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| Interactive Information Disclosure and Issuer Credit Ratings: Evidence from Stock Exchange Interactive Platforms |
| SUN Jie, LI Nengfei, ZHAO Mengru
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School of Accounting, Tianjin University of Finance and Economics;
School of Economics and Management, Xianyang Normal University |
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Abstract Against the backdrop of the current rapid development of the capital market, the quality of information disclosure is particularly critical to the quality development of companies. As a supplement to mandatory information disclosure, the interactive platforms of stock exchanges have become an important innovation in improving investor relations management through a two-way communication mechanism. On the interactive platform, instant Q&A between investors and companies can reflect not only the companies' response strategy to market dynamics, but also the level of voluntary disclosure by companies, which has become an important dimension in assessing the quality of information disclosure. Credit rating agencies (CRAs), as important information intermediaries in the capital market, rely on diversified information for their risk assessment. Therefore, the timeliness and unstructured feature of Q&A information on interactive platforms can be an effective reference for rating agencies. The rating system requires CRAs to combine quantitative information with qualitative analysis in an organic way, which further elevates the importance of non-standardized textual information in rating decisions. However, existing research focuses on the impact of financial indicators on rating outcomes, and the value of textual information disclosed via interactive platforms is still underexplored. Theoretically, the Q&A information of interactive platforms may significantly affect the level of corporate credit ratings through rating adjustment factors, but this path has not yet been empirically tested. Therefore, the purpose of this paper is to explore in depth the effect of interactive disclosure on corporate credit ratings and provide decision support for stakeholders.
To address the above issues, we select a research sample of Chinese A-share listed companies in Shanghai and Shenzhen from 2013 to 2023. We find, first, that the negative tone of interactive disclosure texts and strategic managerial responses significantly lowers the level of issuer credit ratings, and this effect is more pronounced for rating agencies with higher reputations and foreign backgrounds. Second, the negative tone of interactive disclosure texts lowers issuer credit ratings by intensifying corporate financing constraints and increasing debt agency costs, and the strategic response lowers issuer credit ratings by increasing information asymmetry and decreasing stock liquidity. Third, the downgrade in issuer credit ratings caused by the negative tone of interactive disclosure texts and strategic responses may further reduce the amount of trade credit financing available to firms and increase the cost of bond issuance.
The marginal contributions of this paper are mainly as follows: First, it enriches the research boundaries related to the economic consequences of interactive disclosure. Contrary to existing studies, the complex relationship between interactive disclosure and issuer credit ratings is explored in depth from the perspective of the textual features of interactive disclosure, further expanding the research boundaries on the economic consequences of interactive disclosure. Second, it enriches research on the factors influencing credit ratings. By using natural language processing (NLP) technology to construct textual indicators, the effective value of textual information of interactive disclosure on credit ratings is systematically presented. Third, from the perspective of debt financing, the economic impact of interactive disclosure on trade credit financing and bond issuance costs is examined through the financing intermediary role of credit ratings, further enriching research in this area. Fourth, by analyzing the mechanisms, heterogeneity and economic consequences of the textual features of interactive disclosure on issuer credit ratings, we not only deepen the theoretical understanding of the qualitative features of interactive disclosure and the determinants of credit ratings, but also provide useful policy insights for improving the construction of interactive platforms on stock exchanges to support better rating decisions by CRAs.
The policy implications of this paper are as follows: from the corporate level, firms should establish a complete interactive information processing management system. First, companies can implement a categorical response mechanism, use NLP technology to identify high-frequency questions, and require the secretary of the board of directors to conduct a second-level verification and source annotation for important responses. Second, companies can develop an impact analysis system for information disclosure, and anticipate the impact of responses on issuer credit ratings and debt financing so as to avoid avoiding the truth. At the rating agency level, CARs should use sentiment analysis models to quantify the proportion of negative tone and capture changes in management attitudes. They can use semantic association mapping techniques to identify response strategies and incorporate the analysis into credit rating models. At the investor level, investors should explore the textual features of interactive information from multiple perspectives, quantify the proportion of both negative tone and the degree of strategic intent, and comprehensively assess the development prospects of companies. At the regulatory level, regulators should optimize the operating mechanism of the exchanges' interactive platform. First, regulators can establish a categorized review and quality assessment system that requires substantive responses and reduces ambiguity, with regular quality spot checks by the exchange. Second, regulators can jointly develop automated monitoring tools to capture and assess risk signals in real time and incorporate them into credit file management.
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Received: 21 June 2024
Published: 05 April 2025
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