Beta,size, book-to-market equity and returns: A study based on UK data

This paper examines the role of beta, size and book-to-market equity as competing risk measurements in explaining the cross-sectional returns of UK securities for the period July 1980 through June 2000. The methodology of [Fama, E., French, K., 1992. The cross-section of expected stock returns. Journal of Finance 47, 427–467] and [Pettengill, G., Sundaram, S., Mathur, I., 1995. The conditional relation between beta and returns. Journal of Financial and Quantitative Analysis 30, 101–116] is adopted. Results show that, when adopting the methodology of [Pettengill, G., Sundaram, S., Mathur, I., 1995. The conditional relation between beta and returns. Journal of Financial and Quantitative Analysis 30, 101–116], where data is segmented between up and down markets, a significant relationship is found between beta and returns even in the presence of size and book-to-market equity. Size is not found to be a significant risk variable, whereas book-to-market equity is found to be priced by the market and is thus a significant determinant of security returns. This is the case irrespective of the methodology adopted.     

The Cross-Section of Stock Returns on The Shanghai Stock Exchange

This study explores the cross-sectional stock return behavior on the A-share market of the Shanghai Stock Exchange (SSE), which is segmented from world's other equity markets. We estimate the effects of beta, firm size, book-to-market equity ratio and a variable unique to the Chinese stock markets, the proportion of firm's floating (tradable) equity over total equity on SSE stocks over the period 1993–2002. We find that smaller firms and value stocks perform better. Systematic risk is negatively significant in down markets. The proportion of floating equity has no direct effect on stock returns. JEL Classification: G14, G15     

Are the Fama–French factors proxying news related to GDP growth? The Australian evidence

Inspired by Vassalou (J Financ Econ 68:47–73, 2003), we investigate the contention that the Fama and French (J Financ Econ 33:3–56, 1993) model’s ability to explain the cross sectional variation in equity returns is because the Fama–French factors are proxying for risk associated with future GDP growth in the Australian equities market. To assess the validity of Vassalou’s findings, we augment the CAPM and the Fama–French model with a GDP growth factor and run system regressions of the GDP-enhanced models using the GMM approach. Our results suggest that news about future GDP growth is not priced in equity returns and that any ability that SMB and HML exhibit in explaining equity returns is not because they contain information about future GDP growth.

Stock returns and product market competition: beyond industry concentration

The main purpose of this paper is to provide direct evidence that product market structure affects stock returns. This is not only through industry concentration, as found in Hou and Robinson (J Finance 61:1927–1956, 2006), but also based on firms’ product substitutability and industry market size. Furthermore, the predictive power of product substitutability and market size for stock returns is not subsumed by industry concentration. Our results highlight the multi-dimensional structure of product market competition and its impact on asset prices.     

Do option open-interest changes foreshadow future equity returns?

Recent work considers whether information is simultaneously reflected in both option and equity markets. We provide new evidence supporting Black’s (Financ. Anal. J. 31:36–72, 1975) conjecture that information is first revealed in option markets. Specifically, changes in call and put open-interest levels have predictive power for future equity returns. Large increases in call open interest are followed by significantly increased equity returns. Put open-interest increases precede weaker future returns, but the relationship is considerably less pronounced in the presence of certain controls. The recent change in the call-to-put open-interest ratio has predictive power as to equity returns over the following week, even after controlling for numerous factors.     

Is there a viable alternative to ordinary least squares regression when security abnormal returns are the dependent variable?

Regression analysis is often used to estimate a linear relationship between security abnormal returns and firm-specific variables. If the abnormal returns are caused by a common event (i.e., there is “event clustering”) the error term of the cross-sectional regression will be heteroskedastic and correlated across observations. The size and power of alternative test statistics for the event clustering case has been evaluated under ideal conditions (Monte Carlo experiments using normally distributed synthetic security returns) by Chandra and Balachandran (J Finance 47:2055–2070, 1992) and Karafiath (J Financ Quant Anal 29(2):279–300, 1994). Harrington and Shrider (J Financ Quant Anal 42(1):229–256, 2007) evaluate cross-sectional regressions using actual (not simulated) stock returns only for the case of cross-sectional independence, i.e., in the absence of clustering. In order to evaluate the event clustering case, random samples of security returns are drawn from the data set provided by the Center for Research in Security Prices (CRSP) and the empirical distributions of alternative test statistics compared. These simulations include a comparison of OLS, WLS, GLS, two heteroskedastic-consistent estimators, and a bootstrap test for GLS. In addition, the Sefcik and Thompson (J Accounting Res 24(2):316–334, 1986) portfolio counterparts to OLS, WLS, and GLS, are evaluated. The main result from these simulations is none of the other estimator shows clear advantages over OLS or WLS. Researchers should be aware, however, that in these simulations the variance of the error term in the cross-sectional regression is unrelated to the explanatory variable.

