I document that dividend growth and returns on the aggregate U.S. stock market are more correlated with consumption growth in bad economic times. In a consumption-based asset pricing model with a generalized disappointment-averse investor and small, IID consumption shocks, this feature results in a realistic equity premium despite low risk aversion. The model is consistent with the main facts about stock market risk premiums inferred from equity index options, remains tightly parameterized, and allows for analytical solutions for asset prices. An extension with non-IID dynamics accounts for excess volatility and return predictability, while preserving the model’s consistency with option moments.

We use option prices and realized returns to decompose risk premia into different parts of the return state space. In the data, 8/10 of the average equity premium is attributable to monthly returns below −10%, but returns below −30% matter very little. In contrast, prominent asset pricing models based on habits, long-run risks, rare disasters, undiversifiable idiosyncratic risk, and constrained intermediaries attribute the premium predominantly to returns above −10% or to the extreme left tail. We show that the discrepancy arises from an unrealistically small price of risk for stock market tail events in the models.

We propose a statistical methodology for jointly estimating the pricing kernel and conditional physical return densities from option prices. Pricing kernel estimates show that negative stock market returns are significantly more painful to investors in low-volatility periods. Density estimates reflect a significantly positive risk–return trade-off, suggest that Martin’s (2017) lower bound on the equity premium is violated in high-volatility periods, and provide new evidence on the variance premium’s predictive power for excess returns as well as the co-movement between higher return moments. Lastly, we show that leading macrofinance models are at odds with basic features of conditional stock market risks and risk pricing.

This paper shows that standard disaster risk models are inconsistent with movements in stock market volatility and credit spreads during disasters. We resolve this shortcoming by incorporating persistent macroeconomic crises into a structural credit risk model. The model successfully captures the joint dynamics of aggregate consumption, financial leverage, and asset market risks, both unconditionally and during crises. Leverage strongly amplifies fundamental shocks by continuing to rise while crises endure. We structurally estimate the model and show that it replicates the firm-level implied volatility curve and its cross-sectional relation with observable proxies of default risk.