Cross-section Of Returns Research Articles

Technical indicators and cross-sectional expected returns

This study shows that 14 widely documented technical indicators explain cross-sectional stock returns. These indicators have lower estimation errors than the three-factor Fama–French and historical mean models. The long-short portfolios based on the cross-sectional technical signals generate substantial excess returns. These remain consistent after controlling for well-known cross-sectional return determinants, including momentum, size, book-to-market ratio, investment, and profitability. Our findings suggest that technical indicators play an important role in determining variation in cross-sectional returns.

Analysis of Games Industry during COVID-19 Based on Fama-French Five-factor Model

Since the 1960s, asset pricing model has become the core research field of modern finance. It has been widely used in financial market, consumption and investment decision-making, monetary policy and even macroeconomic estimation and prediction. Scholars have done a lot of research on the theory and application of CAPM model, and achieved dramatic results. With the improvement of the stock market, CAPM model has gradually lost its convincing explanatory power when describing the relationship between stock return rate and risk. In 1992, Fama and French proposed a three-factor model to enhance the explanatory power of CAPM, and proposed that factors such as the total market value of a company and the book-to-market ratio could better explain the difference of stock returns on the cross section. In 2013, Fama and French improved the original three-factor model by adding profitability factor and investment mode factor to the three-factor model, and proposed a five-factor model, so as to better explain the difference in cross-sectional returns of stocks. COVID-19 caused a big black swan event and the impact is very dramatic that the economy has a huge impact. Therefore, this paper takes the game and entertainment industry as an example. Based on the Fama-french five-factor model and multiple linear regression, the changes of factor coefficients before and after the epidemic are analyzed, and some investment suggestions are given for reference. It is found that because of the emergence and outbreak of COVID-19 the game industry is more sensitive to the fluctuations of the market economy, and small businesses with a high book-to-market ratio are worth investing in.

Innovation links, information diffusion, and return predictability: Evidence from China

Based on the activities of patent citation in China, a novel type of cross-firm innovation links is generated to investigate the gradual diffusion of information along the innovation chain via tests of cross-sectional return predictability. Various signals are created to represent the value of the information contained in the innovation links; these signals are demonstrated to have robust cross-predictability for stock returns in both the cross-sectional regression model and portfolio strategies. The effect of predictability is found to be stronger for stocks with high institutional ownership and analyst coverage. Considering the minimum number of steps required to establish the cross-firm linkage, innovation links are further partitioned to represent different proximity of the linked firms. It is then found that information diffuses faster across closely-linked firms than across distantly-linked firms. Sophisticated investors are found to be able to properly process the relevant information and benefit from innovation links.

The predictability of cross-sectional returns in high frequency

Stock return forecast is of great importance to trading, hedging, and portfolio management. In this article, we apply LASSO and random forest to make rolling one-minute-ahead return forecasts of Dow Jones stocks, using the cross-section of lagged returns of S&P 500 components as candidate predictors. Although the number of candidate variables is large, the negative out-of-sample R2 suggests that the predictions from LASSO and random forest give larger mean-squared error than the historical average. So, there is no evidence of predictability in the cross-sectional returns of large stocks in high frequency. The predictability presented by Chinco et al. (2019) might be due to the interaction between large and small stocks.

Investor sentiment: a retail trader activity approach

PurposeThis study creates a measure of investor sentiment directly from retail trader activity to identify misvaluation and to examine the link between sentiment and subsequent returns.Design/methodology/approachUsing investor reports from a large discount brokerage that include measures of activity such as net buying, net new accounts and net new assets, this study creates a measure of retail trader sentiment using principal components. This study examines the relation between sentiment and returns through conditional mean and regression analyses.FindingsRetail sentiment activity coincides with aggregate Google Trends search data and firms with the greatest sensitivity to retail sentiment tend to be small, young and volatile. Periods of high retail sentiment precede poor subsequent market returns. Cross-sectional results detail the strongest impact on subsequent returns within difficult to value or difficult to arbitrage firms.Originality/valueThis study links a rich measure of retail trader activity to subsequent market and cross-sectional returns. These results deepen our understanding of noise trader risk and aggregate investor sentiment.

Firm-specific sentiment and individual option's implied volatility slope

PurposePrevious literature shows that market sentiment and the steepness of index option's implied volatility slope have a negative relation. This paper investigates the relation between firm-specific sentiment and individual option's implied volatility slope both theoretically and empirically.Design/methodology/approachThe authors develop a simple model with option traders' sentiment heterogeneity to show that sentiment and the steepness of individual option's implied volatility slope have a positive relation.FindingsWhen firm-specific sentiment is higher (more bullish), individual option's implied volatility slope becomes steeper. The positive relation is stronger when option traders' beliefs on risk are more dispersed. Empirical results support the theoretical model predictions.Originality/valueAlthough both firm-specific sentiment and individual options implied volatility slope predict future stock returns, there is no research exploring the relation between them. In particular, none of previous studies associates implied volatility slope's stock return predictability to investor behavior such as sentiment. The authors’ findings provide a behavior-based explanation on why steep implied volatility slope negatively predicts cross-sectional stock returns.

