We develop a model of information acquisition in capital markets and test its predictions in the data. In the model, investors are uncertain about the returns to acquiring private information before they acquire it. As a result, investors use prior prices and public information as a screen to estimate the value of private information acquisition and efficiently allocate their limited information-processing capacity across firms. The model predicts that larger unexplained price movements lead to more private information acquisition, higher future price volatility, and higher future trading volumes. Using fine-grained data measuring information acquisition on Edgar and Bloomberg, we provide empirical evidence in support of the model’s predictions.