Public information arrival and stock return volatility: Evidence from news sentiment and Markov Regime-Switching Approach

•We use a novel news database that is not subject to the endogeneity problem.•News sentiment has significant positive effects on stock return volatility.•Magnitudes of effects of negative and positive news are state-dependent.•News effects are different across sectors and firm sizes.

Using computational linguistic analysis of intraday firm-level news releases, this study models the relation between public information flows and stock volatility under different regimes. We analyze how the hourly return volatility of S&P100 stocks from 2000 to 2010 are linked to the various linguistics-based sentiment scores of the news releases, which are obtained from the RavenPack News Analytics Database. Results from the Markov Regime-Switching GARCH (MRS-GARCH) model indicate that firm-specific news sentiment is more significant in quantifying intraday volatility persistence in the calm (low-volatility) state than the turbulent (high-volatility) state. Furthermore, the impact of news sentiment differs across industries and firm size.