Why is price momentum absent in China? Since momentum is commonly considered arising from investors’ under-reaction to fundamental news, we decompose monthly stock returns into news- and non-news-driven components and document a news day return continuation along with an offsetting non-news day reversal in China. The non-news day reversal is particularly strong for stocks with high retail ownership, relatively less recent positive news articles, and limits to arbitrage. Evidence on order imbalance suggests that stock returns overshoot on news days due to retail investors' excessive attention-driven buying demands, and mispricing gets corrected by institutional investors on subsequent non-news days. To avoid this tug-of-war in stock price, we use a signal that directly captures the recent news performance and re-document a momentum-like underreaction to fundamental news in China.

Using a sample of U.S. commercial banks from 2009 to 2022, we find that the flow of non-core deposits, rather than that of core deposits, becomes more sensitive to bank performance as banks receive increased attention on Twitter. This effect is particularly pronounced during periods of poor bank performance, when Twitter discussions are more influential, and for banks with more liquidity mismatch. Our results suggest that social media, rather than merely disseminating information about bank performance, makes depositors aware of their peers’ attention to banks, thereby intensifying the sensitivity of deposit outflows to weak fundamentals.

This study examines the impact of strategic alliances on corporate green innovation. We find that strategic alliances significantly promote corporate green innovation. Mechanism tests indicate that strategic alliances promote green innovation through channels of attracting market attention, alleviating agency problems, and stimulating collaborative innovation. Heterogeneity analysis demonstrates that the effects of strategic alliances are more pronounced for firms in areas with stringent environmental regulations and a favorable business environment, and firms facing intense product market competition. The findings provide new insights into the green transformation and upgrading of enterprises.

Financial technology, also known as Fintech, is transforming our daily life and revolutionizing the financial industry. Yet at present, consensus regarding the effect of Fintech on green bonds market is lacking. With novel data from China, this study documents robust evidence showing that Fintech development can significantly boost green bonds issuance. Further analysis suggests that this promotion effect occurs by empowering intermediary institutions and increasing social environmental awareness. Additionally, we investigate the heterogeneous effect and find that the positive relation is more pronounced for bonds without high ratings and in cities connected with High-Speed Railways network. The results call for the attention from policymakers and security managers to take further notice of Fintech utilization in green finance products.

The relationship between corporate Environmental, Social, and Governance (ESG) performance and its value has garnered increasing attention in recent times. However, the utilization of ESG scores by rating agencies, a critical intermediary in the linkage between ESG performance and value, presents challenges to ESG research and investment as a result of inherent subjectivity, hysteresis, and discrepant coverage. Fortunately, news can provide an objective, timely, and socially relevant perspective to augment prevailing rating frameworks and alleviate their shortcomings. This study endeavors to scrutinize the influence of ESG-related news on the Chinese stock market, to showcase its efficacy in supplementing the appraisal of ESG performance. The study's findings demonstrate that (1) the stock market is significantly impacted by ESGrelated news; (2) ESG-related news with different attributes (sentiments and sources) have notably diverse effects on the stock market; and (3) the heterogeneity among enterprises (industries and ownership structures) affects their ability to withstand ESGrelated news shocks. This study contributes novel insights to the comprehensive and objective assessment of corporate ESG performance and the management of its media image by providing a vantage point on ESG-related news.

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.