Financing anomaly, mispricing and cross-sectional return predictability

This study investigates the persistence of financing anomaly in the Chinese stock market. The results show that the long-short portfolio earns an average monthly excess return of 0.88% for the following 12 months based on this anomaly. We provide a behavioral mispricing-based explanation for this anomaly that financing anomaly is stronger in stocks or period with high investor overconfidence. Moreover, we find that financing anomaly is stronger in stocks with more investor attention, indicating that excessive investor attention increases mispricing and reduces market efficiency. However, idiosyncratic volatility cannot capture the arbitrage costs faced by financing anomaly, and investors' lottery-like preference cannot explain financing anomaly. Our findings are robust after controlling for other firm characteristic variables, considering shell value contamination and different sample periods.

Do Ethical Companies Have High Stock Prices or High Returns?

In this paper, we examine the performance of an impact investing strategy using the most ethical companies to build an impact investing portfolio. We test the time-series and cross-sectional returns of the impact portfolio, explore the financial analyst coverage of the most ethical firms, and run regressions to analyze the valuation of the most ethical firms. Our empirical results reveal that the portfolio consisting of the most ethical firms has a higher risk-adjusted return and that the most ethical firms have lower stock valuations than comparable stocks. We attribute our findings to the incomplete information in business ethics norms.

An accounting-based asset pricing model and a fundamental factor

This paper recasts the consumption asset pricing model in terms of accounting numbers that connect to consumption and the risk to consumption under accounting principles. The modeling yields an expected return measure that forecasts realized returns and the risk to those returns. It leads to the construction of a pricing factor from the accounting information. The factor performs well relative to extant factors in explaining cross-sectional returns. The factor return has negative correlation with the market portfolio and exhibits the property of protecting payoffs in bad states when consumption is low. This then prompts a two-factor representation that combines the market portfolio with a hedge portfolio against loss to consumption.

Past is Prologue: Inference from the Cross Section of Returns Around an Event

Past is Prologue: Inference from the Cross Section of Returns Around an Event

Model-Free Implied Dependence and the Cross-Section of Returns

Model-Free Implied Dependence and the Cross-Section of Returns

Trend Information and Cross-Sectional Returns: The Role of Analysts

Trend Information and Cross-Sectional Returns: The Role of Analysts

Quality Acceleration and Cross-Sectional Returns: Empirical Evidence

Quality Acceleration and Cross-Sectional Returns: Empirical Evidence

Realized skewness and momentum

ABSTRACT Extending evidence from extant literature, this study finds the existence of realized skewness and momentum factors in the emerging stock market of Pakistan. Tick-by-tick data of listed firms at Pakistan Stock Exchange (PSX) from 1 July 2008 to 31 August 2018 is used to generate five-minute returns for computing daily estimates of realized moments. Daily measures of realized moments are averaged for each firm to obtain weekly values. The long-short cross-sectional average returns of decile portfolios based on realized skewness and momentum are positive and significant, providing enough evidence that these factors can predict future returns.

Short- and long-term effects of responsible investment growth on equity returns

PurposeThe growth of socially responsible assets has been exponential over the last decade, they now account for almost a third of professional investments. As the growth persists, faith and conviction investors reshape the equity markets. To fully comprehend the impact of socially conscious participants on security returns, this paper attempts to provide insights on how responsible investment growth has impacted the returns of sustainable stocks. The examination is split by investment horizon to account for short and long effects.Design/methodology/approachUsing an exclusive dataset of non-financial ratings, provided by MSCI ESG research, the authors examine the cross-sectional returns of US and European sustainability-leading and lagging corporations between 2007 and 2019. Panel models robust to country, firm-year and industry effects were then employed to examine the impact of responsible investment growth on future stock returns.FindingsThe authors find evidence that the impact of responsible investment growth is dual contingent upon the timeframe considered. In the short run, sustainability-leading and lagging firms display similar stock returns. However, the spread in returns is negative over long horizons and increasing over time.Originality/valueThe examination performed in this study highlights the significant effect of responsible investment growth on future stock returns. Overall, the authors’ findings are consistent with the price pressure hypothesis in the short run and the cost of capital alteration over longer horizons.

