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We examine the incremental cross-sectional role of several common risk factors related to size, book-to-market, and momentum in size-and-momentum-sorted portfolios. Unlike the existing literature, which focuses on the conditional mean specification only, we evaluate the common risk factors’ incremental explanatory power in the cross-sectional characterization of both average return and conditional volatility. We also investigate the role of ex-ante market risk in the cross-section. The empirical results demonstrate that the size-and-momentum-based risk factors explain a significant portion of the cross-sectional average returns and cross-sectional conditional volatility of the benchmark equity portfolios. We find that the Fama–French (1993) factors and the ex-ante market risk are priced in the cross-sectional conditional volatility. We conclude that the size-and-momentum-based factors provide a source of risk that is independent of the Fama–French factors as well as ex-post and ex-ante market risk. Our results bolster the risk-based explanation of the size and momentum effects.

This study examines the five-factor model of Fama and French (2015) on the French stock market by comparing it to the Fama and French (1993)’s base model. The new Fama and French five-factor model directed at capturing two new factors, profitability and investment in addition to the market, size and book to market premiums. The pricing models are tested using a time-series regression and the Fama and Macbeth (1973) methodology. The regularities in the factor’s behavior related to market conditions and to the sovereign debt crisis in Europe are also examined. The findings of Fama and French (2015) for the US market are confirmed on the Paris Bourse. The results show that both models help to explain some of the stock returns. However, the five-factor model is better since it has a marginal improvement over the widely used three-factor model of Fama and French (1993). In addition, the investment risk premium seems to be better priced in the French stock market than the profitability factor. The results are robust to the Fama and Macbeth (1973) methodology. Moreover, profitability and investment premiums are not affected by market conditions and the European sovereign debt crisis.

Previous studies have shown that stock returns bear a premium for downside risk versus upside potential. We develop a new risk measure which scales the traditional CAPM beta by the ratio of the upside beta to the downside beta, thereby incorporating the effects of both upside potential and downside risk. This “modified” beta has substantial explanatory power in standard asset pricing tests, outperforming existing measures, and it is robust to various alternative modeling and estimation techniques.

The purpose of this paper is to investigate the pricing of European real estate equities. The study examines the main drivers of real estate equity returns and determines whether loadings on systematic risk factors – the excess market return, small minus big (SMB), HIGH minus low (HML) – can explain cross‐sectional return differences in unconditional as well as in conditional asset pricing tests.

The paper draws upon time‐series regressions to investigate determinants of real estate equity returns. Rolling Fama‐French regressions are applied to estimate time‐varying loadings on systematic risk factors. Unconditional as well as conditional monthly Fama‐MacBeth regressions are employed to explain cross‐sectional return variations.

Systematic risk factors are important drivers of European real estate equity returns. Returns are positively related to the excess market return and to a value factor. A size factor impacts predominantly negatively on real estate returns. The results indicate increasing market integration after the introduction of the Euro. Loadings on systematic risk factors have weak explanatory power in unconditional cross‐section regressions but can explain returns in a conditional framework. Beta – and to a lesser extent the loading on HML – is positively related to returns in up‐markets and negatively in down markets. Equities which load positively on SMB outperform in down markets.

The implementation of a liquidity or a momentum factor could provide further evidence on the pricing of European real estate equities.

The findings could help investors to manage the risk exposure more effectively. Investors should furthermore be able to estimate their cost of equity more precisely and might better be able to pick stocks for time varying investment strategies.

This is the first paper to examine the pricing of real estate equity returns in a pan‐European setting.

The purpose of this paper is to examine alternative six- and seven-factor equity pricing models directed at capturing a new factor, aggregate volatility, in addition to market, size, book to market, profitability, investment premiums of the Fama and French (2015) and Fama and French’s (2018) aggregate volatility augmented model.

The models are tested using a time series regression and Fama and Macbeth’s (1973) methodology.

The authors show that both six- and seven-factor models best explain average excess returns on the French stock market. In fact, the authors outperform Fama and French’s (2018) model. The authors use sensitivity of aggregate volatility of a stock VCAC as a proxy to construct the aggregate volatility risk factor. The spanning tests suggest that Fama and French’s (1993, 2015, 2018) and Carhart’s (1997) models do not explain the aggregate volatility risk factor FVCAC. The results show that the FVCAC factor earns significant αs across the different multifactor models and even after controlling for the exposure to all the other in Fama and French’s (2018) model. The asset pricing tests show that it is systematically priced. In fact, the authors find a significant and negative (positive) relation between the aggregate volatility risk factor and the excess returns in the French stock market when it is rising (falling), in addition, periods with downward market movements tend to coincide with high volatility.

The authors contribute to the related literature in several ways. First, the authors test two new empirical six- and seven-factor model and the authors compare them to Fama and French’s (2018) model. Second, the authors give new evidence about the VCAC, using it for the first time to the authors’ knowledge, to construct a volatility risk premium.

For most companies, growth measures such as asset growth are positively correlated with accrual measures. Just like investment in fixed assets, current accrual represents one form of investment and is an integral part of a firm’s business growth. This makes it difficult to distinguish between the growth-based and earnings quality-based interpretations of the accrual effects, because high accruals can represent both high growth and inflated earnings. The purpose of this paper is to add to the literature by examining an issue that has not received much attention: the correlation between asset growth and accruals and its implication on stock return predictability. The authors address the issue using Fama and Macbeth’s (1973) cross-sectional regressions that are conditional on the correlations between the two variables.

