Measuring the predictable variation in stock and bond returns

Recent studies show that when a regression model is used toforecast stock and bond returns, the sample R² increases dramaticallywith the length of the return horizon. These studies argue,therefore, that long-horizon returns are highly predictable.This article presents evidence that suggests otherwise. Long-horizonregressions can easily yield large values of the sample R²,even if the populations R² is smaller or zero. Moreover, long-horizonregressions with a small or zero population R² can produce t-ratiosthat might be interpreted as evidence of strong predictability.In general, the analysis provides little support for the viewthat long-horizon returns are highly predictable.     

Habit persistence: Explaining cross-sectional variation in returns and time-varying expected returns

This paper uses an iterated GMM approach to estimate and test the consumption based habit persistence model of Campbell and Cochrane [Campbell, J.Y., Cochrane, J.H., 1999. By force of habit: A consumption-based explanation of aggregate stock market behavior. Journal of Political Economy 107, 205–251] on the US stock market. The empirical evidence shows that the model is able to explain the size premium, but fails to explain the value premium. Further, the state variable of the model – the surplus consumption ratio – explains counter-cyclical time-varying expected returns on stocks. The model also produces plausible low real risk-free rates despite high relative risk aversion.     

Speculative trading and stock returns: A stochastic dominance analysis of the Chinese A-share market

The pricing of A-shares in China has long puzzled financial economists. This paper applies recent tests of stochastic dominance (SD) to examine whether differences in the return distributions of A- and B-shares in China are consistent with market efficiency. As SD is nonparametric, market efficiency can be examined without the joint test problem arising from misspecifications in the asset pricing benchmark. Our results show A-shares have second-order dominated B-shares from 1996 to 2005. This dominance was most significant during the market segmentation period, but has continued, albeit to a lesser extent even after the B-share market was opened to local investors in 2001. Our results are robust to using residual returns from an international asset pricing model instead of raw returns. We conclude that the superior performance of A-shares cannot be attributed to risk. The results are more likely due to a return bias caused by intense speculation among retail individuals under limited arbitrage.     

Information content and other characteristics of the daily cross-sectional dispersion in stock returns

We study the cross-sectional dispersion in daily stock returns, or daily return dispersion (RD). Our primary empirical contribution is to demonstrate that RD contains reliable incremental information about the future traditional volatility of both firm-level and portfolio-level returns. The relation between RD and future stock volatility is pervasive across time and across different industry portfolios, size-based portfolios, and beta-based portfolios. Further, our results suggest that RD contains more incremental information about the future volatility of firm-level stock returns than do lagged market-level return shocks. To further characterize RD and assist in interpretation, we also document how dispersion varies with stock turnover and macroeconomic news.     

The joint cross-sectional variation of equity returns and volatilities

This paper analyzes the determinants of the simultaneous cross-sectional variation of return and volatility risk premia. Independently of the model specification employed, the estimated risk premium associated with the default premium beta is always positive and statistically different from zero. Moreover, the risk premium of the market volatility risk premium beta is negative and statistically significant. However, both risk factors are priced economically and statistically differently in the volatility and return segments of the market. On average, common factors in both segments explain 90% of the variability of volatility risk premium portfolios, but only 65% of the variability of equity return portfolios.     

Relation between time-series and cross-sectional effects of idiosyncratic variance on stock returns

Consistent with the post-1962 US evidence by Ang et al. [Ang, A., Hodrick, R., Xing Y., Zhang, X., 2006. The cross-section of volatility and expected returns. Journal of Finance 51, 259–299], we find that stocks with high idiosyncratic variance (IV) have low CAPM-adjusted expected returns in both pre-1962 US and modern G7 data. We also test in three ways the conjecture that IV is a proxy of systematic risk. First, the return difference between low and high IV stocks – that we dub as IVF – is a priced factor in the cross-section of stock returns. Second, loadings on lagged market variance and lagged average IV account for a significant portion of variation in average returns on portfolios sorted by IV. Third, the variance of IVF correlates closely with average IV, and the two variables have similar explanatory power for the time-series and cross-sectional stock returns.     

Impact of idiosyncratic volatility on stock returns: A cross-sectional study

This paper proposes a new approach to estimate the idiosyncratic volatility premium. In contrast to the popular two-pass regression method, this approach relies on a novel GMM-type estimation procedure that uses only a single cross-section of return observations to obtain consistent estimates. Also, it enables a comparison of idiosyncratic volatility premia estimated using stock returns with different holding periods. The approach is empirically illustrated by applying it to daily, weekly, monthly, quarterly, and annual US stock return data over the course of 2000–2011. The results suggest that the idiosyncratic volatility premium tends to be positive on daily return data, but negative on monthly, quarterly, and annual data. They also indicate the presence of a January effect.     

