We investigate, in a theoretical framework, the joint role played by investors' attention to news and learning uncertainty in determining asset prices. The model provides two main predictions. First, stock return variance and risk premia increase with both attention and uncertainty. Second, this increasing relationship is quadratic. We empirically test these two predictions, and we show that the data lend support to the increasing relationship. The evidence for a quadratic relationship is mixed. Overall, our study shows theoretically and empirically that both attention and uncertainty are key determinants of asset prices.

We investigate, in a theoretical framework, the joint role played by investors' attention to news and learning uncertainty in determining asset prices. The model provides two main predictions. First, stock return variance and risk premia increase with both attention and uncertainty. Second, this increasing relationship is quadratic. We empirically test these two predictions, and we show that the data lend support to the increasing relationship. The evidence for a quadratic relationship is mixed. Overall, our study shows theoretically and empirically that both attention and uncertainty are key determinants of asset prices.

Persistence risk is an endogenous source of risk that arises when a rational agent learns about the length of business cycles. Persistence risk is positive during recessions and negative during expansions. This asymmetry, which solely results from learning about persistence, causes expected returns, return volatility, and the price of risk to rise during recessions. Persistence risk predicts future excess returns, particularly at 3- to 7-year horizons. Its predictability is strongest around business-cycle peaks and troughs. We confirm the model’s predictions in the data and provide evidence that persistence risk is priced in financial markets.Received October 13, 2017; editorial decision September 19, 2018 by Editor Stijn Van Nieuwerburgh.