The authors partition firms based on whether the correlation between current accrual and asset growth in the past five years is positive (ρ+) or negative (ρ−). The authors refer to these two types of firms such as “positive correlation” and “negative correlation” groups. For both groups, the authors examine whether firms with higher asset growth and higher accruals are associated with lower future stock returns. The authors implement Fama and MacBeth’s cross-sectional regressions incorporating the effect of correlations between growth and accrual measures. In addition, the authors regress hedge portfolio returns on Fama and French (1993) three-factor and Fama and French (2015) five-factor models to see if the intercepts (a’s) from these regressions are significantly different from 0.

For each year, the authors partition firms based on whether the correlation between asset growth and current accrual is positive or negative. For both the “positive correlation” and “negative correlation” firms, the authors examine the association between accruals and future stock returns. The authors find that accruals remain strong in predicting future stock returns for both groups. The accrual effects from the “negative correlation” group cannot be attributed to the growth-based hypothesis because for these firms, when accruals are high, growth measures tend to be relatively low and vice versa. The effects are most likely driven by the alternative hypothesis that investors overvalue the accrual part of earnings.

There exist a few issues when investors actually implement these strategies. These include liquidity costs, institutional holdings and short sale constraints. Lesmond (2008) concludes that the bulk of the trading profits is derived from the short side of the trade, but that this position suffers from high liquidity costs that reduces institutional holdings with consequent short sale constraints. The net gains after taking into account these issues remain an open question be addressed in the future.

The empirical results indicate that investors can do an implementable portfolio strategy of going long for a year on an initially equally weighted lowest asset growth (accrual) decile portfolio and going short for a year on an initially equally weighted highest asset growth (accrual) decile portfolio, which produces significant abnormal returns. The results further show that these abnormal returns can be improved if investors classify stocks into “the positive correlation” and “negative correlation” groups and implement trading similar trading strategies.

The empirical evidence finds that firm-year observations that exhibit a negative correlation between growth and accrual measures represents a significant 30 percent of the total firm-year observations during the sample period from July 1974 to June 2017. This highlights the necessity to undertake a detailed analysis on the issue. The authors continue to find accrual effects among these groups of firms. Therefore, the accrual effect cannot be attributed to the diminishing marginal return hypothesis. This is the main contribution of the paper.

Barry and Brown find that returns are higher for securities that have been listed for shorter periods of time after controlling for firm size and a January effect. The purpose of this paper is to examine the robustness of this period of listing effect and test for a post‐listing effect.

By extending the sample and including additional risk measures using both the Fama and Macbeth approach and the Fama and French approach, the author is able to conduct a stronger test of the period of listing effect and jointly test for a post‐listing effect.

The results indicate that there is a period of listing effect but that the effect is driven not by the higher returns of the newly listed firms but by the lower returns of the longest listed firms. The paper also provides additional support for a post‐listing effect in the sample.

While the results support a period of listing effect, they invite the larger question of why longer listed firms underperform. While the Barry and Brown informational risk explanation for period of listing effect may suffice, the results indicate a greater need to understand why returns vary with firm listing age especially for the newly listed and longest listed firms.

Environmental, social, and governance (ESG) issues have recently received much attention. This research investigates the daily performance of socially responsible investment (SRI). To do that, the authors construct portfolios consisting of the SRI, non-SRI, and matched non-SRI. The portfolios can be compared with the market benchmark based on α adjusted asset pricing models. Due to using high-frequency data, the authors use ARCH/GARCH to deal with time-varying volatility. Moreover, the authors also utilized Fama–MacBeth pooled regression to confront the SRI stocks and the non-SRI counterpart. In sum, the findings of this study confirm the superior performance of the value-weighted (VW) SRI portfolio against the market. On a head-to-head basis, the SRI yields a higher return than the non-SRI. The results are robust in the quarterly analysis. It is essential for investors that put their money in socially responsible (SR) portfolios to either promote sustainable development or chase a return on it.

This study aims to investigate information risk in relation to stock returns of a firm and whether information risk is priced in China.

The authors used accruals quality (AQ) as their measure of information risk and performed Fama-Macbeth regressions to investigate association of AQ with future realized stock returns. Moreover, two-stage cross-sectional regression analysis was performed, both at firm level and at portfolio level, to test if the AQ factor is priced in China in addition to existing factors in the Fama French three-factor model.

The authors found poor AQ being associated with higher future realized stock returns. Moreover, they found evidence of market pricing of AQ in addition to existing factors in the Fama French three-factor model. Further, subsample analysis revealed that investors value AQ more in non-state owned enterprises than in state owned enterprises.

The study sample comprises A-shares only and the generalization of the findings is limited by the peculiar institutional and economic setup in China.

This study contributes to market-based accounting literature by providing further insight into how and if investors value information risk, and it seeks to fill gap in empirical literature by providing evidence from the Chinese capital market.

The purpose of this paper is to examine the role of value-at-risk (VaR) in the cross-section of stock returns in the Indian stock market during the period 1999-2014.

The paper follows the methodology of Bali and Cakici (2004) to investigate the relationship between VaR and stock returns and employs Fama and French’s (1993) and Fama and Macbeth’s (1973) methods to find out the predictive power of VaR in time-series and cross-section settings. Further, it follows Fama and French (2008) to estimate separate cross-section regressions for small, medium and big stocks to verify the pervasiveness of the anomaly.

This study finds positive risk premium associated with VaR in the Indian stock market during 2001-2008, the period of short selling constraint for institutional investors. This premium is confined to small stocks and low institutional holdings. The positive premium can be attributed to short selling constraints.

The risk-return tradeoff can be utilized by investors and fund managers. As it is confined to small stocks, transaction costs may affect the profitability of the investment strategy.

The study contributes to the scanty empirical literature on the role of VaR in the cross-section of expected stock returns. Moreover, this is the first study that explores the relationship between VaR and stock returns in the asset pricing context for the Indian stock market.