News and return volatility of Chinese bank stocks

Kin Yip Ho; Yanlin Shi; Zhaoyong Zhang

doi:10.1016/j.iref.2018.12.003

News and return volatility of Chinese bank stocks

Kin Yip Ho, Yanlin Shi, Zhaoyong Zhang^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

21 Citations (Scopus)

Abstract

Using the comprehensive RavenPack Dow Jones News Analytics (DJNA) database that captures firm-specific news releases and their sentiment scores at high frequencies, we examine the contemporaneous correlation as well as the lead-lag relation between news and return volatility of major commercial banks listed on the Chinese stock market. Contrary to the Sequential Information Arrival Hypothesis (SIAH), most of the Chinese bank stocks do not exhibit significant lead-lag relations between news and volatility. However, there is substantial evidence that news is strongly correlated with return volatility in all the stocks, consistent with the Mixture of Distributions Hypothesis (MDH). Further analysis based on news sentiment scores suggests that positive news arrivals influence return volatility more strongly, compared with negative news. In addition, there is some evidence indicating that news arrivals contribute to the persistence in return volatility.

Original language	English
Pages (from-to)	1095-1105
Number of pages	11
Journal	International Review of Economics and Finance
Volume	69
DOIs	https://doi.org/10.1016/j.iref.2018.12.003
Publication status	Published - Sept 2020

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title = "News and return volatility of Chinese bank stocks",

abstract = "Using the comprehensive RavenPack Dow Jones News Analytics (DJNA) database that captures firm-specific news releases and their sentiment scores at high frequencies, we examine the contemporaneous correlation as well as the lead-lag relation between news and return volatility of major commercial banks listed on the Chinese stock market. Contrary to the Sequential Information Arrival Hypothesis (SIAH), most of the Chinese bank stocks do not exhibit significant lead-lag relations between news and volatility. However, there is substantial evidence that news is strongly correlated with return volatility in all the stocks, consistent with the Mixture of Distributions Hypothesis (MDH). Further analysis based on news sentiment scores suggests that positive news arrivals influence return volatility more strongly, compared with negative news. In addition, there is some evidence indicating that news arrivals contribute to the persistence in return volatility.",

keywords = "Chinese stock markets, Lead-lag relations, News sentiment, Stock return volatility",

author = "Ho, {Kin Yip} and Yanlin Shi and Zhaoyong Zhang",

note = "Publisher Copyright: {\textcopyright} 2018",

year = "2020",

month = sep,

doi = "10.1016/j.iref.2018.12.003",

language = "English",

volume = "69",

pages = "1095--1105",

journal = "International Review of Economics and Finance",

issn = "1059-0560",

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T1 - News and return volatility of Chinese bank stocks

AU - Ho, Kin Yip

AU - Shi, Yanlin

AU - Zhang, Zhaoyong

PY - 2020/9

Y1 - 2020/9

N2 - Using the comprehensive RavenPack Dow Jones News Analytics (DJNA) database that captures firm-specific news releases and their sentiment scores at high frequencies, we examine the contemporaneous correlation as well as the lead-lag relation between news and return volatility of major commercial banks listed on the Chinese stock market. Contrary to the Sequential Information Arrival Hypothesis (SIAH), most of the Chinese bank stocks do not exhibit significant lead-lag relations between news and volatility. However, there is substantial evidence that news is strongly correlated with return volatility in all the stocks, consistent with the Mixture of Distributions Hypothesis (MDH). Further analysis based on news sentiment scores suggests that positive news arrivals influence return volatility more strongly, compared with negative news. In addition, there is some evidence indicating that news arrivals contribute to the persistence in return volatility.

AB - Using the comprehensive RavenPack Dow Jones News Analytics (DJNA) database that captures firm-specific news releases and their sentiment scores at high frequencies, we examine the contemporaneous correlation as well as the lead-lag relation between news and return volatility of major commercial banks listed on the Chinese stock market. Contrary to the Sequential Information Arrival Hypothesis (SIAH), most of the Chinese bank stocks do not exhibit significant lead-lag relations between news and volatility. However, there is substantial evidence that news is strongly correlated with return volatility in all the stocks, consistent with the Mixture of Distributions Hypothesis (MDH). Further analysis based on news sentiment scores suggests that positive news arrivals influence return volatility more strongly, compared with negative news. In addition, there is some evidence indicating that news arrivals contribute to the persistence in return volatility.

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JO - International Review of Economics and Finance

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News and return volatility of Chinese bank stocks

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