There is substantial evidence indicating that enterprises are negatively impacted by climate risk, with the most direct effects typically occurring in financial domains. This study examines A-share listed companies from 2007 to 2023, employing text analysis to develop the firm-level climate risk indicator and investigate the influence on corporate financial risk. The results show a significant positive correlation between climate risk and financial risk at the firm level. Mechanism analysis shows that the negative impact of climate risk on corporate financial condition is mainly achieved through three paths: increasing financial constraints, reducing inventory reserves, and increasing the degree of maturity mismatch. To address potential endogeneity, this study applies instrumental variable tests, propensity score matching, and a quasi-natural experiment based on the Paris Agreement. Additional tests indicate that reducing the degree of information asymmetry and improving corporate ESG performance can alleviate the negative impact of climate risk on corporate financial conditions. This relationship is more pronounced in high-carbon emission industries. In conclusion, this research deepens the understanding of the link between climate risk and corporate financial risk, providing a new micro perspective for risk management, proactive governance transformation, and the mitigation of financial challenges faced by enterprises.

This paper investigates the outcomes of ambiguous online interaction between firms and investors. Using question-answer text data from two online investor interactive platforms (IIPs) in China, we show that firms that give less relevant answers to investors’ questions tend to have larger analyst forecast bias and higher analyst optimism. Though the targeted users of the interactive platforms are individual investors, the interaction quality influences analysts’ forecasts. Meanwhile, the effect of question dodging is stronger when questions are related with earnings and disclosure, when firms have higher earnings uncertainty and lower media coverage, but weaker when analysts visit the firm or rely less on public information. Further analysis shows that irrelevant answers increase the market demand for analyst forecasts, deteriorate firms’ information environment, and lead to larger forecast dispersion, lower stock liquidity, and weaker earnings responses of the market. Moreover, we find that other market participants related with analysts are also aware of firms’ question dodging by reducing holdings and site visits. Our findings provide evidence that question dodging in firm-investor interaction exacerbates information asymmetry and unintendedly influences analysts’ forecast behaviors.

We develop novel high-frequency indices that measure climate attention, covering a wide range of both developed and emerging economies. This is achieved by analyzing the text of over 23 million tweets published by leading national newspapers on Twitter during the period from 2014 to 2022. Our findings reveal that a country experiencing more severe climate news shocks tends to see both an inflow of capital and an appreciation of its currency. In addition, brown stocks in highly exposed countries experience large and persistent negative returns after a global climate news shock. These outcomes align with the predictions of a risk-sharing model in which investors price climate news shocks and trade consumption and investment goods in global markets

The impact of corporate environment, society, and governance (ESG) disclosure on the online market remains uncertain. To address this ambiguity, this study utilizes text analysis to thematically classify research samples to examine the positive influence of corporate ESG disclosure on stock liquidity from a reputational perspective. Interestingly, the reputational effect of ESG disclosure shows asymmetry within the online market, particularly in its highly information-sensitive environment. Notably, negative media reputation insignificantly diminishes the positive impact of ESG disclosure on stock liquidity. A series of robustness tests confirm the reliability of the sample screening method and findings.