Topic：Asset Pricing with Learning about Disaster Risk
Speaker：Yang Lu
Affiliation: Hong Kong University of Science and Technology
Time：2:00-3:30pm, October 23
Location：Room 217, Guanghua New Building, Peking University
Abstract: This paper studies asset pricing in an endowment economy with learning about disaster risk. The existing literature on rare disaster models generally assumes complete information about disasters. This literature is able to match a large range of asset pricing moments but can only generate time-varying risk premia under the assumption of exogenous variation in disaster probability. We extend this literature to allow for two sources of uncertainty about a rare disaster: (1) the lack of historical data for a rare disaster results in unknown parameters of the disaster process; (2) the occurrence of a rare disaster takes time to unfold and is thus unobservable directly. We show that when agents employ Bayesian learning rules, learning endogenously introduces time-varying risk premia: Time variation of beliefs generates time variation in returns and the model can hence better explain large stock market movements during recessions even in the absence of disasters. Feeding U.S. consumption data of the 20th century into the model shows that the model improves significantly on matching equity returns relative to a model without learning and illustrates how the disaster belief varies over time. The framework allows us to reconcile the widely held belief during the recent financial crisis that the economy might be at the onset of another great depression.
