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香港城市大学李昕副教授讲座通知

发布时间: 2021/05/14 08:50:21     点击次数:次   打印本页

北航经管学院“至信论坛”系列讲座

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

讲座时间:2021.5.19(周三)14:00-16:30

腾讯会议:884 414 194

讲座嘉宾:李昕 副教授

讲座嘉宾 简介

Xin Li

Xin is an Associate Professor in the Department of Information Systems at City University of Hong Kong.

He has 100+ publications, including 50+ journal papers, which are on MISQ, ISR, JMIS, INFORMS JOC, DSS, I&M, JASIST, IJEC, IEEE/ACM Transactions, Nature Nanotechnology, Bioinformatics, among others. Please referr to his personal website (http://www.is.cityu.edu.hk/staff/xin.li/) for details.

He has received about 20 external and internal grants as PI and Co-I.

He is a senior member of IEEE, and ACM, and a member of INFORMS and AIS.

Kun Chen

Dr.KunChen is an associate professor in the Department of Information Systems and Management Engineering at Southern University of Science and Technology. Her research focuses on social media analytics, fintech and data science. She has published papers in Information Systems Research, INFORMS Journal on Computing, Journal of Management Information Systems, etc.Before joining in SUSTech, she worked in some world-famous financial institutions, i.e., Australian Capital MarketsCooperativeResearch Center (CMCRC), Securities and Futures Commission of Hong Kong, and Shenzhen Stock Exchange.

讲座概要

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 co-benefit/counter-benefit networks based on firms’ mutual or conflicting interests in business events. We find that the resulting net-works 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 co-mentions. 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 co-benefit 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.