We study whether bond markets efficiently incorporate information about risk. Our results suggest that bond investors underreact to risk information embedded in earnings announcements. A one-standard deviation increase in unexpected risk is associated with a three-day abnormal bond return about...

Prior-biased inference is a subset of confirmation bias - it suggests that agents update from observed signals in a way that favors their current beliefs. There is experimental evidence of prior-biased inference, but field evidence is much more limited. We provide evidence of biased inference...

We use the k-nearest neighbors (i.e., k-NN) algorithm to forecast a firm’s annual earnings by matching its recent trend in annual earnings to historical earnings sequences of “neighbor” firms. Our forecasts are more accurate than forecasts obtained from the random walk, the regression...

On average, across the years 1980 to 2018, almost 8.5 percent of firms on the Compustat Annual data set, which had earnings observations in year t-1, did not have earnings observations in year t. Because these disappearances were not random, there is attrition bias in estimates of earnings...