The cross-sectional relationship between stock returns and domestic and global factors in the Chinese A-share market

By using an extension of the Fama and MacBeth cross-sectional regression model, this analysis examines the relationship between stock returns and (i) a local beta, (ii) two global betas, and (iii) some firm-specific characteristics in the Chinese A-share market. The results of the analysis suggest that neither the conditional local beta nor the global betas has a significant relationship with stock returns in A-shares. Our findings indicate that firm factors, such as the book-to-market ratio and firm size, are important in explaining stock returns. However, the size effect is sensitive to the specification of the model. Finally, the results of sub-period tests indicate that the A-share market did not become increasingly integrated with either the world stock markets or the Hong Kong stock market over the period 1995–2002.

Speculative bubbles in emerging stock markets and macroeconomic factors: A new empirical evidence for Asia and Latin America

The purpose of this study is firstly to test for the existence of periodically collapsing stock price bubbles in Asian and Latin American emerging stock markets for the period 1990–2009. We use the new non-cointegration test developed by Taylor and Peel (1998) with the Residuals-Augmented Least Squares (RALS) method of Im (1996) and Im and Schmidt (2008) for monthly data of price indexes and dividends. The results show that the hypothesis of formation of bubbles cannot be rejected for all of the studied emerging stock markets. This evidence implies that the co-integration relation between the prices and the dividends is not always supported, indicating that the stock prices do not reflect their fundamental values in the emerging stock markets. We then link speculative bubbles with macroeconomic and financial factors, which is an interesting contribution of this study. The degree of equity market openness is found to be the key factor, positively related to the formation of speculative bubbles in these markets.     

Predicting stock returns

This paper studies whether incorporating business cycle predictors benefits a real time optimizing investor who must allocate funds across 3,123 NYSE-AMEX stocks and cash. Realized returns are positive when adjusted by the Fama-French and momentum factors as well as by the size, book-to-market, and past return characteristics. The investor optimally holds small-cap, growth, and momentum stocks and loads less (more) heavily on momentum (small-cap) stocks during recessions. Returns on individual stocks are predictable out-of-sample due to alpha variation, whereas the equity premium predictability, the major focus of previous work, is questionable.     

The impact of internet stock message boards on cross-sectional returns of small-capitalization stocks

We examine the impact of more than 2.5 million HotCopper messages on the Australian stock market. HotCopper is the largest online stock message board in Australia and the sample of messages covers over 2000 companies listed on the Australian Securities Exchange (ASX) from January 2003 through December 2008. We exclude messages surrounding public price-sensitive announcements released centrally by the ASX in order to examine the private information content of internet board messages. We find that the number of board messages and message sentiment significantly and positively relate to the contemporaneous returns of underperforming (low ROE, EBIT margin, EPS) small capitalization stocks with high market growth potential (low book-to-market). Posting activity is positively associated with trading volume for small stocks and negatively associated with bid-ask spreads for small and large stocks in the short term. Bullish small stocks outperform bearish ones significantly in respective days and months, exhibiting no return reversals to pre-message board activity levels in subsequent time periods. Large stocks are not found to be affected by message board activity. We conclude that higher message board activity quickly reflects itself into the prices of small capitalization stocks in a highly regulated market like the ASX.     

Innovative efficiency and stock returns

We find that innovative efficiency (IE), patents or citations scaled by research and development expenditures, is a strong positive predictor of future returns after controlling for firm characteristics and risk. The IE-return relation is associated with the loading on a mispricing factor, and the high Sharpe ratio of the Efficient Minus Inefficient (EMI) portfolio suggests that mispricing plays an important role. Further tests based upon attention and uncertainty proxies suggest that limited attention contributes to the effect. The high weight of the EMI portfolio return in the tangency portfolio suggests that IE captures incremental pricing effects relative to well-known factors.     

