Learning, slowly unfolding disasters, and asset prices

We develop a model that generates slowly unfolding disasters not only in the macroeconomy but also in financial markets. In our model, investors cannot exactly distinguish whether the economy is experiencing a mild/temporary downturn or is on the verge of a severe/prolonged disaster. Due to imperfect information, disaster periods are not fully identified by investors ex ante. Bayesian learning induces equity prices to gradually react to persistent consumption declines, which plays a critical role in explaining the VIX, variance risk premium, and put-protected portfolio returns. We show that our model can rationalize the market patterns of recent major crises, such as the dot-com bubble burst, Great Recession, and COVID-19 crisis, through investors' belief channel.