This study investigates the source and motivation of professional inquiries on China’s Investor Interaction Platforms (IIPs). Given that IIPs do not require identity verification, professional inquiries may not originate exclusively from retail investors. The study empirically tests whether institutional investors are the primary contributors to these inquiries and examines whether their motivation reflects corporate governance oversight or information arbitrage behavior.
This study integrates large language models (LLMs) with supervised machine learning techniques to evaluate the professional level of investor inquiries on China’s Investor Interaction Platforms (IIPs). We construct a professional inquiry index and combine it with firm-level data to identify the source of professional inquiries. Empirical analyses, including instrumental variable and cross-sectional tests, are employed to examine whether institutional investors dominate these inquiries and to explore their underlying motivations.
This study finds that professional inquiries on IIPs may be predominantly initiated by institutional investors except for retail investors. Contrary to the governance oversight hypothesis, the results indicate that institutional investors use IIPs primarily for information arbitrage. They strategically post inquiries to attract market attention and drive stock price fluctuations, enabling short-term trading gains. When firms exhibit higher growth potential, stronger equity balance or greater total asset turnover ratio, institutional investors’ propensity for information arbitrage diminishes.
This study presents a novel application of large language models to evaluate the professional level of investor inquiries, advancing text analysis in accounting and finance research. It provides the first empirical evidence that professional inquiries on IIPs are predominantly posed by institutional investors, motivated by information arbitrage. This finding extends the principal agent theory by revealing intra-principal conflicts and offers broader implications for understanding institutional behavior and enhancing market transparency in emerging digital investor communication environments.
