Information based trade,the PIN variable,and portfolio style differences: Evidence from Tokyo stock exchange firms

We investigate whether the variables related to information based trade proposed by Easley et al. [Easley, D., Kiefer, N.M., O'Hara, M., Paperman, J.B., 1996. Liquidity, information, and infrequently traded stocks. Journal of Finance 51, 1405–1436.] help explain the daily price discovery process in an electronically order-driven market of the Tokyo Stock Exchange using the microstructure tick data. We find strong evidence that the value firms show higher probability of bad news occurrences than the growth firms. We also find that the PIN is higher for smaller firms as is the case in the U.S. With the portfolio ranking tests and the Fama and MacBeth test we find that the alpha variable, which represents the information event occurrence rate, is systematically related to required returns, while the evidence related to the PIN is weaker. In the final Fama and MacBeth test, in which the PIN or alpha variable is used as an additional explanatory variable to the benchmark Fama and French three factor model, we find that the sign of the alpha variable supports our hypothesis that the arrival of new information reduces the risk of the stock, though not significantly. We also find that the higher PIN value increases the risk of the stock, at the same time it can marginally improve the explanatory power of the multifactor model. We conclude that the PIN variable cannot be a substitutable proxy variable for the book-to-market factor unlike in the U.S., and that it is strongly related to the size variable.     

Reports of beta's death are premature: Evidence from the UK

A number of authors have found that firm size and book-to-market-value capture the cross-sectional variation in average stock returns. More importantly, these variables have been shown to out-perform the CAPM's β coefficient in explaining the cross-section of US stock returns. However, these studies all employ variants of the two-step estimator due to Fama and MacBeth (Fama, E.F., MacBeth, J.D., 1973. Risk, return and equilibrium: Empirical tests. Journal of Political Economy 71, 607–636), which impose implicitly the restriction that idiosyncratic returns are uncorrelated. In this paper we use a one-step estimator due to McElroy et al. (McElroy, M.B., Burmeister, E., Wall, K.D., 1985. Two estimators for the APT model when factors are measured. Economics Letters 19, 271–275) and find a highly significant role for β risk in the UK stock market when we allow for correlation amongst idiosyncratic returns.     

The systematic risk of corporate bonds: default risk,term risk,and index choice

In this paper, we empirically examine the systematic risk of corporate bonds in the Euro area. Based on a unique sample of 784 bonds from 1999 to 2010, we show that the systematic risk of constructed bond portfolios and individual bonds—measured against three different market indices—depends on credit quality, term risk, and index choice. A significant increase in systematic risk for lower-rated bonds is observed following the start of the financial crisis. In multi-factor models, bond portfolios load significantly on default and term risk, which are included as additional factors. Conducting Fama and MacBeth cross-sectional tests, we find that default and term risk are priced with economically relevant premiums that range from 0.35 to 0.62 % per month. Our results are robust to the inclusion of characteristics such as rating and time to maturity.     

Default Risk in Equity Returns

This is the first study that uses Merton's (1974) option pricing model to compute default measures for individual firms and assess the effect of default risk on equity returns. The size effect is a default effect, and this is also largely true for the book‐to‐market (BM) effect. Both exist only in segments of the market with high default risk. Default risk is systematic risk. The Fama–French (FF) factors SMB and HML contain some default‐related information, but this is not the main reason that the FF model can explain the cross section of equity returns.     

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.     

The cross-section of stock returns in an early stock market

Using a new dataset which contains monthly data on 1015 stocks traded on the London Stock Exchange between 1825 and 1870, we investigate the cross section of stock returns in this early capital market. Unique features of this market allow us to evaluate the veracity of several popular explanations of asset pricing behavior. Using portfolio analysis and Fama–MacBeth regressions, we find that stock characteristics such as beta, illiquidity, dividend yield, and past-year return performance are all positively correlated with stock returns. However, market capitalization and past-three-year return performance have no significant correlation with stock returns.     

Risk Interpretation of the CAPM's Beta: Evidence from a New Research Method

This study tests the validity of using the CAPM beta as a risk control in cross‐sectional accounting and finance research. We recognize that high‐risk stocks should experience either very good or very bad returns more frequently compared to low‐risk stocks, that is, high‐risk stocks should cluster in the tails of the cross‐sectional return distribution. Building on this intuition, we test the risk interpretation of the CAPM's beta by examining if high‐beta stocks are more likely than low‐beta stocks to experience either very high or very low returns. Our empirical results indicate that beta is a strong predictor of large positive and large negative returns, which confirms that beta is a valid empirical risk measure and that researchers should use beta as a risk control in empirical tests. Further, we show that because the relation between beta and returns is U‐shaped, that is, high betas predict both very high and very low returns, linear cross‐sectional regression models, for example, Fama–MacBeth regressions, will fail on average to reject the null hypothesis that beta does not capture risk. This result explains why previous studies find no significant cross‐sectional relation between beta and returns.     

