Investor flows and stock market returns

This study simultaneously analyzes the relation between aggregate stock market returns and cash flows (net purchases of equity) from a broad array of investor groups in the United States over a long period of time from 1952 to 2004. We find strong evidence that quarterly flows are autocorrelated for each of the different investor groups. We further document a significant and positive contemporaneous relation between stock market returns and flows of Mutual Funds and Foreign Investors.     

Investor sentiment and stock returns: Global evidence

We assess the impact of investor sentiment on future stock returns in 50 global stock markets. Using the consumer confidence index (CCI) as the sentiment proxy, we document a negative relationship between investor sentiment and future stock returns at the global level. While the separation between developed and emerging markets does not disrupt the negative pattern, investor sentiment has a more instant impact in emerging markets, but a more enduring impact in developed markets. Individual stock markets reveal heterogeneity in the sentiment-return relationship. This heterogeneity can be explained by cross-market differences in culture and institutions, along with intelligence and education, to varying degrees influenced by the extent of individual investor market participation.     

Investor sentiment and stock returns: Wenchuan Earthquake

This paper exploits a natural experiment (the Wenchuan Earthquake in China) to study the effects of investor sentiment on stock returns. We find that during the 12 months following the earthquake, stock returns are significantly lower for firms headquartered nearer the epicenter than for firms further away. Further analyses indicate that this pattern of stock returns does not exist before or long after the earthquake, and cannot be explained by actual economic losses or a change in systematic risk. Overall, our evidence is consistent with the interaction of local bias and investor sentiment affecting stock returns.     

Investor sentiment and stock returns: Some international evidence

We examine whether consumer confidence – as a proxy for individual investor sentiment – affects expected stock returns internationally in 18 industrialized countries. In line with recent evidence for the U.S., we find that sentiment negatively forecasts aggregate stock market returns on average across countries. When sentiment is high, future stock returns tend to be lower and vice versa. This relation also holds for returns of value stocks, growth stocks, small stocks, and for different forecasting horizons. Finally, we employ a cross-sectional perspective and provide evidence that the impact of sentiment on stock returns is higher for countries which have less market integrity and which are culturally more prone to herd-like behavior and overreaction.     

Investor attention,aggregate limit-hits,and stock returns

We develop a simple measure of investor attention by aggregating the number of days that a stock hits the upper or lower limit on a monthly basis. This attention proxy describes investor trading behavior and contains information of future stock returns. Using data from the Chinese equity market from 2002 to 2017, we provide extensive evidence that the investor attention captured by our measure negatively predicts cross-sectional stock returns, and the long–short trading strategy based on this attention measure produces significant economic value. We argue that the attention-motivated trading is the main cause behind the return predictability of aggregate limit-hits.     

Fast profits: Investor sentiment and stock returns during Ramadan

Observed by more than 1.5 billion Muslims, Ramadan is one of the most celebrated religious traditions in the world. We investigate stock returns during Ramadan for 14 predominantly Muslim countries over the years 1989-2007. The results show that stock returns during Ramadan are significantly higher and less volatile than during the rest of the year. No discernible declines in market liquidity are recorded. We find these results consistent with a notion that Ramadan positively affects investor psychology, as it promotes feelings of solidarity and social identity among Muslims world-wide, leading to optimistic beliefs that extend to investment decisions.     

Investor sentiment and aggregate stock returns: the role of investor attention

Review of Quantitative Finance and Accounting - We build on the intuitive, albeit overlooked, relationship between investor attention and investor sentiment to explore the open question of the...     

Investor sentiment and the cross-section of stock returns: new theory and evidence

Review of Quantitative Finance and Accounting - Narrative reporting is an important avenue for investors to know more about a company from the eyes of its board of directors. This study aims to...     

Social media effect,investor recognition and the cross-section of stock returns

Investor recognition affects cross-sectional stock returns. In informationally incomplete markets, investors have limited recognition of all securities, and their holding of stocks with low recognition requires compensation for being imperfectly diversified. Using the number of posts on the Chinese social media platform Guba to measure investor recognition of stocks, this paper provides a direct test of Merton's investor recognition hypothesis. We find a significant social media premium in the Chinese stock market. We further find that including a social media factor based on this premium significantly improves the explanatory power of Fama-French factor models of cross-sectional stock returns, and these results are robust when we control for the mass media effect and liquidity effect. Finally, we find that investment strategies based on the social media factor earn sizable risk-adjusted returns, which signifies the importance of the social media premium in portfolio management.     

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.     

Investor sentiment and the dispersion of stock returns: Evidence based on the social network of investors

This paper extracts an investor sentiment indicator for the 30 DJIA stocks based on the textual classification of 289,024 online tweets posted on the so-called StockTwits, and examines its contemporaneous and predictability effects on the dispersion of stock returns using the quantile regression technique. We find that both contemporaneous and predictability effects of sentiment are heterogeneous throughout the return distribution. Specifically, sentiment is positively contemporaneously associated with stock returns at higher quantiles. However, it is a strong negative predictor of future returns at lower quantiles. Overall, our findings are broadly consistent with most behavioural theories and show that sentiment mainly affects the valuation of assets in extreme market conditions.     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

Institutional trading and stock returns

In this study, we explore the dynamics of the relation between institutional trading and stock returns. We find that stock returns Granger-cause institutional trading (especially purchases) on a quarterly basis. The robust and significant causality from equity returns to institutional trading can be largely explained by the time-series variation of market returns, that is, institutions buy more popular stocks after market rises. Stock returns appear to be negatively related to lagged institutional trading. A further analysis of the behavior of trading and the returns of the traded stocks reveals evidence that stocks with heavy institutional buying (selling) experience positive (negative) excess returns over the previous 12 months.