News-Induced Dynamic Networks for Market Signaling: Understanding the Impact of News on Firm Equity Value

Kun Chen (), Xin Li (), Peng Luo () and J. Leon Zhao ()
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Kun Chen: Department of Information Systems and Management Engineering, Southern University of Science and Technology, Shenzhen 518055, China
Xin Li: Department of Information Systems, College of Business, City University of Hong Kong, Hong Kong
Peng Luo: School of Business, Sichuan University, Chengdu 610065, China
J. Leon Zhao: School of Management and Economics, Chinese University of Hong Kong, Shenzhen 518172, China

Information Systems Research, 2021, vol. 32, issue 2, 356-377

Abstract: Firm relations, which inform the competitive environments of firms, are critical to firm operations and are often factored into investor decisions. Previous studies and practices have considered relatively stable and long-term business relations as an indicator of firm market value. Public news often reports on business relations, especially dynamic and short-term opportunities and challenges involving different partners. Learning about firm relations from news is commonly done by human investors but has not been studied systematically in previous research, leading to a research opportunity in market signaling via dynamic firm relations . In this study, we propose a new approach to market signaling by leveraging text-mining methods to extract cobenefit/counter-benefit networks based on firms’ mutual or conflicting interests in business events. We find that the resulting networks in the long term are partially aligned with firm cooperation and competition relationships, confirming their semantic implications for investor perception and attention. Our empirical study further shows that dynamic networks formed in a short time period (measured by firm centrality in networks) have significant impacts on firm equity value, after controlling for market activities and other information from news, such as volume, sentiment, and comentions. We show that dynamic networks can provide additional value in predicting firm equity value over stable networks. Moreover, the negative effects of counter-benefit networks emerge rapidly and persist longer than the positive effects of cobenefit networks. This study provides new insights into investor perception of news and suggests new research directions for financial text mining. Our research findings on market signaling via news-induced networks also have an impact on financial practices, such as market analysis and automatic trading.

Keywords: dynamic network; financial text mining; competitive environment; investor attention; firm equity value (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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