We develop a return variance decomposition model to separate the role of different types of information and noise in stock price movements. We disentangle four components: market-wide information, private firm-specific information revealed through trading, firm-specific information revealed...

I study how the diffusion of market news, firm-specific news, and noise among firms affects stock returns in a global network. I use a structural vector auto-regression to estimate market news, firm-specific news, and noise. To determine global network linkages, I exploit analyst co-coverage....

We study the impact of the arrival of macroeconomic news on the informational and noise-driven components in high-frequency quote processes and their conditional variances. We decompose bid and ask returns into a common ("efficient return") factor and two market-side-specific components...

We study the impact of the arrival of macroeconomic news on the informational and noise-driven components in high-frequency quote processes and their conditional variances. Bid and ask returns are decomposed into a common ("efficient return") factor and two market-side-specific components...

We study the impact of the arrival of macroeconomic news on the informational and noise-driven components in high-frequency quote processes and their conditional variances. Bid and ask returns are decomposed into a common ("efficient return") factor and two market-side-specific components...