THE EFFECT OF SIZE,BOOK-TO-MARKET EQUITY,PRIOR RETURNS,AND BETA ON STOCK RETURNS: JANUARY VERSUS THE REMAINDER OF THE YEAR

Size and book-to-market equity are shown to transcend beta in explaining stock returns. One possible explanation of the book-to-market equity effect is overreaction. We investigate the effect of size, book-to-market equity, prior returns, and beta on stock returns. We find significant reversals in January consistent with overreaction. We find a strong positive relation between returns and prior returns for February through December. Both patterns are distinct from either a size or book-to-market equity effect. Book-to-market equity is significantly related to returns, with some evidence of a stronger effect in January.     

The relationship between size,book-to-market equity ratio,earnings–price ratio,and return for the Hong Kong stock market

In this paper, we investigate the relation between stock returns and β, size (ME), leverage, book-to-market equity ratio, and earnings–price ratio (E/P) in Hong Kong stock market using the Fama and French (FF) [J. Finance 47 (1992) 427] approach. FF find that two variables, size and book-to-market equity, combine to capture the cross-sectional variation in average stock returns associated with β, size, leverage, book-to-market equity, and E/P ratios. In this paper, similar to previous studies in Hong Kong and US stock markets, we find that β is unable to explain the average monthly returns on stocks continuously listed in Hong Kong Stock Exchange for the period July 1984–June 1997. But three of the variables, size, book-to-market equity, and E/P ratios, seem able to capture the cross-sectional variation in average monthly returns over the period. The other two variables, book leverage and market, are also able to capture the cross-sectional variation in average monthly returns. But their effects seem to be dominated by size, book-to-market equity, and E/P ratios, and considered to be redundant in explaining average returns when size, book-to-market equity, and E/P ratios are also considered. The results are consistent across subperiods, across months, and across size groups. These suggest that the results are not driven by extreme observations or abnormal return behavior in some of the months or by size groups.     

Default Risk and Equity Returns: Evidence from the Taiwan Equities Market

Studies of risk and return characteristics of different portfolios have recently gained enormous attention. Differing from past studies, this paper uses a compound option model to build the proxy of default risk and evaluate the relationship between default risk effect and equity returns. The primary goal of this paper is to evaluate the relationship among default risk, size, book-to-market, and equity returns, using data drawn from the Taiwan equities market, and to also examine whether size and book-to-market are proxies for default risk. The results show that the effects of size and book-to-market exist in different default portfolios when default risks are controlled. If size or book-to-market is controlled, there are no default effects. In the regression analysis, when default risk is included in Fama and French’s Three Factor Model, it shows that size, book-to-market and default risk have significant influence on equity returns and default risk is a systematic risk. Default risk is also more powerful in explaining returns when the compound option model is adopted for estimating default risks.     

Stock returns and beta,firms size,E/P,CF/P,book-to-market,and sales growth: evidence from Singapore and Malaysia

Using data from Singapore and Malaysia for the period 1988–1996, this paper examines the relationship between stock returns and beta, size, the earnings-to-price ratio, the cash flow-to-price ratio, the book-to-market equity ratio, and sales growth (SG). We find the presence of anomalies in these emerging markets. There is a conditional relationship between beta and stock returns for both countries. During months with positive market excess returns, there is a significant positive relationship. We also find a negative relationship between beta and stock returns during months with negative market excess returns. We document the existence of a negative relationship between stock returns and size for both countries. For Singapore, we also document a negative relationship between returns and SG. For Malaysia, we find a positive relationship between returns and the E/P ratio. These relationships are only significant in non-January months.     

Using Nonnormal Distributions to Analyze the Relationship Between Stock Returns in Japan and the US

The Pearson distribution system is researched and applied to financial engineering (Nagahara, Financ Eng Jpn Mark 2(2):139–154 in 1995, Financ Eng Jpn Mark 3(2):121–149 in 1996, Stat Prob Lett 43:251–264 in 1999, J Time Ser Anal 24(6):721–738 in 2003, A method of fitting multivariate nonnormal distributions to financial data. Discussion paper of Institute of Social Sciences, F-2006-2, Meiji University in 2006, Asia Pac Financial Markets 15(3–4):175–184 in 2008a). And a method of fitting multivariate nonnormal distributions by using random numbers from the Pearson distribution system was developed (Nagahara, Comput Stat Data Anal 47(1):1–29 in 2004). This method uses the grid search of the parameters for the maximum likelihood. In this paper, we adopt Grid-Computing and its middleware for the parameter sweep in order to reduce the computational time and the workload of this method. In the area of the financial risk management, it is very important to analyze the relationship between stock returns in Japan and the US. We analyze the data based on the same date and the following date because Japanese stock market opens before the US stock market opens in a day. We compare these returns by means of the multivariate nonnormal distributions by using this method. And we test the international transmission of stock markets movement. Furthermore, we obtain the optimal job schedule for our computer system using the middleware in order to reduce the computational time.     

The cross-sectional relationship between stock returns and domestic and global factors in the Chinese A-share market

By using an extension of the Fama and MacBeth cross-sectional regression model, this analysis examines the relationship between stock returns and (i) a local beta, (ii) two global betas, and (iii) some firm-specific characteristics in the Chinese A-share market. The results of the analysis suggest that neither the conditional local beta nor the global betas has a significant relationship with stock returns in A-shares. Our findings indicate that firm factors, such as the book-to-market ratio and firm size, are important in explaining stock returns. However, the size effect is sensitive to the specification of the model. Finally, the results of sub-period tests indicate that the A-share market did not become increasingly integrated with either the world stock markets or the Hong Kong stock market over the period 1995–2002.

