Abstract
I suggest a characteristic-based covariance model that directly links the predetermined fi rm characteristics to time-varying covariance risk. Using a large cross section of individual stock-level data, I parsimoniously estimate both conditional expected returns and conditional covariances as functions of fi rm characteristics. I fi nd a strong and positive intertemporal risk-return relation on individual stocks. In comparison to the Fama-French three-factor model, the characteristic-based covariance model substantially reduces the pricing errors of characteristic-sorted portfolios on size, book-to-market, accruals, asset growth, investment-to-assets, return-on-assets, net stock issues, financial distress, and momentum. Portfolio tests similar to Daniel and Titman (1997) suggest that firm characteristics, mainly through the characteristic-based covariance structure of returns, appear to explain the cross section of average stock returns.
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