I generalize the long-run risks (LRR) model of Bansal and Yaron (2004) by incorporating recursive smooth ambiguity aversion preferences from Klibanoff et al. (2005, 2009) and time-varying ambiguity. Relative to the Bansal-Yaron model, the generalized LRR model is as tractable but more flexible...

We examine the effects of parameter uncertainty and Bayesian learning on equilibrium asset prices when all the structural parameters of the aggregate consumption and dividend growth rate processes are unknown. With realistic calibration of a parsimonious set of prior parameters, the model...

We incorporate joint learning about state and parameter into a consumption-based asset pricing model with rare disasters. Agents are uncertain whether a negative shock signals the onset of a disaster or how much long-term damage a disaster will cause and they update their beliefs over time. The...

I consider a consumption based asset pricing model where the consumer does not know if shocks to dividends are stationary (temporary) or non-stationary (permanent). The agent uses a Bayesian learning algorithm with a bias towards recent observations to assign probability to each process. While...

In this paper, we examine how learning about disaster risk affects asset pricing in an endowment economy. We extend the literature on rare disasters by allowing for two sources of uncertainty: (1) the lack of historical data results in unknown parameters for the disaster process, and (2) the...

We show that the S&P 500’s instantaneous response to surprises in U.S. macroeconomic announcements depends on the level of long-term stock market volatility. When long-term volatility is high, stock returns are more sensitive to news, and there is a pronounced asymmetry in the response to good...