INTERNATIONAL STOCK MARKET COMOVEMENT AND NEWS

• Author: Markus Höchstötter,Ryan Riordan,Stephan Meyer,Andreas Storkenmaier
• Published date: 01 December 2014
• DOI: http://doi.org/10.1111/jfir.12046
• Date: 01 December 2014

INTERNATIONAL STOCK MARKET COMOVEMENT AND NEWS

Markus Höchstötter and Stephan Meyer

Karlsruhe Institute of Technology

Ryan Riordan

Queen’s University–Queen’s School of Business

Andreas Storkenmaier

Karlsruhe Institute of Technology

Abstract

We explore how news comovement drives a portion of stock return comovement using

the Thomson Reuters international business news database. We develop a measure of

news comovement similar in design to a well-known measure of stock return

comovement and find that news helps explain country-level stock market comovement.

Our results are novel in that we find that more news comovement is related to higher stock

market comovement. The explanatory power of news comovement is found to be

particularly strong in countries that have low total market capitalization, are more corrupt,

and have lower accounting standards.

JEL Classification: G14, G15, G18

I. Introduction

Researchers have found numerous partial explanations for stock return comovement, yet

no clear picture has emerged. Two common explanations for comovement focus on the

role of investor behavior and comovement in firm fundamentals in stock return

comovement. In contrast to the literature that has concentrated more on the frictions or

behavioral explanations for comovement, such as Barberis, Shleifer, and Wurgler (2005),

an emerging strain of literature, motivated by the dramatic increase in the information

available to investors, focuses on the role of information and information production in

explaining stock market comovement as in Brockman, Liebenberg, and Schutte (2010)

and Veldkamp (2006a). The increase in the amount of news is driven in part by the

technologies used to produce and transmit news. The 2008–2009 financial crisis and the

more recent crisis in the euro zone highlight the importance of timely news in the pricing

and the comovement of asset prices. And while the exact transformation of information

into prices is still not fully understood, it is clear that news (asset-specific information)

plays an important role for aggregate asset price behavior.

The fixed costs associated with news production have fallen dramatically, along

with the costs associated with distributing the information to investors. This has led to,

combined with other factors, more efficient prices and decreased comovement in the U.S.

stock market as reported by Veldkamp and Wolfers (2007).

The Journal of Financial Research Vol. XXXVII, No. 4 Pages 519–542 Winter 2014

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Rubin and Rubin (2010) report that investors have also been able to reduce the

costs associated with turning information on assets into trading decisions. Previous

studies such as Durnev et al. (2003) and Durnev, Morck, and Yeung (2004) or, more

recently, Bartram, Brown, and Stulz (2012) that examine the relation between asset-

specific information and stock return comovement have generated conflicting empirical

results. These studies have focused on the time-series relation between information

proxies and stock market comovement. We look at a more direct measure of information,

news, and relate this to stock market comovement.

In this article we examine the impact of news and its comovement on country-

level stock market comovement. As in Brockman, Liebenberg, and Schutte (2010), we

use the Campbell et al. (2001) measure of stock market comovement. We calculate an

analogous measure of news comovement similar in design to the volatility decomposition

presented in Campbell et al. More precisely, we introduce a measure of news comovement

and study how news comovement drives stock return comovement. Our study uses data

from 23 countries covering over 20 different industries from 2005 to 2009. We use a new

and unique database of news distributed over the Thomson Reuters newswire service as

our news measure. The database is important in that it allows us to directly measure the

flow of information rather than resort to proxies of information. This data set includes the

content of news messages, company codes, relevance, and the sentiment of news.

Relevance denotes a stock-specific score representing the importance of the message

content for the affected company. According to Mitra and Mitra (2011), the relevance

measure is defined as the number of occurrences of the particular company in the news

item relative to the appearance of all other companies mentioned in the very same item.

Our contribution is two-fold. First we show that news comoves. In fact, our

measure of news comovement is quite high at 78%. This suggests that news stories about

firms in specific industries or specific countries cluster in time, meaning that we rarely

observe a single story about one firm in an industry; rather, we observe multiple stories

about multiple firms. We also find that news comovement is a significant determinant of

stock market comovement. Between 9% and 13% of monthly stock market comovement

can be explained by news comovement. Both of these findings are novel. No previous

studies have shown that news comoves nor have they established a link between this news

comovement and stock market comovement. Finally, we show that the explanatory power

of news comovement is higher in countries with less well-developed financial markets.

II. Literature and Hypothesis Development

Motivated by the capital asset pricing model, comovement has traditionally been

measured by the covariance. Campbell et al. (2001) find that the observed covariance has

generally declined over past decades. Bartram, Brown, and Stulz (2012) focus on

explaining higher volatility in U.S. stocks compared to comparable international stocks.

They find that the higher volatility can be explained by more good volatility, where good

is defined as being “related to better growth opportunities for firms and better ability to

take advantage of these opportunities”(p. 1329). Durnev et al. (2003) look at the relation

between firm-specific volatility and the informativeness of prices. They show that firms

520 The Journal of Financial Research