This paper mathematically transforms unobservable rational expectation equilibrium model parameters (information precision and supply uncertainty) into a single variable that is correlated with expected returns and that can be estimated with recently observed data. Our variable can be used to explain the cross section of returns in theoretical, numerical, and empirical analyses. Using Center for Research in Security Prices data, we show that a -1 sigma to +1 sigma change in our variable is associated with a 0.31% difference in average returns the following month (equaling 3.78% per annum). The results are statistically significant at the 1% level. Our results remain economically and statistically significant after controlling for stocks' market capitalizations, book-to-market ratios, liquidities, and the probabilities of information-based trading.