Long-run reversal in commodity returns: Insights from seven centuries of evidence

We perform the longest study of long-run reversal in commodity returns. Using a unique dataset of 52 agricultural, industrial, and energy commodities, we examine the price behavior for the years 1265 to 2017. The findings reveal a strong and robust long-run reversal effect. The returns of the past one to three years negatively predict subsequent performance in the cross-section of returns. The effect is robust to extensive subsample and subperiod analysis, and not driven by statistical biases, extreme events, or macroeconomic risks. Our findings support the explanation that the long-term reversal originates from supply and demand adjustments following price changes. Finally, the phenomenon is elevated in more volatile commodities and in periods of high return dispersion.

AN ANOMALY WITHIN AN ANOMALY: THE HALLOWEEN EFFECT IN THE LONG-TERM REVERSAL ANOMALY

In this paper, we investigate the presence of the Halloween effect in the long-term reversal anomaly in the US. When we examine the cross-sectional returns of winner-minus-loser portfolios formed on prior returns over the time period of 1931-2021, we find evidence of stronger returns during winter months versus summer months. In particular, the effect appears to be driven by very strong winter-summer seasonality in the portfolio of small-capitalisation losers, and lack of Halloween effect in the portfolio of large-capitalisation winners. Our finding is robust to alternative measures of long-term reversal, differing sub-periods, the inclusion of the January effect and outlier considerations, as well as within small and large-sized companies.

Taming the Factor Zoo: New Evidence from China

We address the well-known “factor zoo” problem in the Chinese stock market. By replicating a generation of pricing factors, we verify the Liu–Stambaugh–Yuan four-factor model which subsumes other counterparts in the Chinese A-share market. We further construct a characteristic library and apply the double-selection LASSO approach to explore whether significant anomalies contribute to current pricing factors. We find that some anomalies indeed play a significant role in pricing cross-sectional returns, but the improvement to the Liu–Stambaugh–Yuan four-factor model is limited.

Structural innovation in state variables and expected stock returns

PurposeThe purpose of this study is to investigate whether the surprise components of systematic risk, which are useful in forecasting future investment opportunities, help explain the cross-section of average returns associated with portfolios sorted on size, book-to-market and accruals. This study also aims to examine the mispricing attributes of the size, value and accrual effects by investigating the relative economic relevance of aggregate risk factors, which are related to exogenous shocks in state variables, in the cross-sectional returns of triple-sorted portfolios.Design/methodology/approachThis study uses innovations of systematic risk, which affect the cash flows and risk-adjusted discount rates of all firms in an economy and determines the expected returns of portfolios based on firm characteristics. This study uses independent sorts based on size, book-to-market and total accruals – all of which are measured at the firm level – and construct three-dimensional test portfolios. For unobserved innovations, this study estimates a triangular structural vector autoregressive system and obtain the exogenous innovations in state variables. The author uses Fama-MacBeth two-pass cross-sectional regressions and examines whether the structural innovations explain a significant part of the cross-sectional variation in the average returns of the test portfolios.FindingsThis study finds that variations in expected returns of testing assets are determined by differences in the underlying assets’ exposure to systematic risk innovation. The empirical evidence also shows that exogenous innovation in Fama-French (FF) risk factors leaves out important cross-sectional information about expected returns, and additionally, the FF-factor betas have lower cross-sectional power than the proxy for innovation betas. The cross-sectional differences in the test portfolios’ sensitivity to instruments such as the short-term Treasury bill rate and term spread survive the presence of FF-factor betas.Originality/valueIn contrast to the existing literature, this study uses structural innovations that are uncorrelated and thus exogenous in nature. The author creates test portfolios that display a wide range of average returns and are unlikely to show spurious variability in risk exposures. Unlike the existing research, where size, value and accrual anomalies have been analyzed in isolation, this study examine these pricing patterns jointly, focusing on the possible contributing role of structural innovation in economy-wide predictor variables. To the best of the author’s knowledge, this paper is the first attempt to link the sensitivity of portfolios sorted on size, book-to-market and accruals to exogenous structural innovation.

Maximum Drawdown, Recovery, and Momentum

We empirically test predictability on asset price using stock selection rules based on maximum drawdown and its consecutive recovery. In various equity markets, monthly momentum- and weekly contrarian-style portfolios constructed from these alternative selection criteria are superior not only in forecasting directions of asset prices but also in capturing cross-sectional return differentials. In monthly periods, the alternative portfolios ranked by maximum drawdown measures exhibit outperformance over other alternative momentum portfolios including traditional cumulative return-based momentum portfolios. In weekly time scales, recovery-related stock selection rules are the best ranking criteria for detecting mean-reversion. For the alternative portfolios and their ranking baskets, improved risk profiles in various reward-risk measures also imply more consistent prediction on the direction of assets in future. Moreover, turnover rates of these momentum/contrarian portfolios are also reduced with respect to the benchmark portfolios. In the Carhart four-factor analysis, higher factor-neutral intercepts for the alternative strategies are another evidence for the robust prediction by the alternative stock selection rules.