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

Yanlin Shi, Kin-Yip Ho and Wai-Man Liu

International Review of Economics & Finance, 2016, vol. 42, issue C, 291-312

Abstract: 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.

Keywords: Public information arrival; Stock return volatility; News sentiment; Markov Regime-Switching GARCH (search for similar items in EconPapers)
JEL-codes: C52 G14 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1059056015002294
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reveco:v:42:y:2016:i:c:p:291-312

DOI: 10.1016/j.iref.2015.12.003

Access Statistics for this article

International Review of Economics & Finance is currently edited by H. Beladi and C. Chen

More articles in International Review of Economics & Finance from Elsevier
Bibliographic data for series maintained by Catherine Liu ().