This paper uses a dataset of more than 900,000 news stories to test whether news can predict stock returns. We measure sentiment with a proprietary Thomson-Reuters neural network. We find that daily news predicts stock returns for only 1 to 2 days, confirming previous research. Weekly news,...

This paper constructs a leading macroeconomic indicator from microeconomic data using recent machine learning techniques. Using tree-based methods, we estimate probabilities of default for publicly traded non-financial firms in the United States. We then use the cross-section of out-of-sample...

We present a dynamic structural model of subprime adjustable-rate mortgage (ARM) borrowers making payment decisions taking into account possible consequences of different degrees of delinquency from their lenders. We empirically implement the model using unique data sets that contain information...