Researches Related Stock Return

Sharpe (1964) and Lintner (1965) proposed the Capital Asset Pricing Model (CAPM) and

find that there was a positive relation between the expected returns and market βs, and market βs could explain the change of the cross-section returns. In other words, knowing market βs can estimate the asset returns.

Black, Jensen and Scholes (1972) selected monthly stock returns listed on NYSE from January 1926 to March 1966 and estimated βs of stocks. They used βs to sort all stock into ten portfolios. The empirical results showed that there was a linearly positive relation between market risk and stock returns.

Fama and MacBeth (1973) used the monthly returns of common stock listed on NYSE as a sample from January 1926 to June 1968. They demonstrated that market risk can complete explain return and there existed a significantly positive relation between market risk and returns.

Although CAPM has long shaped the way academics and practitioners, since 1980s some researchers found that some phenomena that CAPM cannot explain exist. Market βs cannot complete explain asset pricing, and “anomalies” which affect asset pricing exist, which is demonstrated such as size effect, price earning ratio, book-to-market effect etc.

Banz (1981) tested the relation between total market value of common stocks and returns.

Banz used a generalized asset pricing model on a sample which were monthly stock returns listed NYSE from 1936 to 1975, and constructed portfolios by using market value of common stock and market risk, and used generalized least square regression analysis. He found in general small firms had bigger risk-adjusted returns than large firms, and that is, size effect existed.

Reinganum (1981) examined the earning/price and market value effects on stock returns.

He collected stock listed NYSE and AMEX between 1963 and 1977 and constructed ten portfolios based on market value at the end of very year. The empirical results showed that the average returns of small firms were bigger 20% than large firm, and the effect existed at least two years.

Chan, Chen and Hsieh (1985) investigated the firm size effect for the period 1958 to 1977 by using a multi-factor pricing model. They found that the risk-adjusted difference in returns between the top five percent and the bottom five percent of the NYSE firms is about one to two percent a year, a drop from about twelve percent per year before risk adjustment. The variable most responsible for the adjustment is the sensitivity of asset returns to the changing risk premium, measured by the return difference between low-grade bonds and long-term government bonds.

Chan and Chen (1991) showed differences in structural characteristics that lead firms of different sizes to react differently to the same economic news. They found that a small firm portfolio contains a large proportion of marginal firms. They found that return indices are important in explaining the time-series return difference between small and large firms.

Fama and French (1992) investigated all NYSE, AMEX, and NASDAQ stocks that met the CRSP-COMPUSTAT data requirements, and divided stocks into ten portfolios sorted by size and book-to-market equity. They found that the two variables, size and book-to-market equity, combined to capture the cross-sectional variation in average stock returns associated with market beta, size, leverage, book-to-market equity, and earnings-price ratios, and when the tests allow for variation in beta that is unrelated to size, the relation between market beta and average return is flat, even when beta is the only explanatory variable.

Fama and French (1993,1995) confirmed that portfolio constructed to mimic risk factors related to size and book-to-market equity add substantially to the variation in stock returns explained by a market portfolio. They showed that a three-factor model that included a market factor and risk factors related to size and book-to-market equity seemed to capture the cross-section of average stock returns.

Dichev (1998) finds that bankruptcy risk is not rewarded by higher returns and concludes that a distress factor cannot be at the origin of the size and book-to-market effect. In particular, he finds that portfolios formed on the basis of a distress measure, whether Altman’s Z-score or

Ohlson’s O-score, have returns inversely related to bankruptcy risk, a high probability of default is associated with low average returns. After examining the cross-sectional relation between stock returns and bankruptcy measures, as well as size and book-to-market, he concludes that the fact that firms with low bankruptcy risk outperform firms with high bankruptcy risk can only be explained by a mispricing argument.

Griffin and Lemmon (2002) measured bankruptcy risk by using the Ohlson’s O-score, and found that the low return of high default-risk firms was driven by low book-to-market stocks with extremely low returns. They attributed these very low returns to mispricing due to a high degree of information asymmetry proxied by low analyst coverage.

Vassalou and Xing (2004) used a sample from January 1971 to December 1999 and the distance to default implied by the Merton (1974) model to conclude that the size and book-to-market effects exist only in the quintiles defined by high default risk stocks. They also provided evidence that distress risk is priced in the cross-section and that the Fama and French (FF) factors capture some of the default-related information.