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.

We investigate the impact of severe snowfall induced operational disruptions on insider trading. Applying geospatial analytics to an extensive dataset of snow cover, we conduct granular analyses of snowstorms across firms at establishment level. When analyzing a sample of firms that operate in snowfall-impacted areas, we find that corporate insiders significantly adjust their trading behavior during these events. These insiders not only predict lower future returns but also increase the size of their sales in response to snowfall crises. Further, we explore the salience and operational insights channels through which snowfall triggers informed insider sales. Our findings show that insiders residing in impacted regions, as well as senior insiders with unique operational insights, effectively avoid losses during these periods. The snow intensity test reveals that these phenomena are more pronounced for snowstorms of greater severity. We also provide direct evidence that establishments under severe snow strikes experience lower total sales volumes. Our study highlights the capacity of insiders to anticipate and respond to weather-related business risks.

Since the global financial crisis of 2007–2009, preventing financial crises has become one of the most important objectives of regulators and banks. Although previous studies have identified the phenomenon of risk contagion in the banking system, the underlying mechanisms of risk contagion are still unclear. This study delves into the multi-stage contagion mechanism of liquidity risk based on interbank lending linkages and clearing rules and introduces a new index to quantify bank liquidity risk. We find that the contagion of liquidity risk is primarily determined by the network structure of risk exposures between banks in default and is not significantly influenced by the lending relationships of banks that remain solvent. The empirical results suggest that banks with high risk should be prioritized for cash injections to improve system liquidity. These findings offer new insights into financial risk contagion and practical recommendations for regulatory authorities formulating intervention strategies and for banks conducting risk management.

This paper represents the first attempt to show how heterogeneous shock experiences help explain the enduring scars on household future behaviors. Using a large-scale household survey with 15,652 observations combined with geospatial transportation big data, we identify a novel belief-updating mechanism through which crises may exert prolonged impacts on household asset allocation and consumption patterns. An increase in the duration of previous lockdown experience is associated with a 10.52% escalation in enhanced anxiety for future precautionary saving motivations. This experience-based learning perspective supports the resolution of long-lasting overreactions to negative shocks via belief revisions and extends to households’ consumption behaviors. The lingering effects continue to skew households' beliefs even when conditions improve. Additionally, households with different individual-based shock experiences may exhibit varying perceptions of external shocks, resulting in disparate belief revision processes.

This paper investigates the impact of two global crises, the global financial crisis and the COVID-19 crisis, on herding behavior in the Chinese and U.S. stock markets. We find no evidence of herding behavior during these two global crises in the U.S. stock market, yet significant herding emerges under the COVID-19 crisis in Chinese mainland stock market. Additionally, the observed herding behavior in mainland China is primarily driven by sentiment. Our results reveal and explain the differences in the effects of financial crisis and public health crisis on herding behavior, as well as variations between emerging and developed stock markets.

Fintech firms mobilize information technology to provide intermediation services using a broker methodology, whereas dealer banks intermediate using leveraged balance sheets. The integration of Fintech into banking may reduce the unit cost of intermediation by shifting the production function from dealer to broker. A “Fintech score” is derived using nonlinear and machine learning algorithms that show on-balance sheet lending for low Fintech score dealer banks versus securitization, brokered deposits, and non-interest income for high score, broker banks. Using Data Envelopment and Stochastic Cost Frontier Analyses, we find that banks with higher Fintech scores are more operationally efficient and resilient in crises.

This paper studies the trading behavior of investors facing a large number of firm-initiated stock trading suspension events during the Chinese stock market crisis in July of 2015. Using account-level trading data from the Shanghai Stock Exchange, we find that investors with a higher fraction of holding value in suspension sell less (or purchase more) of non-suspended stocks. Consequently, non-suspended stocks whose shareholders having high average account- level suspension fraction experience a relative price appreciation, which subsequently reverses. These evidences indicate that trading suspension can calm down investors and therefore helps to stabilize the volatile market in crisis time.

Since September 1, 2014, the renminbi (RMB) offshore market in Taiwan has been started on according a cross-strait MOU. A completed RMB market in the Chinese Economic Area therefore has been established. Due to political and economic disruptions, such as the aftermath of the global tsunami, mainland China’s stock market crash and RMB exchange rate reform in 2015, as well as failure of the Service Trade Agreement between Taiwan and mainland China in 2016, the arbitrage opportunities among the three RMB markets can be explored. This paper evaluates the convergence and divergence of RMB market returns by the sigma-convergence (or log t) test, which provides a more precise indication for market return convergence than does the traditional unit root test. Policy implications for the RMB arbitrage are also provided.

This paper studies the trading behavior of investors facing a large number of firm-initiated stock trading suspension events during the Chinese stock market crisis in July of 2015. Using account-level trading data from the Shanghai Stock Exchange, we find that investors with a higher fraction of holding value in suspension sell less (or purchase more) of non-suspended stocks. Consequently, non-suspended stocks whose shareholders having high average account level suspension fraction experience a relative price appreciation, which subsequently reverses. These evidences indicate that trading suspension can calm down investors and therefore helps to stabilize the volatile market in crisis time.

This paper applies a variety of short‐run and long‐run time series techniques to data on a broad group of Asia‐Pacific stock markets and the United States extending to 2010. Our empirical work confirms the importance of crises in affecting the persistence of equity returns in the Asia‐Pacific region and offers some support for contagion effects. Post‐Asian financial crisis quantile regressions yield substantial evidence of long‐run linkages between the Shanghai market, the US market and many regional exchanges. Cointegration is particularly prevalent at the higher end of the distribution. Our results suggest that the enormous growth of the Shanghai market in the new millennium has been accompanied by a meaningful level of integration with other regional and world markets in spite of ongoing capital controls.