Existing high-frequency monetary policy shocks explain surprisingly little variation in stock prices and exchange rates around FOMC announcements. Further, both of these asset classes display heightened volatility relative to non-announcement times. We use a heteroskedasticity-based procedure to...

Central banks across the globe introduced large-scale asset purchase programs to address the unprecedented circumstances experienced during the pandemic. Many of these programs were announced as open-ended to shock-and-awe market participants and restore confidence in financial markets. This...

We integrate a high-frequency monetary event study into a mixed-frequency macro-finance model and structural estimation. The model and estimation allow for jumps at Fed announcements in investor beliefs, providing granular detail on why markets react to central bank communications. We find that...

We study how the arrival of macro-news affects the stock market's ability to incorporate the information in firm-level earnings announcements. Existing theories suggest that macro and firm-level earnings news are attention substitutes; macro-news announcements crowd out firm-level attention,...

Financial reports present assets, liabilities, and earnings on a nominal basis (unadjusted for inflation). Using a novel dataset of nearly a century of financial reports, this paper examines whether and how inflation affects the relation between accounting earnings and stock market value, i.e.,...

We study how the social transmission of public news influences investors' beliefs and securities markets. Using an extensive dataset to measure investor social networks, we find that earnings announcements from firms in higher-centrality locations generate stronger immediate price and trading...

News media operate in two-sided markets, offering bundles of content to readers as well as selling readers' attention to advertisers. Technological innovations in content delivery, such as the advent of broadcast television or of the Internet, affect both sides of the market, threatening the...

Media outlets are increasingly owned by conglomerates, inducing a conflict of interest: a media outlet can bias its coverage to benefit companies in the same group. We test for bias by examining movie reviews by media outlets owned by News Corp.--such as the Wall Street Journal--and by Time...

Using text from 200 million pages of 13,000 US local newspapers and machine learning methods, we construct a 170-year-long measure of economic sentiment at the country and state levels, that expands existing measures in both the time series (by more than a century) and the cross-section. Our...

A war-related factor model derived from textual analysis of media news reports explains the cross section of expected asset returns. Using a semi-supervised topic model to extract discourse topics from 7,000,000 New York Times stories spanning 160 years, the war factor predicts the cross section...