Developing an early warning model for company financial crises holds critical significance in robust risk management and ensuring the enduring stability of the capital market. Although the existing research has achieved rich results, the disadvantages of insufficient text information mining and poor model performance still exist. To alleviate the problem of insufficient text information mining, we collect related financial and annual report data from 820 listed companies in mainland China from 2018 to 2023 by using sophisticated web crawlers and advanced text sentiment analysis technologies and using missing value interpolation, standardization, and data balancing to build multi-source datasets of companies. Ranking the feature importance of multi-source data promotes understanding the formation of financial crises for companies. In the meantime, a novel Attention-based Fuzzy Neural Network (AFNN) was proposed to parse multi-source data to forecast financial crises among listed companies. Experimental results indicate that AFNN exhibits significantly improved performance compared to other advanced methods.

Corporate misconduct poses significant risks to financial markets, undermining investor confidence and economic stability. This study investigates the influence of World Heritage culture, with its social, historical, and symbolic values, on reducing corporate misconduct. Using firm-level data from China, with its rich cultural heritage and ancient civilization, we find a significant negative association between the number of World Heritage sites near a company and corporate misconduct. This suggests that a richer World Heritage culture fosters an informal institutional environment that mitigates corporate misconduct. This effect is robust across 100 km, 200 km, and 300 km thresholds and remains significant when using a binary misconduct indicator. The results also show that World Heritage culture enhances corporate social responsibility (CSR) and social capital, which in turn reduces corporate misconduct. Additionally, the impact of World Heritage culture is more pronounced in firms located in high social trust areas, those with high institutional investor supervision, and those farther from regulatory authorities. These findings advance academic knowledge and offer practical implications for policymakers and investors.

Corporate site visits provide investors with opportunities to obtain non-standard, tailored "soft" information about the firm. In this study, we investigate the impact of information disclosed from corporate site visits on stock market stability from the perspective of stock return volatility. Our findings suggest that it is the information disclosed rather than the visits themselves that significantly reduce stock return volatility, primarily by mitigating information asymmetry. Moreover, we observe that the volatility-mitigating effect of site visits is more pronounced when the visit information better aligns with investors' concerns and when it is more effectively disseminated. Our study contributes to the literature by demonstrating that the timely disclosure of site visit details serves as a stabilizing mechanism for stock prices through effective information mining and dissemination.

Compared to previous literature on external FinTech, this paper is more interested in the role played by bank FinTech. Based on panel data from Chinese commercial banks spanning 2010 to 2021, this paper investigates the impact of digital transformation on bank soundness and its potential mechanisms. The empirical findings demonstrate a positive association between digital transformation and bank soundness, driven primarily by strategic and management digitization. Mechanistic analysis indicates that digital transformation improves bank soundness by mitigating risk-taking behavior and promoting diversification. The positive effect of digital transformation is more pronounced in state-owned and joint-stock banks, banks with higher liquidity mismatch as well as in sub-samples with greater levels in external FinTech development and economic policies uncertainty. Additional analysis suggests that digital transformation can still enhance bank soundness even in the presence of relatively easy monetary and macroprudential policies, highlighting the harmonization and complementarity between internal innovation from digital transformation and external regulatory policies in maintaining banking stability. Overall, this paper contributes to the literature on bank FinTech, factors influencing bank stability. And it also provides a novel explanation for the relationship between financial innovation and financial stability.

With China being a large developing economy, the trading in China’s stock market is dominated by retail investors, and its government actively participates in this market. These features are quite different from those of typical developed markets, and This review focuses on two important questions: how do retail and institutional investors trade in China and why? We have three main findings after reviewing 100+ previous studies. First, small retail investors have low financial literacy, exhibit behavioral biases, and not surprisingly, negatively predict future returns; whereas large retail investors and institutions are capable of process information, and they positively predict future returns. Second, the macro- and firm-level information environment in China is slowly but gradually improving. Finally, the Chinese government actively adjusts their regulations of the stock market to serve the dual goals of growth and stability, with many of them being effective, while some may not generate intended consequences.

