Persistence and mean reversion in UK stock returns

This paper re-examines the issue of persistence and mean reversion in UK stock returns in the light of new developments published in Chow and Denning (1993) the random walk hypothesis is tested using multiple variance ratios for returns on the Financial Times All Share Index and 330 individual stocks for the period January 1965 to June 1994. There is no evidence of reversion in the UK stock market. Persistence only exists in high frequency data and is less strong in more recent times. Moreover, it is a portfolio phenomenon and is related to firm size. There is a possibility that persistence/reversion is also industry-related.     

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.     

Measurement effects and the variance of returns after stock splits and stock dividends

This article examines the relation between two factors affectingstock returns, the bid-ask spread and price discreteness, andthe increase in return variance after ex-dates of stock splitsand stock dividends. Controlling for these effects, the varianceof daily returns still increases significantly. The varianceof weekly returns also increases significantly, and the varianceof returns for a control sample of nonsplitting firms showsno significant increase. Variance ratio tests show that bid-askerrors are small for these stocks and therefore cannot explainthe large increase in variance. Spreads and price discretenessdo not explain increased variance after stock distributions.     

Firm efficiency and stock returns: Australian evidence

We employ a stochastic frontier approach to estimate firm efficiency - the efficiency with which a firm converts its inputs into output. We find a negative relation between firm efficiency and the cross-section of stock returns (‘firm efficiency effect’) in the Australian stock market. The firm efficiency effect is robust after controlling for other firm characteristics and is more pronounced in stocks with high limits-to-arbitrage. However, we find no evidence that firm efficiency is a priced factor in the cross-section. Our findings suggest that investors misprice firm efficiency and arbitrage costs perpetuate its return predictability.     

A Bayesian analysis of a variance decomposition for stock returns

We apply Bayesian methods to study a common vector autoregression (VAR)-based approach for decomposing the variance of excess stock returns into components reflecting news about future excess stock returns, future real interest rates, and future dividends. We develop a new prior elicitation strategy, which involves expressing beliefs about the components of the variance decomposition. Previous Bayesian work elicited priors from the difficult-to-interpret parameters of the VAR. With a commonly used data set, we find that the posterior standard deviations for the variance decomposition based on these previously used priors, including “non-informative” limiting cases, are much larger than classical standard errors based on asymptotic approximations. Therefore, the non-informative researcher remains relatively uninformed about the variance decomposition after observing the data. We show the large posterior standard deviations arise because the “non-informative” prior is implicitly very informative in a highly undesirable way. However, reasonably informative priors using our elicitation method allow for much more precise inference about components of the variance decomposition.     

An analysis of inflation and stock returns for the UK

Whether common stocks provide a hedge against inflation has been long debated. This paper focuses on this question by investigating the relationship between inflation and stock returns in the short term and medium term and under different inflationary regimes using the UK data. Empirical evidence suggests that the UK stock market fails to hedge against inflation in the short term. However, in the medium term there is mixed results. Results from different inflationary regimes show that the relationship between inflation and returns varies in different regimes.     

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.     

Short selling and stock returns: Evidence from the UK

The practice of shorting stocks was put forward as one of the causes of the recent financial crisis whereas Shiller (2003), for example, considers shorting an essential element of an efficient market. Shorting involves selling borrowed stocks and subsequently closing the position by purchasing and returning the stock to the lender. A profit will be realised if the stock's price decreases. Shorting enables investors who do not own a perceived overvalued stock to sell. Using a high-frequency UK dataset for the period between September 2003 and April 2010, our findings suggest shorting indicates evidence of overvalued stocks as significantly negative abnormal stock returns appear to follow an increase in shorting. These results do not hold, however, for shorting which occurs around the ex-dividend date. We further find that these results hold during the recent financial crisis.     

An examination of alternative CAPM-based models in UK stock returns

We evaluate the performance of unconditional and conditional versions of seven stochastic discount factor models in UK stock returns between January 1975 and December 2001. We find that the conditional four-moment capital asset pricing model (CAPM) has the best performance among the models we consider in terms of the lowest [Hansen, L.P., Jagannathan, R., 1997. Assessing specification errors in stochastic discount factor models. Journal of Finance 52, 591–607] distance measure and explaining the time-series predictability of industry portfolio excess returns. Conditional models also do a better job than unconditional models. However we find that the superior performance of the conditional four-moment CAPM, and conditional models in general, arises in part due to overfitting the data.     

Time-varying stock returns and labor income risks in the US and UK

I propose and estimate conditional asset pricing models where the risk premiums of the markets are related to the conditional covariance of the markets with labor income growth within and across countries and the volatility of the markets are related to the shocks and interactions of stock returns and labor income growth. I document that the risk premiums for the US and UK stock markets are more related to the conditional covariance of returns with the labor income growth within countries than across countries. I also find significant interactions of volatilities between stock returns and labor income within countries but not across countries. The results are consistent with the hypothesis that prices of domestic stocks are determined to a greater extent by stochastic discount factors of domestic investors than foreign investors and vice versa.     

Size,time-varying beta,and conditional heteroscedasticity in UK stock returns

The purpose of this study is to examine the relationship between firm size and time-varying betas of UK stocks. We extend the Schwert and Seguin (1990)(Journal of Finance 45, 1120–1155) methodology by explicitly modeling conditional heteroscedasticity in the market model residual returns. Our results show that the time-varying coefficient is not statistically significant for both small and large firm stock indexes. We also find that accounting for GARCH effects in the Schwert-Seguin market model yields beta estimates that are markedly differently from those when conditional heteroscedasticity is ignored. Event studies that ignore conditional heteroscedasticity may bias the abnormal returns of small and large firms, thereby leading to a different conclusion regarding the significance of an information event.     

The impact of diverse measures of default risk on UK stock returns

A number of recent papers examine the relationship between default risk and equity returns, and the results are mixed. These studies employ different measures of default risk and we find that correlations between eight diverse measures of default risk tend to be less than 50%. Nonetheless, we find that the relationship between stock returns and diverse measures of default risk tends to be consistent; default risk is a significant determinant of stock returns and this relationship is “hump backed”, as predicted by Garlappi and Yan (2011).     

Accruals quality,stock returns and asset pricing: Evidence from the UK

The extent to which accruals quality (AQ) is relevant for asset pricing has been debated widely. Prior research in this area has focused almost exclusively on the US. Using UK data, we investigate whether AQ portfolios exhibit evidence of significant mispricing, and whether an AQ factor is useful in explaining the portfolios' returns. We also investigate whether AQ is a priced risk factor. Using a two stage cross-sectional regression, we show that an AQ measure explains the cross-section of stock returns. AQ also explains the time-series variation in returns for two sets of portfolios: 16 size-BM portfolios, and 20 industry portfolios. Consistent with some recent US evidence, however, we find no evidence that AQ is a priced risk factor for UK stocks.     

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.     

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.     

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.     

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.