The Conditional Relationship Between Beta and Returns: A Reassessment

Abstract:  Several recent empirical tests of the Capital Asset Pricing Model have been based on the conditional relationship between betas and market returns. This paper shows that this method needs reconsideration. An adjusted version of this test is presented. It is then demonstrated that the adjusted technique has similar, or lower, power to the more easily implemented CAPM test of Fama and MacBeth (1973) if returns are normally distributed.     

Foreign exchange volatility and stock returns

This paper explores whether foreign exchange volatility is a priced factor in the US stock market. Our investigation is motivated by a number of empirical as well as theoretical considerations. Empirically, Menkhoff et al. (2012) find that foreign exchange volatility is a pervasive factor across a variety of test assets. Theoretically, Shapiro (1974), Dumas (1978), and Levi (1990) imply that foreign exchange volatility can influence firms’ cash flow volatility therefore the discount rate. In terms of empirical implementation, we employ the cross-sectional regression methodology of Fama and MacBeth (1973) as well as the time-series regression approach of Fama and French (1996). For robustness, we also use the mimicking portfolio approach of Fama and French (1993). We find that foreign exchange volatility has no power to explain either the time-series or the cross-section of stock returns, which calls for more research on foreign exchange risk. Bartov et al. (1996) and Adrian and Rosenberg (2008) suggest an alternative and maybe promising direction.     

The wages of social responsibility — where are they? A critical review of ESG investing

This paper contributes both to investigating the link between the corporate social and financial performance based on environmental, social and corporate governance (ESG) ratings and to reviewing the existing empirical evidence pertaining to this relationship. The sample used includes ESG data of ASSET4, Bloomberg and KLD for the U.S. market from 1991 to 2012. The econometrical framework applies an ESG portfolio approach using the Carhart (1997) four-factor model as well as cross-sectional Fama and MacBeth (1973) regressions. Previous empirical research indicates a relationship between ESG ratings and returns. As against this, the ESG portfolios do not state a significant return difference between companies with high and low ESG ratings. Although the Fama and MacBeth (1973) regressions reveal a significant influence of several ESG variables, investors are hardly able to exploit this relationship. The magnitude and direction of the impact are substantially dependent on the rating provider, the company sample and the particular subperiod. The results suggest that investors should no longer expect abnormal returns by trading a difference portfolio of high and low rated firms with regard to ESG aspects.     

Financial Sector Risk and the Stock Returns: Evidence from Tokyo Stock Exchange Firms

We investigate whether the activity of financial firms creates value and/or risk to the economy within the asset pricing framework. We use stock return data from nonfinancial firms listed in the first section of the Tokyo Stock Exchange. The value-weighted index that is solely composed of nonfinancial firms is augmented with the index of the firms from the financial sector, and we estimate multivariate asset pricing model with these two indices. We note that our procedure can simultaneously take into account the cross-holding phenomena among Japanese firms, especially between the financial sector and the nonfinancial sector. Our augmented index model performs well both with cross-sectional Fama and MacBeth regression test and GMM test. Our two index model with additional Fama and French's HML factor can capture cross-sectional variations of the returns of sample portfolios better than the original Fama and French model can, when measured by Hansen and Jagannathan distance measure. We find that this additional new sector variable can be a substitute for Fama and French's size factor, but not related to the bond index return. This variable has similar factor characteristic as money supply growth or the term structure, but the latter variables contain more information than the former. Morever, our financial sector model helps explain the return and risk structure of Japanese firms during the so-called bubble period.     

Exploring risk premium factors for country equity returns

In this paper, we study a comprehensive set of risk premia of country equity returns for 45 countries over the sample period 2002 - 2018 in both a single and a multiple factor setting. Using a new three-pass estimation method for factor risk premia by Giglio and Xiu (2021), we find that several factors, including default risk, are also priced in country equity excess returns, controlled by the Fama–French 5-factor and Carhart models. Moreover, we apply a novel approach to investigate the multi-factor impact on country equity returns. We find that the multi-factor information, constructed from the first principal component of the statistically significant single factors, provides a consistent and stronger prediction of anomalies in country equity returns.     

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.     

