The U.S. stock market’s return during the first month of a quarter correlates strongly with returns in future months, but the correlation is negative if the future month is the first month of a quarter, and positive if it isn’t. These correlations offset, consistent with the well-known near-zero unconditional autocorrelation, yet they are pervasive, present across industries and countries. The pattern accords with a model in which investors extrapolate announced earnings to predict future earnings, not recognizing that earnings in the first month of a quarter are discretely less predictable than in prior months. Survey data support the model.

We reconsider the excess volatility puzzle through the lens of a model in which agents believe they can predict dividend growth when in fact they cannot. Besides excess volatility in the time series, the model explains the value premium, and the explanatory power of the value factor. In support of the model, we show that analysts’ earnings forecasts align with market valuation and that analysts are far more optimistic about growth stocks than they are about value stocks. Using both survey and price data, we show that the same mechanism can explain the excess returns earned by investing in high-interest rate currencies. (JEL G12, G15, G41)

This paper develops an asset market-based test for preference for the timing of resolution of uncertainty. Our main theorem provides a characterization of preference for early resolution of uncertainty in terms of the risk premium realized during the period when the informativeness of macroeconomic announcements is resolved. Empirically, we find support for preference for early resolution of uncertainty based on evidence on the dynamics of the implied volatility of S&P 500 index options before Federal Open Market Committee announcements. (JEL D81, D83, G13, G14, G41)