based on the activities of patent citation in China, a novel type of cross-firm innovation links is generated to investigate the gradual diffusion of information along the innovation chain via tests of cross-sectional return predictability. Various signals are created to represent the value of the information contained in the innovation links; these signals are demonstrated to have robust cross-predictability for stock returns in both the cross-sectional regression model and portfolio strategies. The effect of predictability is found to be stronger for stocks with high institutional ownership and analyst coverage. Considering the minimum number of steps required to establish the cross-firm linkage, innovation links are further partitioned to represent different proximity of the linked firms. It is then found that information diffuses faster across closely-linked firms than across distantly-linked firms. Sophisticated investors are found to be able to properly process the relevant information and benefit from innovation links.     

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.     

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.     

Are Asian stock markets efficient? Evidence from new multiple variance ratio tests

This paper tests for the martingale hypothesis in the stock prices of a group of Asian markets. We use new multiple variance ratio tests based on the wild bootstrap and signs. These are non-parametric finite sample tests, which do not rely on large sample theories for statistical inference. This paper also presents Monte Carlo results that these non-parametric tests show superior small sample properties to those of the conventional Chow–Denning test. Both weekly and daily data from 1990 are considered, while moving sub-sample windows are used for the latter to control the sensitivity of the results to a particular sample period. It is found that the Hong Kong, Japanese, Korean and Taiwanese markets have been efficient in the weak-form. The markets of Indonesia, Malaysia and Philippines have shown no sign of market efficiency, despite financial liberalization measures implemented since the eighties. We have also found evidence that the Singaporean and Thai markets have become efficient after the Asian crisis. In general, the results point toward the notion that the pricing efficiency of a market depends on the level of equity market development as well as the regulatory framework conducive of transparent corporate governance.     

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.