The Robustness of the APT to Alternative Estimators

We test the robustness of the APT to two alternative estimation procedures: the Fama and MacBeth (1973) two-step methodology; and the one-step procedure due to Burmeister and McElroy (1988). We find that the APT is indeed sensitive to the chosen estimator and assumptions about the factor structure of stock returns. We believe that our findings have implications for the estimation of asset pricing models in general.     

Seasonality in the Risk-Return Relationship: Some International Evidence

We report evidence of seasonality in the Fama and MacBeth estimate of the CAPM-based risk premium in four stock exchanges: the NYSE and the London, Paris, and Brussels exchanges. Specifically, we found that, in Belgium and France, risk premia are positive in January and negative the rest of the year. There is no January seasonal in the U.K. risk premium. Instead, we observed in this country a positive April seasonal and a negative average risk premium over the rest of the year. In the U.S., the pattern of risk-premium seasonality coincides with the pattern of stock-return seasonality. Both are positive and significant only in January. We also found that the January risk premium in the U.S. is significantly larger than those observed in the European markets. Interestingly, the reported patterns of risk-premium seasonality in European equity markets do not fully coincide with the observed patterns of stock-return seasonality in these markets. For example, in the U.K., average stock returns are significant and positive in January and April, whereas the market risk premium is significantly positive only in April. A possible interpretation of this phenomenon is presented in the paper.     

The “forward premium puzzle” and the sovereign default risk

Carry-trade strategies which consist of buying forward high-yield currencies tend to yield positive excess returns when global financial markets are booming, whereas they generate losses during crises. Firstly, we show that the sovereign default risk, which is taken on by investing in high-yield currencies, may increase the magnitude of the gains during the boom periods and the losses during crises. We empirically test for this hypothesis on a sample of 18 emerging currencies over the period from June 2005 to September 2010, the default risk being proxied by the sovereign credit default swap spread. Relying on smooth transition regression (STR) models, we show that default risk contributes to the carry-trade gains during booms, and worsens the losses during busts. Secondly, we turn to the “Fama regression” linking the exchange-rate depreciation to the interest-rate differential. We propose a nonlinear estimation of this equation, explaining the puzzling evolution of its coefficient by the change in the market volatility along the financial cycle. Then, we introduce the default risk into this equation and show that the “forward bias”, usually evidenced by a coefficient smaller than unity in this regression, is somewhat alleviated, as the default risk is significant to explain the exchange-rate change.     

Do the Fama–French Factors Proxy for Innovations in Predictive Variables?

The Fama–French factors HML and SMB are correlated with innovations in variables that describe investment opportunities. A model that includes shocks to the aggregate dividend yield and term spread, default spread, and one‐month Treasury‐bill yield explains the cross section of average returns better than the Fama–French model. When loadings on the innovations in the predictive variables are present in the model, loadings on HML and SMB lose their explanatory power for the cross section of returns. The results are consistent with an ICAPM explanation for the empirical success of the Fama–French portfolios.     

Resolving the Presidential Puzzle

Many financial economists are puzzled by the fact that stock returns are higher under Democratic than Republican presidencies. In this paper, we test whether this return differential is explained by risk using a conditional version of the Fama and French (1993) model that allows risk to vary across political cycles. We find that the presidential puzzle can be explained when risk is properly taken into account. Much of the return differential can be attributed to the fact that Democratic presidencies are associated with higher market and default risk premiums than their Republican counterparts.     

SMB — Arousal,disproportionate reactions and the size-premium

This paper examines SMB (small minus big), the mimicking portfolio in Fama and French's [Fama, E., French, K., 1993. Common risk factors in the returns on stocks and bonds, Journal of Financial Economics 33, 3–56] three-factor asset pricing model. We do not examine whether SMB is a factor in explaining the cross-section of returns. This paper's focus is why S is greater than B. After controlling for market-pervasive effects, we argue that the small-firm premium is driven by both investors' emotional arousal (proxied by the turnover ratio) and their disproportionate reactions to arousing stimuli.     

On the robustness of higher-moment factors in explaining average expected returns: Evidence from Australia

This study tests the importance of systematic skewness and systematic kurtosis of Australian stock returns in the spirit of the higher-moment asset pricing model. We apply the Dagenais and Dagenais (1997) higher-moment estimators to correct for the errors-in-variables (EIVs) problems commonly found in the Fama and MacBeth (1973) two-pass regression methodology. After correcting for the EIVs problems, the two higher-moment factors, especially systematic skewness, are important in pricing Australian stocks. Systematic kurtosis appears to replace beta which plays a diminished role in the heavy-tailed return distribution.