Based on a generalization of the Campbell and Shiller (1988) approach to a framework with regime-switching parameters and variances, we analyze the conditional variance decomposition of the market return over the business cycle. Discount-rate news is more important than cash-flow news in determining the conditional variance of the market return in recessions, while the opposite holds true in expansions. In an asset pricing model with regime-switching fundamentals, the fact that discount-rate news is more sensitive to changes in investors’ beliefs about the state of the economy, which are more volatile in recessions, provides a potential explanation.

We compare statistical and economic measures of forecasting performance across a large set of stock return prediction models with time-varying mean and volatility. We find that it is very common for models to produce higher out-of-sample mean squared forecast errors than a model assuming a constant equity premium, yet simultaneously add economic value when their forecasts are used to guide portfolio decisions. While there is generally a positive correlation between a return prediction model’s out-of-sample statistical performance and its ability to add economic value, the relation tends to be weak and only explains a small part of the cross-sectional variation in different models’ economic value.