Comoment risk and stock returns

We estimate investable comoment equity risk premiums for the US markets. The stock's contribution to the asymmetry and the fat tails of the market portfolio's payoff are priced into a coskewness premium and a cokurtosis premium. We construct zero-investment strategies that are long and short in coskewness and cokurtosis equity risks; we infer from the spread the returns attached to a unit exposure to US equity coskewness and cokurtosis. The coskewness and cokurtosis premiums present positive monthly average returns of 0.27% and 0.14% from January 1959 to December 2011. Comoment risks appear to be significantly priced within the US stock market and display significant explanatory power regarding the US size and book-to-market effects. The premiums do not subsume, but rather complement the empirical capital asset pricing model. Our analysis relies on data collected from CRSP (Chicago Research Center for Security Prices) over December 1955 to December 2011. To our knowledge, the paper is the first to propose investable higher-moment risk factors over such an extensive time period.     

Revenue surprises and stock returns

This paper examines the relation between revenue surprises and contemporaneous and future stock returns. It also investigates whether analysts update their earnings forecasts in response to revenue surprises in a timely and unbiased fashion. Stock price reaction on the earnings announcement date is significantly related to contemporaneous as well as past revenue surprises. After controlling for earnings surprises, we find significant abnormal returns in the post-announcement period for stocks that have large revenue surprises. Although analysts revise their forecasts of future earnings in response to revenue surprises, they are slow to incorporate fully the information in revenue surprises.     

Multifrequency news and stock returns

Equity prices are driven by shocks with persistence levels ranging from intraday horizons to several decades. To accommodate this diversity, we introduce a parsimonious equilibrium model with regime shifts of heterogeneous durations in fundamentals, and estimate specifications with up to 256 states on daily aggregate returns. The multifrequency equilibrium has higher likelihood than the Campbell and Hentschel [1992. No news is good news: an asymmetric model of changing volatility in stock returns. Journal of Financial Economics 31, 281–318] specification, while producing volatility feedback 10 to 40 times larger. Furthermore, Bayesian learning about volatility generates a novel trade-off between skewness and kurtosis as information quality varies, complementing the uncertainty channel [e.g., Veronesi, 1999. Stock market overreaction to bad news in good times: a rational expectations equilibrium model. Review of Financial Studies 12, 975–1007]. Economies with intermediate information best match daily returns.     

Asset liquidity and stock returns

We document the significant predictive power of firms' asset liquidity in the cross section of subsequent stock returns. The annual return spread between portfolios featuring the highest and lowest levels of asset liquidity is significantly positive. Our proposed measure of asset liquidity outperforms those measures developed by Gopalan et al. (2012) in predicting returns. The asset liquidity anomaly also provides significantly positive alphas when controlling for the asset pricing factors in the Fama and French (1993) three-factor model and the Carhart (1997) four-factor model. Asset liquidity exhibits strong return forecasting power even after controlling for acknowledged cross-sectional determinants of return. The positive relation between asset liquidity and future returns tends to be stronger for firms with greater asset productivity, higher quality cash flow and lower capital investment.     

Google searches and stock returns

We investigate whether data from Google Trends can be used to forecast stock returns. Previous studies have found that high Google search volumes predict high returns for the first one to two weeks, with subsequent price reversal. By using a more recent dataset that covers the period from 2008 to 2013 we find that high Google search volumes lead to negative returns. We also examine a trading strategy based on selling stocks with high Google search volumes and buying stocks with infrequent Google searches. This strategy is profitable when the transaction cost is not taken into account but is not profitable if we take into account transaction costs.     

Financial constraints and stock returns

We test whether the impact of financial constraints on firmvalue is observable in stock returns. We form portfolios offirms based on observable characteristics related to financialconstraints and test for common variation in stock returns.Financially constrained firms' stock returns move together overtime, suggesting that constrained firms are subject to commonshocks. Constrained firms have low average stock returns inour 1968-1997 sample of growing manufacturing firms. We findno evidence that the relative performance of constrained firmsreflects monetary policy, credit conditions, or business cycles.     

Slow-moving capital and stock returns

This paper studies the effects that delay in capital allocations in the stock market and high short-term trading incentives have on returns of this market. We report that capital inertia makes the Sharpe ratio and the volatility of the stock returns many times higher than in an economy with no capital delays. Furthermore, in agreement with empirical literature, the stock price displays short-term overreaction and high volatility of the conditional Sharpe ratio.     

Geographic dispersion and stock returns

This paper shows that stocks of truly local firms have returns that exceed the return on stocks of geographically dispersed firms by 70 basis points per month. By extracting state name counts from annual reports filed with the Securities and Exchange Commission (SEC) on Form 10-K, we distinguish firms with business operations in only a few states from firms with operations in multiple states. Our findings are consistent with the view that lower investor recognition for local firms results in higher stock returns to compensate investors for insufficient diversification.