Predicting Stock Returns in a Cross-Section: Do Individual Firm Characteristics Matter?
It is a common wisdom that individual stocks' returns are difficult to predict, though in many situations it is important to have such estimates at our disposal. In particular, they are needed to determine the cost of capital. Market equilibrium models posit that expected returns are proportional to the sensitivities to systematic risk factors. Fama and French (1993) three-factor model explains the stock returns premium as a sum of three components due to different risk factors: the traditional CAPM market beta, and the betas to the returns on two portfolios, "Small Minus Big" (the differential in the stock returns for small and big companies) and "High Minus Low" (the differential in the stock returns for the companies with high and low book-to-price ratio). The authors argue that this model is sufficient to capture the impact on returns of companies' accounting fundamentals, such as earnings-to-price, cash flow-to-price, past sales growth, long term and short-term past earnings. Using a panel of stock returns and accounting data from 1979 to 2008 for the companies listed on NYSE, we show that this is not the case, at least at individual stocks' level. According to our findings, fundamental characteristics of companies' performance are of higher importance to predict future expected returns than sensitivities to the Fama and French risk factors. We explain this finding within the rational pricing paradigm: contemporaneous accounting fundamentals may be better proxies for the future sensitivity to risk factors, than the historical covariance estimates
|Date of creation:||May 2009|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: + 33 44 07 81 00
Fax: + 33 1 44 07 83 01
Web page: http://centredeconomiesorbonne.univ-paris1.fr/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:mse:cesdoc:09037. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Lucie Label)
If references are entirely missing, you can add them using this form.