This study investigates how digital transformation can affect ESG performance within China’s unique environment. Using data from Chinese A-share listed firms from 2009 to 2022, this paper reveals digital transformation can positively affect ESG performance. Within the mechanism, customer concentration plays a medicating effect and organizational structure stability plays a positive moderating effect. Besides, the effect of digital transformation on ESG performance is more pronounced in Chinese western enterprises, non-heavy polluting industries and large-size enterprises. To our knowledge, this paper is one of the pioneering studies that examines the relationship between digital transformation and ESG performance from the perspective of supply chain management.

As China’s shadow banking sector expands, the impact of listed companies’ involvement in financial stability and the real economy accumulates increasing attention. Despite being a crucial channel for non-financial firms to participate in shadow banking, the literature has given limited consideration to the acquisition of wealth management products (WMPs). Using data from Chinese listed firms between 2007 and 2020, we analyze how excessive equity financing affects companies’ WMP acquisitions. Our findings indicate that over-financing significantly boosts WMP purchases among these firms, particularly in cases of private ownership, raised environmental uncertainty, and strict financing constraints.

Climate change shocks pose a threat to the stability of the financial system. This study examines the influence of climate risks on systemic risk in the Chinese market by utilizing extreme risk spillover network. Moreover, we construct climate risk indices for physical risks (abnormal temperature), and transition risks (Climate Policy Uncertainty). We demonstrate a significant increase in systemic risk due to climate risks, which can be attributed, in part, to investor sentiment. Furthermore, institutional investors can mitigate the adverse impact of climate risks. Our findings suggest that policymakers and investors need to exercise greater vigilance in addressing climaterelated adverse effects.

This paper presents an innovative Comprehensive Growth Dynamic Model (CGDM). CGDM is designed to simulate the temporal evolution of an event, incorporating economic and social factors. CGDM is a regression of logistic regression, power law regression, and Gaussian perturbation term. CGDM is comprised of logistic regression, power law regression, and Gaussian perturbation term. CGDM can effectively forecast the temporal evolution of an event, incorporating economic and social factors. The illicit trade in wildlife has a deleterious impact on the ecological environment. In this paper, we employ CGDM to forecast the trajectory of illegal wildlife trade from 2024 to 2034 in China. The mean square error is utilized as the loss function. The model illuminates the future trajectory of illegal wildlife trade, with a minimum point occurring in 2027 and a maximum point occurring in 2029. The stability of contemporary society can be inferred. CGDM's robust and generalizable nature is also evident.

Interest rate liberalization in China intensifies the exposure of commercial banks' interest rate risks and further increases the difficulty for commercial banks to effectively control interest rate risks, thus putting forward higher requirements for the normal operation and management of commercial banks. With the development of China's financial derivatives market, banking institutions begin to use basic interest rate derivatives to hedge interest rate risks. It is very important to give full play to the maturity transformation Function of commercial banks to enhance the ability of financial services to the real economy. Based on the semi annual unbalanced panel data of 37 listed banks in A-share stock markets from 2006 to 2020, this paper empirically tests the impact of the use of off balance sheet interest rate derivatives on the Maturity Transformation Function of banks in the case of interest rate fluctuations. The empirical results show that: (1) the use of interest rate derivatives helps to weaken the negative impact of interest rate fluctuations on the Maturity Transformation Function of banks. (2) The analysis of the mechanism shows that the use of interest rate derivatives improves the stability of the bank's asset side term structure and liability side term structure, so as to support the effective play of the bank's financial intermediary role. (3) Further analysis shows that the of interest rate derivatives significantly reduces the volatility of bank earnings. This study makes it clear that the use of interest rate derivatives has a positive impact on the commercial banks, which provides evidence for the further development of interest rate derivatives market in China.