Economics at your fingertips  

Baidu news information flow and return volatility: Evidence for the Sequential Information Arrival Hypothesis

Dehua Shen (), Xiao Li and Wei Zhang

Economic Modelling, 2018, vol. 69, issue C, 127-133

Abstract: This paper employs Baidu News as the proxy for information flow and investigates competing hypotheses on the relationships between information flow and return volatility in Chinese stock market. The empirical results show that: (1) trading volume and return volatility are not driven by the same variable, i.e., the information flow, and thus contradicts the predication of the Mixture of Distribution Hypothesis (MDH); (2) there exist significant lead-lag relationships between information flow and return volatility, which is in accordance with the Sequential Information Arrival Hypothesis (SIAH); (3) these findings are robust to alternative measurement of return volatility and subsample analysis. Generally speaking, these findings contradict the prediction of MDH and support the SIAH.

Keywords: Return volatility; Sequential Information Arrival Hypothesis; Mixture of Distribution Hypothesis; Information flow; Baidu News (search for similar items in EconPapers)
JEL-codes: G12 G14 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3) Track citations by RSS feed

Downloads: (external link)
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:

Access Statistics for this article

Economic Modelling is currently edited by S. Hall and P. Pauly

More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().

Page updated 2019-03-31
Handle: RePEc:eee:ecmode:v:69:y:2018:i:c:p:127-133