Publications

Abstract: This study leverages Large Language Models to extract stock expectation beliefs from millions of posts by 60,000+ financial influencers on Xueqiu, and employs finite mixture models with EM algorithm to filter out "luck noise" and scientifically measure actual investment abilities. Results show only 46.63% of influencers possess positive investment ability, with merely 2.22% achieving strong weekly returns of 1.25%. A long-short portfolio following top 10% influencers yields 22.4 bps daily returns and 4.94x cumulative returns from 2016-2025. Retail investors struggle to identify skilled influencers, while institutional investors respond more to high-ability KOLs. The methodology provides regulators and platforms with tools to identify and monitor financial social media content.

Abstract: This paper investigates the stock price spillover effects arising from corporate network ties on the Chinese social media platform "Xueqiu". By constructing a comprehensive dataset of corporate relationships and stock price movements, we analyze how information and sentiment propagate through social networks and impact stock valuations. Our findings reveal significant spillover effects where connected firms experience correlated price movements, particularly during periods of high market volatility. We identify key mechanisms through which social media amplifies these effects, including information cascades, herding behavior, and investor attention. The results provide important insights into the role of social media in modern financial markets and have implications for portfolio management, risk assessment, and regulatory policy.

Abstract: A large body of literature has examined whether posts on social media propagate noise or information. In this paper, we propose that both coexist on Chinese social media platforms but can be distinguished by posters' trading behavior. Individuals may post articles on social media that do not reflect their true opinions, often for impression management purposes, resulting in inconsistency between their words and subsequent actions. Additionally, observing a poster's trading behavior prior to posting can help assess the reliability of their expressed views.