Google search and stock returns: A study on BIST 100 stocks

This study investigates whether there is a relationship between Google search and stock returns after we account for market, size, and value. We analyze weekly data on BIST 100 stocks from 2012 to 2017. Our results reveal that Google search is associated with positive returns, especially in small-capitalization stocks, but high search volume in the current period does not predict positive returns in the next period. The relationship is stronger (weaker) for sports and real estate (commercial and banking) firms. We provide additional evidence for market, size, and value factors. Institutional interest in the stock, more than firm size, can explain the relation between search volume and stock returns.     

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.     

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.     

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.     

Investor recognition and stock returns

It is well established that investment fundamentals, such as earnings and cash flows, can explain only a small proportion of the variation in stock returns. We find that investor recognition of a firm’s stock can explain relatively more of the variation in stock returns. Consistent with Merton’s (J Finance 42(3):483–510, 1987) theoretical analysis, we show that (i) contemporaneous stock returns are positively related to changes in investor recognition, (ii) future stock returns are negatively related to changes in investor recognition, (iii) the above relations are stronger for stocks with greater idiosyncratic risk and (iv) corporate investment and financing activities are both positively related to changes in investor recognition. Our research suggests that investors and managers who are concerned with firm valuation should consider investor recognition in addition to accounting information and related investment fundamentals.     

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.     

Earnings acceleration and stock returns

We document that earnings acceleration, defined as the quarter-over-quarter change in earnings growth, has significant explanatory power for future excess returns. These excess returns are robust to a wide range of previously documented anomalies and a battery of risk controls. The future return predictability appears to be consistent with investors assuming a seasonal random walk model for quarterly earnings and missing predictable implications of earnings acceleration for future earnings growth. Finally, the excess returns from the basic earnings acceleration strategy can be enhanced further by focusing on profit firms, low earnings volatility firms and on specific patterns of earnings acceleration.     

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.     

Expected stock returns and volatility

This paper examines the relation between stock returns and stock market volatility. We find evidence that the expected market risk premium (the expected return on a stock portfolio minus the Treasury bill yield) is positively related to the predictable volatility of stock returns. There is also evidence that unexpected stock market returns are negatively related to the unexpected change in the volatility of stock returns. This negative relation provides indirect evidence of a positive relation between expected risk premiums and volatility.     

Models for stock returns

Historically, the normal variance model has been used to describe stock return distributions. This model is based on taking the conditional stock return distribution to be normal with its variance itself being a random variable. The form of the actual stock return distribution will depend on the distribution for the variance. In practice, the distributions chosen for the variance appear to be very limited. In this note, we derive a comprehensive collection of formulas for the actual stock return distribution, covering some sixteen flexible families. The corresponding estimation procedures are derived by the method of moments and the method of maximum likelihood. We feel that this work could serve as a useful reference and lead to improved modelling with respect to stock market returns.     

Time-varying correlation between stock market returns and real estate returns

Direct investment in commercial or residential real estate is found to provide valuable diversification benefits for Australian investors though this is not so evident for indirect real estate investment vehicles like listed Australian real estate investment trusts (A-REIT). Further, multivariate analysis of Australian real estate and share market quarterly returns, spanning the period from the 3rd quarter 1986 to the 3rd quarter 2009, suggest that the correlation between real estate returns and share market returns is time-varying. Finally, while all of the asset class correlation coefficients increased with the Global Financial Crisis period this broad movement in asset class correlation is not evident in during the Wall Street Crash of 1987.     

Bank stock returns and economic growth

Previous research has established (i) that a country’s financial sector influence future economic growth and (ii) that stock market index returns affect future economic growth. We extend and tie together these two strands of the growth literature by analyzing the relationship between banking industry stock returns and future economic growth. Using dynamic panel techniques to analyze panel data from 18 developed and 18 emerging markets, we find a positive and significant relationship between bank stock returns and future GDP growth that is independent of the previously documented relationship between market index returns and economic growth. We also find that much of the informational content of bank stock returns is captured by country-specific and institutional characteristics, such as bank-accounting-disclosure standards, banking crises, enforcement of insider trading law and government ownership of banks.     

Consumption habit and international stock returns

We use the consumption-based asset pricing model with habit formation to study the predictability and cross-section of returns from the international equity markets. We find that the predictability of returns from many developed countries' equity markets is explained in part by changing prices of risks associated with consumption relative to habit at the world as well as local levels. We also provide an exploratory investigation of the cross-sectional implications of the model under the complete world market integration hypothesis and find that the model performs mildly better than the traditional consumption-based model, the unconditional and conditional world CAPMs and a three-factor international asset pricing model.     

Foreign exchange volatility and stock returns

This paper explores whether foreign exchange volatility is a priced factor in the US stock market. Our investigation is motivated by a number of empirical as well as theoretical considerations. Empirically, Menkhoff et al. (2012) find that foreign exchange volatility is a pervasive factor across a variety of test assets. Theoretically, Shapiro (1974), Dumas (1978), and Levi (1990) imply that foreign exchange volatility can influence firms’ cash flow volatility therefore the discount rate. In terms of empirical implementation, we employ the cross-sectional regression methodology of Fama and MacBeth (1973) as well as the time-series regression approach of Fama and French (1996). For robustness, we also use the mimicking portfolio approach of Fama and French (1993). We find that foreign exchange volatility has no power to explain either the time-series or the cross-section of stock returns, which calls for more research on foreign exchange risk. Bartov et al. (1996) and Adrian and Rosenberg (2008) suggest an alternative and maybe promising direction.     

Endogenous leverage and expected stock returns

This note clarifies conditions under which endogenous choice of debt induces a negative relation between leverage or default risk and expected stock returns. In the context of the model of George and Hwang [2009. Journal of Financial Economics 96, 56–79], we correct the contention that variation in bankruptcy costs across firms is sufficient. Variation in asset risk parameters can lead to the desired relation, but may not when also controlling for variation in book-to-market ratios. A simple parameterization of cross-sectional heterogeneity in risk and profitability implies a negative association of expected return with leverage and distress risk and a positive association with book-to-market.