The Impact of Information Disclosure Consistency on IPO Pricing Efficiency: Evidence from China’s A-share Market

Ruyi Shen

doi:10.6981/FEM.202610_7(10).0017

Authors

Ruyi Shen School of Public Finance and Taxation, Guangdong University of Finance and Economics, Guangzhou, Guangdong, China

DOI:

https://doi.org/10.6981/FEM.202610_7(10).0017

Keywords:

IPO Underpricing; Information Disclosure Consistency; Textual Analysis; TF-IDF Algorithm; Investor Heterogeneous Beliefs.

Abstract

The core of the comprehensive registration-based IPO reform is information disclosure. However, traditional single-period static textual analysis is limited in identifying ex ante over-packaging and strategic disclosure by IPO firms driven by financing incentives. Using IPO firms listed on China’s A-share registration-based boards from 2019 to 2025 as the sample, this study applies the TF-IDF algorithm and cosine similarity model in natural language processing to quantify intertemporal textual consistency between prospectuses and the first annual reports after listing, and empirically examines its effect on IPO underpricing. The results show a significant negative association between information disclosure consistency and IPO underpricing: the lower the ex post observed textual consistency, the higher the underpricing compensation required by investors. This conclusion remains robust after employing an instrumental-variable approach to alleviate endogeneity concerns. Further tests indicate that, after additionally controlling for secondary-market sentiment noise measured by post-listing first-month turnover and information-environment factors proxied by analyst coverage, the coefficient on information disclosure consistency remains significantly negative. This finding suggests that intertemporal textual consistency has independent pricing value in restraining IPO underpricing and does not merely reflect short-term secondary-market noise. Further analysis reveals a substitution effect between internal corporate governance and information disclosure consistency in reducing IPO underpricing, and this effect is more pronounced in market segments with higher information asymmetry. The study provides quantitative evidence and policy implications for regulators to introduce regulatory technology for penetrating textual scanning, for IPO firms to maintain long-term honest disclosure, and for investors to avoid pricing risks.

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