Return Predictability in Recessions: an Asset Pricing Perspective

I show that the dividend-price ratio predicts aggregate stock market returns with higher precision during recessions than in expansions, in a way that is both statistically and economically significant. This empirical evidence cannot be reconciled with three popular asset pricing approaches: habit-persistence (Campbell and Cochrane (1999)), long-run risk (Bansal and Yaron (2004)) and rare disasters (Gourio (2012)). Instead, I propose a long-run risk model with three new features. First, I link volatility and left tail events in consumption and dividend growth: positive shocks to volatility lead to a higher probability of observing negative growth rates. Second, I introduce negative skewness: investors require higher risk premia when they anticipate negative future consumption growth. Third, the model also incorporates the negative relation between the conditional mean and the conditional variance of growth rates because periods of high volatility are more likely to generate negative growth rates. These features, for which I find strong support in the data, allow the model to match the business-cycle fluctuations in return predictability observed empirically.