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This paper explores the relationship between size, book-to-market, beta, and expected stock returns in the U.S. Information Technology sector over the July 1990–June 2001 period. Two models, the multivariate model and the three-factor model, are employed to test these relationships. The risk-return tests confirm the relationship between size, book-to-market, beta and stock returns in IT stocks is different from that in other non-financial stocks. However, the sub-period results (the periods before and after the technology crash in April 2000) show that the nature of the relationship between stock returns, size, book-to-market, and market factors, or the magnitude of the size, book-to-market, and market premiums, is on average unchanged for both sub-periods. This result suggests the technology stock crash in April 2000 was not a correction of stock prices.

This study examines the value relevance of recognised and disclosed revaluations of land and buildings for a large sample of Australian firms from 1993 through 1997. In contrast to prior research, we control for risk and cyclical effects and find no difference between recognised and disclosed revaluations, using yearly‐cross‐sectional and pooled regressions and using both market and non‐market dependent variables. We also find only weak evidence that revaluations of recognised and disclosed land and buildings are value relevant.

Daniel and Titman (1997) contend that the Fama‐French three‐factor model’s ability to explain cross‐sectional variation in expected returns is a result of characteristics that firms have in common rather than any risk‐based explanation. The primary aim of the current paper is to provide out‐of‐sample tests of the characteristics versus risk factor argument. The main focus of our tests is to examine the intercept terms in Fama‐French regressions, wherein test portfolios are formed by a three‐way sorting procedure on book‐to‐market, size and factor loadings. Our main test focuses on ‘characteristic‐balanced’ portfolio returns of high minus low factor loading portfolios, for different size and book‐to‐market groups. The Fama‐French model predicts that these regression intercepts should be zero while the characteristics model predicts that they should be negative. Generally, despite the short sample period employed, our findings support a risk‐factor interpretation as opposed to a characteristics interpretation. This is particularly so for the HML loading‐based test portfolios. More specifically, we find that: the majority of test portfolios tend to reveal higher returns for higher loadings (while controlling for book‐to‐market and size characteristics); the majority of the Fama‐French regression intercepts are statistically insignificant; for the characteristic‐balanced portfolios, very few of the Fama‐French regression intercepts are significant.

Whether the risk factors or firm characteristics cause the value premium of stocks still needs further investigation. This paper shows that the factor‐based models are significant but not sufficient for the stock returns in Taiwan. Size or book‐to‐market ratio alone cannot influence the stock returns under a factor‐based model. However, size along with book‐to‐market is significant under a factor‐based model. Furthermore, the risk characteristics are more influential than the factor load in stock return behavior. We conclude that employing only a factor‐based model or only risk characteristics will not consider some important content in stock returns.

We would like to thank C. Y. Chen, Wenchih Lee, two anonymous referees and the seminar participants at the 2000 FMA annual meeting for their helpful comments and encouragement. All of the remaining errors are our responsibility.

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.

This study investigates the economic content of the two firm‐specific characteristics, size and book‐to‐market equity. Size is found to be significantly related to a combination of betas on all of the macro variables proposed in this research. Its significance persists through out the entire sample period. This provides further evidence that size is a proxy for pervasive risk factors in the stock market. The support for book‐to‐market equity’s role as a risk proxy is also evidenced, however to a lesser extent. Securities are then sorted into size and book‐to‐market equity portfolios and their effects on investment decisions are examined in the context of macro variables. Important investment implications are drawn based on the findings.

We revisit the performance of seasoned equity offerings (SEOs) in Japan against the backdrop of the Tokyo Stock Exchange's historical nine-year run up from 1980 to 1989, with the time period chosen for the purpose of comparison to previous studies. We analyze the long-run performance of 427 issues or 387 Japanese firms that conducted SEOs from 1980–1990. Initial results indicate that SEOs firms underperform standard benchmarks over subsequent 3- and 5-year periods after issuing. The results from value-weighted portfolios, however, show that SEOs outperform three out of five benchmarks. The results from the Fama-French three factor model show that all of the 16 SEO portfolios (formed by size and book-to-market quartiles) have positively significant intercepts, and most loadings are significant. The size loadings from time series three-factor model of value-weighted portfolio show that SEO sample firm returns exhibit characteristics of large firms as opposed to those of small firms under equally weighted portfolios. Our results support the arguments that (1) the returns of issuing firms are not idiosyncratic, but rather covary with the common factors of nonissuing firms and that (2) the underperformance of SEOs is sensitive to the precise test specifications.

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 reinvestigate the performance of common stock returns with respect to two popularly known firm level characteristics: size and book‐to‐market ratio.

All of New York Stock Exchange, American Stock Exchange, and National Association of Securities Dealers Automated Quotations stocks between July 1926 and June 2007 are used, and divided into various size and book‐to‐market equity groups. The extension of the various versions of the simple Fama‐French model is implemented.

From the findings, it is inferred that: two risk factors based on the mimicking return for the size and book‐to‐market ratio play a significant role in capturing strong variation in stock returns; and volatility persistence can significantly improve the common risk factors' impact in explaining the time series variation in size and book‐to‐market sorted portfolios.

In some sense, the model is based on only two firm level variables. In reality there exists plenty of other sources of average return anomalies. For a clearer understanding, an integration of various firm level characteristics would be an interesting issue to explore. A general equilibrium model that incorporates volatility exposure in a Fama‐French framework would be a challenging task as well.

The approach will help scholars and investment professionals make robust quantification of risk and average returns with respect to various measures of fundamental value.

The patterns in the monthly and yearly average excess returns with respect to two firm level characteristics, which documented are consistent with earlier studies. Even though the important role of firm level characteristics on the average‐return anomalies of common stocks is widely known, the approach is the very first that extends its support with respect to volatility models.

The purpose of this paper is to investigate the connection between the accrual quality and the growth/value characteristics (and their return premia) at firm level.

The paper employs a battery of univariate and multivariate cross‐sectional tests. Fama‐MacBeth regressions with main effects and interaction effects are used to identify the relation between accrual quality, book‐to‐market and returns. The analysis is conducted on the overall sample, as well as after conditioning on up and down markets.

Value (growth) stocks are more likely to be associated with high (low) accrual quality. Value stocks earn higher returns mainly in down markets, while poor accrual quality firms have significantly higher returns during up markets, but significantly lower returns during down markets. There is a significant interaction effect between accrual quality and the value premium, which only exhibits in the down markets (i.e. stocks with poor accrual quality earn a higher value premium in down markets than stocks with good accrual quality).

Results in this paper help disentangle between various explanations proposed for the accrual quality premium and the value premium. These findings are consistent with the idea that the same underlying risk factor generating the value premium also generates the cross‐sectional variation in accrual quality responsible for the accrual quality premium. From the corporate managers' perspective, the results imply that value firms can mitigate their higher costs of capital by providing high quality of accounting information. From an analyst's perspective, the study suggests that considering both accrual quality and growth characteristics can help make better portfolio allocation decisions than when these are considered separately.