This paper explores the ability of conditional versions of the CAPM and the consumption CAPM—jointly the (C)CAPM—to explain the cross section of average stock returns. Central to our approach is the use of the log consumption–wealth ratio as a conditioning variable. We demonstrate that such conditional models perform far better than unconditional specifications and about as well as the Fama-French three-factor model on portfolios sorted by size and book-to-market characteristics. The conditional consumption CAPM can account for the difference in returns between low-book-to-market and high-bookto-market portfolios and exhibits little evidence of residual size or book-to-market effects. We are grateful to Eugene Fama and Kenneth French for graciously providing the

We construct a dynamic general equilibrium production economy to explicitly link expected stock returns to firm characteristics such as firm size and the book-to-market ratio. Stock returns in the model are completely characterized by a conditional capital asset pricing model (CAPM). Size and book-to-market are correlated with the true conditional market beta and therefore appear to predict stock returns. The cross-sectional relations between firm characteristics and returns can subsist even after one controls for typical empirical estimates of beta. These findings suggest that the empirical success of size and book-to-market can be consistent with a single-factor conditional CAPM model. We gratefully acknowledge the helpful comments of Andy Abel, Jonathan Berk, Michael

and an anonymous referee who greatly helped to improve the paper. The paper has also strongly benefited from comments of participants of the Market Microstructure and High Frequency Data Conference, Sandbjerg, August 2001, the 64th annual meeting of the “Verband der Hochschullehrer für Betriebswirtschaft”, Munich,

Association Meetings (Maastricht) and a referee and the editor, Stephen Brown, for helpful comments. We are grateful to Anchada Charoenrook and Jennifer Conrad for providing us with Amihud factor. We thank Morgan Stanley for research support. The authors are solely responsible for the contents of this paper. Factoring Information into Returns We examine the potential profits of trading on a measure of private information (pin) in a stock. A zero-investment portfolio which is size neutral, but long in high pin stocks and short in low pin stocks earns a significant abnormal return. The Fama-French, momentum and liquidity factors do not explain this return. However, significant covariation in returns exists among high pin stocks and among low pin stocks, suggesting that pin might proxy for an underlying factor. We create a pin factor as the monthly return on the zero-investment portfolio above and show that it is successful in explaining returns to independent pin-size portfolios. We also show that it is robust to inclusion of the Pastor-Stambaugh liquidity factor and the Amihud illiquidity factor. We argue that information remains an important determinant of asset returns even in the presence of these additional factors. Factoring Information into Returns I.

Abstract. Size and book to market ratio are both highly correlated with the average returns of common stocks. Fama and French (1993) argue that these effects are proxies for factors of risk. In this study, we try to test the three factor model of Fama and French and the Capital Asset Pricing Model on French Stock Market. We use returns on the Fama and French six portfolios sorted by size and book to market ratio. The sample is from July 1976 to June 2001. Our results show that the three factor model explains better the common variation in stock returns than the capital asset pricing model. Moreover, both the CAPM and the three factor model do a good job in explaining the cross section of stock returns. We test the three factor model with a set of market portfolios and we show that all market portfolios capture the common variation in stock returns. However, only the value-weight market portfolio can explain the cross-section in the stock returns. Finally, we test the January effet in the French case and we show that there is no January effect for both the dependent variable (stock portfolios) and the explanatory variables (the market, HML and SMB).