The game of lies by stock investors in social media: a study based on city lockdowns in China

Author:

Liu Qing,Son Hosung,Lee Woon-SeekORCID

Abstract

AbstractThe potential hypotheses for finance research based on social media sentiment revolve around the reliability of investor sentiment expressed on social media and the causal relationship between financial markets and this sentiment. The central hypothesis we focus on is derived from the "lie game" played by investors on social media. This study is the first to explore three states of this lie game in the context of the Chinese stock market: the "equilibrium state", the "confusion state", and the "subversion state". Our findings indicate that the "equilibrium" state is the typical state of the lie game, where increased investor sentiment results in more positive market behavior, and higher stock prices lead to increased investor sentiment. We also examine the effect of significant social events, such as the "lockdown in Wuhan" and the "lockdown in Shanghai", on the lie game's outcome. The successful lockdown in Wuhan and the public's opposition to the politicization of COVID-19 reinforced the "equilibrium" state of the game. However, the Shanghai lockdown's failure to promptly halt the spread of COVID-19 led to the intertwining of the economy and COVID-19 in public discourse, shifting the lie game's outcome from an "equilibrium state" to a "subversive state". We emphasize that the "confusion state" and "subversion state" outcomes of the lie game are concerning, and managing public opinion and the externalization of domestic conflicts can help reduce this risk. This study offers a fresh perspective on the traditional issues of investor sentiment reliability and the causal relationship between investor sentiment and stock markets.

Publisher

Springer Science and Business Media LLC

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Methods for aggregating investor sentiment from social media;Humanities and Social Sciences Communications;2024-07-17

2. Data selection and collection for constructing investor sentiment from social media;Humanities and Social Sciences Communications;2024-06-19

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