We model how investor learning about monetary-policy transmission impacts asset prices. In an asset-pricing model, investors learn from realized inflation surprises how effectively monetary policy steers future inflation. Downward revisions in perceived effectiveness raise expected inflation persistence, increasing return volatility and risk premia. These effects intensify when policy deviates significantly from neutral or monetary-transmission uncertainty is high. We estimate the model using U.S. macro and policy data from 1954 to 2023. The resulting dynamics align with observed patterns in equity returns and volatility. Empirical tests support the model’s core prediction: investor learning turns central-bank credibility into a priced risk factor.

Recent empirical findings document downward-sloping term structures of equity return volatility and risk premia. An equilibrium model with rare disasters followed by recoveries helps reconcile theory with empirical observations. Indeed, recoveries outweigh the upward-sloping effect of time-varying disaster intensity and expected growth, generating downward-sloping term structures of dividend growth risk, equity return volatility, and equity risk premia. In addition, the term structure of interest rates is upward-sloping when accounting for recoveries and downward-sloping otherwise. The model quantitatively reconciles high risk premia and a low risk-free rate with the shape of the term structures, which are at odds in other models.

The term structure of equity risk has been shown to be downward sloping. We capture this feature using return dynamics driven by both a transitory and a permanent component. We study the asset allocation and portfolio performance when transitory and permanent components cannot be observed and therefore need to be estimated. Strategies that account for the observed timing of equity risk outperform those that do not, particularly so out of sample. Indeed, the mean (median) certainty equivalent return increases from about 13% (12%) to about 21% (15%) because properly modeling the timing of equity risk implies surges in portfolio returns.