Price and earnings momentum in Australian stock returns

There is no prior published Australian research on earnings momentum and only one prior unpublished work of limited depth and scope. We provide some of the first Australian evidence on earnings momentum and revisit price momentum with the first Australian evidence of the behaviour of returns beyond 12 months. Price momentum is found to be a feature of this market, but there is some reversal of returns during the second year after portfolio formation, suggesting trend chasing behaviour. Earnings momentum is also present, but with weak continuation into the second year. Price momentum and earnings momentum are shown to provide independent explanatory power over future returns.     

Reversal and momentum patterns in weekly stock returns: European evidence

We analyze short‐term reversal and medium‐term momentum patterns in weekly stock returns in Europe. Focusing on raw and stock‐specific returns, our empirical results show for both return specifications (a) a negative relation between weekly past returns and future returns in the short run and (b) a positive relation in the medium run. However, returns from reversal and momentum strategies based on stock‐specific returns are less volatile. In further analyses, we find short‐term reversal and medium‐term momentum patterns to be connected to stock characteristics. Looking at the potential causes of these effects, our results do not support the idea that short‐term reversal in weekly stock returns is due to an over‐ or underreaction to firm‐specific news nor that it is mainly driven by illiquidity. Medium‐term momentum in weekly stock returns, on the other hand, can be connected to behavioral biases. Our concluding tests confirm that our findings are robust among industries, in subperiods, for the January effect and in varying market states. Finally, while medium‐term momentum strategies remain profitable after accounting for transaction costs, short‐term reversal strategies can be mainly explained by transaction costs due to their high turnover.     

A tale of three schools: insights on autocorrelations of short-horizon stock returns

This article reexamines the autocorrelation patterns of short-horizonstock returns. We document empirical results which imply thatthese autocorrelations have been overstated in the existingliterature. Based on several new insights, we provide supportfor a market efficiency-based explanation of the evidence. Ouranalysis suggests that institutional factors are the most likelysource of the autocorrelation patterns.     

Momentum strategies and stock returns: Chinese evidence

This paper investigates the profitability of momentum investment strategies for equities listed in the Shanghai Stock Exchange. We also investigate the role of trading volume to examine whether there is any relationship between stock returns and past trading volume for Chinese equities. We find evidence of substantial momentum profits during the period 1995 to 2005 and that momentum is a pervasive feature of stock returns for the market investigated in this paper.Our findings suggest that investors can generate superior returns by investing in strategies unrelated to market movements. We also investigate the potential of past volume to explain momentum profits, and find no strong link between past volume and momentum profits. Our findings also show a strong momentum effect around earnings announcements but the magnitude of these returns is small in relation to the average monthly returns earned in the early months following portfolio formation.     

Size,value and momentum in stock returns: evidence from India

This paper examines the effects of size, value and momentum on the cross-sectional relation between expected returns and risk in the Indian stock market. We find that the conditional Carhart four-factor model empirically describes the variation of cross-section of return better than the unconditional model. When size, book-to-market and momentum effects are controlled in the conditional model, the positive relation of market beta, book-to-market and momentum with expected returns remains economically and statistically significant. However, this evidence is found to be subject to characteristics of test portfolios. The expected returns are sensitive to changes in predictive macroeconomic variables.     

Idiosyncratic momentum and the cross‐section of stock returns: Further evidence

In this article, we evaluate the profitability and economic source of the predictive power of the idiosyncratic momentum effect, by using five popular asset pricing models to construct the idiosyncratic momentum. We show that all five idiosyncratic momentum strategies produce similar return predictability and consistently outperform the conventional momentum strategy in the cross‐sectional pricing of equity portfolios and individual stocks. This positive effect of idiosyncratic momentum on returns is consistent with the investment capital asset pricing model (CAPM). Further analysis reveals that the firm‐level idiosyncratic momentum effect cannot extend to the aggregate stock market.     

Feasible momentum strategies: Evidence from the Swiss stock market

While there is little controversy on the profitability of momentum strategies, their implementation is afflicted with many difficulties. Most important, chasing momentum can generate high turnover. Though there are already several attempts to make momentum strategies less expensive with respect to transaction costs, we go a step further in the simplification of momentum strategies. By restricting our sample to Switzerland’s largest blue-chip stocks and choosing only one winner and one loser stock, we find average returns to our momentum arbitrage portfolios of up to 44% p.a. depending on the formation and holding periods. While unconditional risk models are at odds with momentum profits, stock market predictability and time-varying expected returns explain a large part of the momentum payoffs, including the post-holding period behavior of the winner and loser stocks (overreaction and subsequent price correction).

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.     

Time-series and cross-sectional momentum in anomaly returns

We find strong evidence of time-series and cross-sectional momentum in the long–short returns of a comprehensive sample of anomalies. Strategies that exploit such persistence deliver significant abnormal returns that are robust to the stock momentum effect, cannot be explained by traditional asset-pricing models, and are more pronounced when arbitrage capital is scarcer or market liquidity is lower. Momentum in anomaly returns dissipates but does not reverse, in the long-run. Our findings are consistent with limits-to-arbitrage and slow-moving capital causing mispricing to persist. Supporting this explanation, we find that both the level and persistence of anomaly returns are positively related to idiosyncratic volatility.     

International comparison of returns from conventional,industrial and 52-week high momentum strategies

The performance of industrial and 52-week high momentum strategies is compared to the conventional strategy, using a large sample of stocks drawn from multiple countries covering a quarter of century to 2007. The sample of 51,879 stocks in 51 countries removes the potential for criticism, such as data mining, and provides more generalisable findings and knowledge concerning the robustness and usefulness of return from momentum strategies. Both the industry and 52-week high strategies generate positive returns but neither is greater than the conventional momentum strategy. A new 52-week high industry momentum strategy is examined and it achieves a similar result.     

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.     

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.     

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.     

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.     

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.