Latest Projects

Listening in on investors' thoughts and conversations

Journal of Financial Economics 145(2) 426-444. 2022.

Authors: Hailiang Chen and Byoung-Hyoun Hwang

Abstract: A large literature in neuroscience and social psychology shows that humans are wired to be meticulous about how they are perceived by others. We propose that impression-management considerations also end up guiding the content that investors transmit via word-of-mouth. We analyze server-log data from one of the biggest investment-related websites in the United States, as well as experimental data. Consistent with our proposition, we find that investors more frequently share articles that are more suitable for impression management, even when such articles less accurately predict returns. Additional analyses suggest that high levels of sharing can lead to overpricing.


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Fake News, Investor Attention, and Market Reaction

Information Systems Research 32(1) 35-52. 2021.

Authors: Jonathan Clarke, Hailiang Chen, Ding Du, and Yu Jeffrey Hu

Abstract: Does fake news in financial markets attract more investor attention and have a significant impact on stock prices? We use the SEC crackdown of stock promotion schemes in April 2017 to examine investor attention and the stock price reaction to fake news articles. Using data from Seeking Alpha, we find that fake news stories generate significantly more attention than a control sample of legitimate articles. We find no evidence that article commenters can detect fake news. Seeking Alpha editors have only modest ability to detect fake news. The broader stock market appears to price fake news correctly. The stock price reaction to the release of fake news is not significantly different than a matched control sample over short and longer-term windows. We conclude by presenting a machine learning algorithm that is successful in identifying fake news articles.


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Signal or Noise in Social Media Discussions: The Role of Network Cohesion in Predicting the Bitcoin Market

Journal of Management Information Systems 37(4) 933-956. 2020.

Authors: Peng Xie, Hailiang Chen, and Yu Jeffrey Hu

Abstract: Prior studies have shown that social media discussions can be helpful in predicting price movements in financial markets. With the increasingly large amount of social media data, how to effectively distinguish value-relevant information from noise remains an important question. We study this question by investigating the role of network cohesion in the relationship between social media sentiment and price changes in the Bitcoin market. As network cohesion is associated with information correlation within the discussion network, we hypothesize that less cohesive social media discussion networks are better at predicting the next-day returns than more cohesive networks. Both regression analyses and trading simulations based on data collected from confirm our hypothesis. Our findings enrich the literature on the role of social media in financial markets and provide actionable insights for investors to trade based on social media signals.


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Look Before You Leap: Stock Market Valuation of Mobile App Investments

Authors: Ziqing Yuan, Hailiang Chen, and Choon Ling Sia

Abstract: With the continuous growth of the mobile market, many firms are considering investing in mobile apps. Prior research and anecdotal evidence have shown that the success of a mobile app is associated with positive changes in user behavior. However, it is unclear whether the performance implications of mobile app investment can be generalized to a wide range of firms. To further our understanding of IT investments in the mobile domain, we utilized the event study methodology to analyze 761 US public firms that released their first mobile app between 2008 and 2017 on the two leading mobile app stores, Apple’s App Store and Google Play. Our results show that, on average, public firms experience a negative abnormal stock return on the day they release their first mobile app and that the value creation process of mobile app investment is highly contingent on a firm’s market position, IT capability, and industry competition. As the first empirical study to rigorously and systematically document the impact of IT investment in the mobile domain, our findings imply that firms should act cautiously when planning to enter the mobile app market.


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