Implied volatility and future portfolio returns

Prior studies find that the CBOE volatility index (VIX) predicts returns on stock market indices, suggesting implied volatilities measured by VIX are a risk factor affecting security returns or an indicator of market inefficiency. We extend prior work in three important ways. First, we investigate the relationship between future returns and current implied volatility levels and innovations. Second, we examine portfolios sorted on book-to-market equity, size, and beta. Third, we control for the four Fama and French [Fama, E., French, K., 1993. Common risk factors in the returns on stocks and bonds. Journal of Financial Economics 33, 3–56.] and Carhart [Carhart, M., 1997. On persistence in mutual fund performance. Journal of Finance, 52, 57–82.] factors. We find that VIX-related variables have strong predictive ability.     

Can long-term performance plans mitigate the negative effects of stock consideration and high cash for acquirers?

Following Travlos (J Finance 42: 943–963, 1987), Loughran and Vijh (J Finance 52: 1765–1790, 1997), Harford (J Finance 54: 1969–1997, 1999), and Oler (Rev Acc Stud 13: 479–511, 2008), we investigate whether acquisitions involving stock consideration and acquirers with high cash levels are associated with poor performance or not. In addition, we investigate whether including a long-term performance plan in top management’s compensation package can mitigate these negative effects. We find that acquirers with a long-term performance plan are less likely to hold a high cash balance and are less likely to use stock consideration, thus avoiding scenarios that are more likely to be value-destructive. Even if an acquirer with a long-term performance plan carries a high cash balance or uses stock, we find that the plan is associated with improved fundamental performance; however, this relationship does not flow through to improved post-acquisition returns.     

The Cross-Section of Expected Stock Returns

Two easily measured variables, size and book-to-market equity, combine to capture the cross-sectional variation in average stock returns associated with market β, size, leverage, book-to-market equity, and earnings-price ratios. Moreover, when the tests allow for variation in β that is unrelated to size, the relation between market β and average return is flat, even when β is the only explanatory variable.     

An Empirical Re-Examination of the Cross-Section of Expected Returns: UK Evidence

This paper is a study of the Fama and French (1992) analysis in the UK context. Consistent with their findings, our results do not support a positive relationship between beta and average monthly returns. We find that book-to-market equity and market leverage are consistently significant in explaining UK average returns. Contrary to the Fama-French evidence, size has an insignificant effect on average returns. A puzzling negative beta-returns relationship is found in some monthly regressions,and results based on annual data reveal a reversal of betas for the smallest-size portfolios. Some possible explanations are offered for these findings.     

Advertising intensity,investor recognition,and implied cost of capital

The main purpose of this paper is to test Merton’s (J Finance 42(3):483–510, 1987) hypothesis that better investor recognition is correlated with lower expected returns. We measure investor recognition with the firms’ advertising intensity and offer consistent evidence that higher advertising intensity is associated with lower implied cost of capital, as derived from Value Line target prices and dividend forecasts. Investor recognition plays an important role in attracting investors, improving liquidity, and ultimately reducing the cost of capital. The findings shed light on the capital market implications of advertising expenditures and complement the extant research on investor recognition.     

Monetary Policy and the Cross-Section of Expected Stock Returns

Ample evidence shows that size and book-to-market equity explain significant cross-sectional variation in stock returns, whereas beta explains little or none of the variation. Recent studies also demonstrate that proxies for monetary stringency increase the explained variation in stock returns. We reexamine a three-factor model that includes beta, size, and book-to-market equity, while allowing monetary conditions to influence the relations between these risk factors and average stock returns. We find that ex-ante proxies for monetary stringency significantly influence the relations between stock returns and all three risk factors. Additionally, all three variables are found to contribute significantly to explaining cross-sectional returns in a three-factor model that includes the monetary sector.     

Cross-sectional determinants of New Zealand share market returns

We present evidence of the cross-sectional relation between security returns, beta, firm size and book-to-market ratio over the period 1971 to 1993 on the New Zealand sharemarket. Our results suggest that the NZSE-40 market index is not a mean-variance efficient market proxy—the betas calculated with respect to it being of little use for explaining expected returns cross-sectionally. Also, there is a significant positive relation between book-to-market ratio and average return.     

Hierarchical Determinants of Brazilian Stock Returns During the 2008 Financial Crisis

Abstract:

We analyze the influence of firm- and industry-level determinants on stock returns during the 2008 financial crisis, using a hierarchical linear model to analyze the returns of 135 Brazilian firms. The impact of these determinants on stock returns has not received sufficient attention in periods of severe market decline. The following determinants were significant: (1) industry-level determinants (unlevered beta, historical sales growth, and regulated tariff), and (2) firm-level determinants (size, illiquidity, and book-to-market ratio). We also identified an indirect influence of unlevered beta over book-to-market that reflects a behavior that we call the “misconfidence effect.”