Identification of Fed monetary policy shocks is complex, in light of the distinct policymaking regimes before, during, and after the ZLB period of December 2008 to December 2015. We develop a heteroscedasticity-based partial least squares approach, combined with Fama-MacBeth style cross-section...

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,...

Using high frequency data, we develop an event study method to test for level shifts in beta and measure abnormal returns for events that produce such level shifts. Using this method, we estimate abnormal returns for the Troubled Asset Relief Program (TARP) announcement and find that its...

We investigate the uncertainty dynamics surrounding extreme weather events through the lens of option and stock markets by identifying market responses to the uncertainty regarding both potential hurricane landfall and subsequent economic impact. Stock options on firms with establishments...