Using a simple dynamic asset pricing model, this paper investigates the relationship between the precision of public information about economic growth and stock market returns. After fully characterizing expected returns and conditional volatility, I show that (i) higher precision of signals tends to increase the risk premium, (ii) when signals are imprecise the equity premium is bounded above independently of investors' risk aversion, (iii) return volatility is U‐shaped with respect to investors' risk aversion, and (iv) the relationship between conditional expected returns and conditional variance is ambiguous.

Previous work on information and financial markets has focused on a special set of assumptions: agents have exponential utility, and random variables are normally distributed. These assumptions are often necessary to obtain closed-form solutions. We present an example with alternative assumptions, and demonstrate that some of the conclusions from previous literature fail to hold. In particular, we show that in our example, as more agents acquire information, prices do not necessarily become more informative, and agents may have greater incentive to acquire information. Learning can therefore be a strategic complement, allowing for the possibility of multiple equilibria.