Public Information Arrival and Stock Return Volatility: Evidence from News Sentiment and Markov Regime-Switching Approach
42 Pages Posted: 8 Jul 2014
Date Written: July 1, 2013
Abstract
Using computational linguistic analysis of intraday firm-level news releases, this study models the relationship between public information flows and stock volatility under different regimes. We analyze how the hourly return volatility of S&P100 stocks from 2000-2010 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-turbulent) state. Furthermore, the impact of news sentiment differs across industries and firm size.
Keywords: Public Information Arrival, Stock Return Volatility, News Sentiment, Markov Regime-Switching GARCH
JEL Classification: G14, C52
Suggested Citation: Suggested Citation