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Social Media

Wisdom of crowds: peer opinions and value discovery: empirical evidence from social media

JIN Dehuan;LI Yan

Business Management Journal,Vol 39,No. 12

【Abstract】 As an important medium for information transmission, social media has a significant impact on stock market pricing and stock price fluctuation. Adopting the methods of machine learning and textual analysis to classify the opinions reflected by the posts published in guba.eastmoney.com, we examined the role of value discovery of social media from the perspective of peer opinions. We came up with the following empirical results. (1) There is a positive correlation between peer opinions and future stock returns, indicating that peer opinions contain investment value. This finding refuses the hypothesis that peer opinions lack information content. (2) Peer opinions have the effect of follow. In other words, the more comments a post attracts, the greater the impact peer opinions exert on future stock returns. Further, we find that, compared with positive information, the negative information of peer opinions are the main cause affecting future stock returns. In addition, peer opinions can also significantly account for earnings surprises, indicating that investors’ opinions have characteristics of wisdom of crowds favorable for value discovery and investment practice. The research conclusions have important theoretical and practical values for understanding the relationship between social media and capital markets and how to effectively improve the pricing of capital markets.

Research on credit risk mitigation mechanisms of peer-to-peer lending based on social network

YANG Li;ZHAO Cuicui;CHEN Xiaohong

Chinese Journal of Management Science,Vol 26,No. 01

【Abstract】 Risk management is the core issue to determine the sustainable and healthy development of financial innovation. Based on the information economics and game theory, an information asymmetry mathematical model was set up to analyze the acting mechanism and working conditions of the social network in mitigating P2P lending’s credit risk. It was proved that with the introduction of social network, the credit risk of P2P lending can be mitigated by three mechanisms of the social network, which are ex-ante information acquisition mechanism, joint liability mechanism, and ex-post default constraint mechanism. Those constitute unique credit risk mitigation mechanisms of social network, which can effectively relieve adverse selection caused by the imperfection of credit system as well as moral hazards caused by the lack of effective monitoring mechanism and the lack of default constraint mechanism in P2P lending market. Joint liability, dynamic incentive, the level of supervision, sanctions, constraints of default and the mining of social information are the determining factors for the risk mitigation level of social network. The theoretical frameworks were first proposed for credit risk mitigation of social network in P2P lending, including the developed social network theory and credit risk management theory, which provides new scientific evidence and theoretical support for risk control trial with social network in P2P platform. Great theoretical importance was provided to understand and grasp risk mitigation mechanisms of social network, as well as to use social network credit risk management.

Social media, investor sophistication and earning expectation: evidence from SSE e-interaction

DING Hui;LYU Changjiang;HUANG Haijie

Economic Research Journal,Vol 53,No. 01

【Abstract】 Investor sophistication is defined as how smart investors can be in the process of information acquisition and interpretation (Tan et al., 2014; Kalay, 2015). Information technology is changing the process of investors’ information acquisition and interpretation and thus can change the corresponding smartness of the investors. Therefore, research on how market efficiency is influenced by the change in investor sophistication due to information technology is considerably important for academia and policy. “SSE E-Interaction,” a Chinese security-themed social media platform operated and regulated by the Shanghai Stock Exchange (SSE), is aimed at facilitating the process of investors’ information acquisition and interpretation by allowing online interaction between investors and the listed firms. This online interaction is organized such that investors ask the listed firms questions and the SSE asks the listed firms to answer these questions according to their disclosed information. According to the SSE requests, a listed firm has the obligation to answer the questions from investors on the SSE E-Interaction, and the answers of the listed firms should not contain any private information or false information. Here, we studied how the accuracy of the market earnings expectation is influenced by the change in investor sophistication due to information technology. Two competing theories may be related to the market consequence of investor sophistication. The market efficiency hypothesis (Fama, 1998) argues that market prices fully reflect all publicly available information. Conditional on this hypothesis, the improvement of investor sophistication makes no difference to market efficiency. In contrast, the incomplete revelation hypothesis (Bloomfield, 2002) asserts that statistics that are more costly to extract from public data are less completely revealed in market prices. Conditional on this hypothesis, the improvement of investor sophistication can speed up the incorporation of information into prices. In this study, we found that when there were more words in the listed firms’ answers on “SSE E-Interaction,” the market earnings expectation was more accurate, and the effect was more pronounced when the institutional ownership was lower. We also found that when there were more words in the listed firms’ answers on “SSE E-Interaction,” the information asymmetry was lower during the earnings announcements. Our findings suggest that the market efficiency can be improved by the investor sophistication improvement due to information technology. Our findings are robust to different measurements of the interactions of the listed firms, different earnings expectation models, and different measurements of information asymmetry during the earnings announcements. One endogenous problem of this study lies in the incentive issues of the listed firms’ interactions. The market efficiency may be improved by the incentive issues of the listed firms’ interactions rather than by the interactions themselves. To solve this endogenous problem, we provide evidence that disclosure quality has no correlation with the listed firms’ online answers. The problem of endogeneity is a limitation of this study, as we did not filter out other potential incentive issues related to the listed firms’ answers. This study mainly makes the following contributions. First, our study shed light on the potential limitation of the efficient market hypothesis with the empirical evidence that the market efficiency could be improved by the improvement of investor sophistication due to information technology. Second, in our study of investor sophistication, we used the online interaction of social media as a proxy for investor sophistication improvement due to information technology, which provided more details of the information acquisition and interpretation process than the traditional proxy of institutional ownership. Third, by illustrating how information technology has changed the information environment of the capital market, we provided empirical evidence that information technology can facilitate the information acquisition and interpretation of investors through online interactions.

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