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.

“How does a firm’s bankruptcy affect its regional environment?” is an open empirical question that has received little attention in the literature. We hypothesize that because enterprises provide funds to protect their regional environment, their default risk negatively impacts that environment. We analyze the impact of corporate default risk on environmental deterioration in the international setting to answer this question. Using a firm-level corporate default risk quarterly data from 2013q1 to 2020q4, we find that corporate default risk is positively associated with CO2 emissions and decomposed components. These findings are reliable in low-income and highly uncertain countries but weak in countries having more market competition. We also find that the negative impact of corporate default risk on the environment is more robust in countries with more population density and fewer forest area thresholds. Finally, using the instrumental variable approach, we provide preliminary evidence that firm-level political risk (for US and Canadian firms only) increases corporate default risk, leading to a degrading environment. Our findings are robust to alternative measurements of a firm’s default risk and environmental deterioration. Our research will help environmental authorities to consider corporate default risk as a determinant when formulating environmental-related strategies.

This paper, based on data from Chinese A-share listed companies between 2009 and 2019, employs the implementation of the "Shanghai-Hong Kong Stock Connect" as a landmark event of capital market liberalization, utilizing a difference-in-differences model to empirically examine the impact of market openness on firms' cross-region investment behavior and its underlying mechanisms. The findings indicate that: (1) the launch of the "Shanghai-Hong Kong Stock Connect" has significantly promoted the establishment of cross-provincial and cross-border subsidiaries by the companies involved; (2) capital market liberalization influences firms' cross-region investment through three dimensions: finance, governance, and stakeholders. In terms of finance, the openness alleviated financing constraints and improved stock liquidity; in governance, it pressured companies to adopt more digitalized and transparent governance structures to accommodate cross-regional expansion; in the stakeholder dimension, it attracted the attention of external investors, accelerating their understanding of firms and alleviating the trust issues associated with cross-region expansion. (3) The effect of capital market liberalization on promoting cross-border investments by private enterprises is particularly pronounced, and this effect is further strengthened as the quality of corporate information disclosure improves. Firms with higher levels of product diversification benefit more from market liberalization, accelerating their overseas expansion. (4) Capital market liberalization has elevated the level of cross-region investment, thereby significantly fostering innovation and improving investment efficiency. The conclusions of this study provide fresh empirical evidence for understanding the microeconomic effects of China's capital market liberalization, the intrinsic mechanisms of corporate cross-region investments, and their economic consequences.

In the digital era, the information value of online prices, characterized by weak price stickiness and high sensitivity to economic shocks, deserves more attention. This paper integrates the high-frequency online inflation rate into the dynamic Nelson-Siegel (DNS) model to explore its relationship with the term structure of interest rates. The empirical results show that the weekly online inflation can significantly predict the yield curve, particularly the slope factor, while the monthly official inflation is predicted by yield curve factors. The mechanism analyses indicate that, due to low price stickiness, online inflation is more responsive to short-term economic conditions and better reflects money market liquidity, thereby having predictive power for the yield curve. Specifically, online inflation for non-durable goods and on weekdays shows stronger predictive power for the slope factor. The heterogeneity in price stickiness across these categories explains the varying impacts on the yield curve.

This paper utilizes the COVID-19 pandemic as an exogenous shock to investor uncertainty and examines the effect of uncertainty on stock liquidity. Analyzing data from Chinese listed firms, we find that stock liquidity dries up significantly in response to an increase in uncertainty resulting from regional pandemic exposure. The underlying reason for the decline in stock liquidity during the pandemic is a combination of earnings and information uncertainty. Funding constraints, market panic, risk aversion, inattention rationales, and macroeconomics factors are considered in our study. Our findings corroborate the substantial impact of uncertainty on market efficiency, and also add to the discussions on the pandemic effect on financial markets.

Based on 31 provinces, municipalities, and autonomous regions in mainland China, this paper explores the temporal and spillover effects of the provincial COVID19 pandemic on stock returns. The results show that stock returns are significantly and negatively correlated both with the pandemic in the firm’s headquartered province (referred to as, local province), and the pandemics in other provinces (referred to as, non-local provinces). By multiple time dimensions analysis, we find that at the weekly (monthly) level, the impact of the pandemic in local province on stock returns is larger (weaker) than the pandemics in non-local provinces, showing the temporal (spillover) effects. Mechanism analysis shows that COVID-19 can quickly reduce investors’ attention to stock market. The heterogeneity analysis shows that firms owned by state, with bad CSR, or a higher proportion of shares held by the largest shareholder are more affected by COVID-19. After replacing samples and time intervals, the results remain robust.

The “Internet celebrity economy” is a business model aimed at capitalizing on online traffic based on the purchasing power of users on social media in which “influencers”—highly influential individuals—exercise their marketing power to create a fandom. China has witnessed an abrupt outbreak in its “Wanghong” (internet celebrity) economy since 2016, eventually leading to consecutive high closes for related stocks from around 2020. The empirical findings are as follows: First, investors’ attention to Wanghong stocks and cumulative abnormal returns (CARs) are significantly positively associated. However, operational results and CARs are weakly linked, implying that the economic impact of intense influencer marketing is short-lived, and abnormal returns constitute an anomaly. Second, the positive abnormal returns of Wanghong stocks last approximately six months, which overlaps with the boom period of the Wanghong index based on influencer news articles.

Although sentiment-driven investors are believed to play an important role in the Chinese stock market, there are very few sentiment measures at the individual stock level based on their trading activities. Due to the unique “T+1” trading rule in China, the low overnight return of stocks reflects intensified trading activities from short-term speculators. Therefore, we construct a sentiment measure for individual stocks based on the close-to-open return (CTO). We find that CTO positively predicts future stock returns in the cross-section, supporting the idea that low CTO, as an indicator of sentiment-driven excess demand, leads to lower subsequent returns. This finding is not driven by firm-specific news and alternative explanations based on risks, investor attention, or investor underreaction. Further analyses suggest that investors overpay for low-CTO stocks because of their inherent preference for this type of stock.

Digital transformation empowers enterprises with new kinetic energy for high-quality development, can digital transformation enhance the transparency of capital market? This study constructs a corporate digital transformation index, and examines its impact on Chinese capital market transparency from the perspective of information senders. We find that corporate digital transformation significantly improves transparency, and this finding is more pronounced in non-SOEs, firms with low political connection, high industry environment uncertainty, and low regional marketization level. Channel tests show that lowering management myopia and increasing analyst attention are possible mechanisms. Furthermore, digital transformation improves stock liquidity by enhancing enterprises’ information transparency. Overall, our findings provide critical insights for improving transparency in China’s capital market.

Empowered by comprehensive data on smartphone fund investors’ trading and browsing histories from a Chinese financial company, we explore the role of investors’ financial attention in influencing the relationship between unrealized profits and investors’ selling decisions. Against a backdrop in which retail investors are not attentive to their portfolio information, we find supportive evidence suggesting that investors exhibit realization preference when we condition on days when investors pay financial attention. Further, we show that failing to account for investors’ financial inattention may induce observers to reject the realization-preference hypothesis. This paper also offers insights into the determinants of financial attention and the influence of financial attention on investor disposition effect.