We evaluate the impact of digital finance on the ESG performance of manufacturing enterprises and whether digital and traditional finance play a complementary or substitute role in promoting the ESG performance. First, we find that developing digital finance can alleviate financing constraints and promote technological innovation, thereby increasing enterprises' investment in environmental, social, and governance, providing sufficient technical support, and improving their ESG performance. Furthermore, digital finance and traditional finance have a direct impact on the ESG performance and further enhance their influence through complementary effects. Therefore, this paper may provide a valuable reference for finance to support manufacturing enterprises' development effectively.

The study indicates that under conditions of financial repression, a enterprise’s ESG performance significantly impacts the extent of its short-term debt used for long-term purposes. The mechanism test reveals that ESG performance mitigates the degree of short-term debt for long-term use through three pathways: enhancing information transparency, alleviating financing constraints, and curbing excessive investment. Further research suggests that the influence of ESG performance on the use of short-term debt for long-term purposes is more pronounced among private enterprises, high-pollution and high-energy-consuming enterprises, and enterprises in underdeveloped regions. This paper enriches the research on the relationship between ESG performance and corporate financing decisions.

Purpose – This paper takes the Shanghai-Shenzhen-Hong Kong Stock Connect as a quasi-natural experimentand investigates the impact of capital market liberalization on the corporate debt maturity structure. It also aimsto provide some policy implications for corporate debt financing and further liberalization of the capital marketin China. Design/methodology/approach – Employing the exogenous event of Shanghai-Shenzhen-Hong Kong StockConnect and using the data of Chinese A-share firms from 2010 to 2020, this study constructs a difference-in-differences model to examine the relationship between capital market liberalization and corporate debt maturitystructure. To validate the results, this study performed several robustness tests, including the parallel test, theplacebo test, the Heckman two-stage regression and the propensity score matching. Findings – This paper finds that capital market liberalization has significantly increased the proportion of long-term debt of target firms. Further analyses suggest that the impact of capital market liberalization on thedebt maturity structure is more pronounced for firms with lower management ownership and non-Big 4 audit.Channel tests show that capital market liberalization improves firms’ information environment and curbsself-interested management behavior. Originality/value – This research provides empirical evidence for the consequences of capital marketliberalization and enriches the literature on the determinants of corporate debt maturity structure. Further thisstudy makes a reference for regulators and financial institutions to improve corporate financing through thegovernance role of capital market liberalization.

We examine how the sudden drop in public information search capability caused by Google’s withdrawal from China affects Chinese analysts’ earnings forecasts. We observe, after Google’s withdrawal, a decline in analysts’ forecast accuracy for firms with foreign trade relative to those without it. This decline suggests that the withdrawal hinders analysts’ acquisition of foreign information about firms, which decreases the quality of their earnings forecasts. We also find that the effect of the withdrawal on forecast accuracy is stronger for firms with higher business complexity and more opaque financial reporting and for analysts with weaker information processing capacity and more attention constraints. Additionally, we find that corporate site visits serve as an alternative information source that can compensate for the information loss caused by the Google withdrawal. Last, we document that the withdrawal reduces analysts’ forecast timeliness and increases their forecast dispersion.

We examine the pricing ofsystematic information asymmetry, induced by Chinese gov-ernment intervention, in the cross-section of stock returns. Using market-wide order im-balance as a proxy for systematic information, we observe a strong correlation betweenthe standard deviation of market-wide order imbalance and economic policy uncertainty.Furthermore, we find a significant positive relationship between the sensitivity of stocks tosystematic information asymmetry (OIBeta) and their future returns. The average monthlyreturn spread between high- and low-OIBeta portfolios ranges from 1.30% to 1.77%, andthis result remains robust after controlling for traditional risk factors. Our results providesubstantial evidence that the pricing of OIBeta is driven by systematic information asym-metry rather than alternative explanatory channels.

Using comprehensive account-level data and 192 asset pricing anomaly signals, we investigate whether retail investors and institutions trade on anomalies in China. We find that retail investors tend to trade contrary to anomaly prescriptions, suggesting that they have a strong tendency to buy (sell) overvalued (undervalued) stocks. In contrast, institutions trade consistent with anomalies, indicating that they buy (sell) undervalued (overvalued) stocks. Regarding the information content of anomalies, we find that small retail investors trade contrary to trading-based anomalies, whereas institutions trade consistent with both trading- and accounting-based anomalies. Additionally, lottery stock preference and return extrapolation help explain investors’ trading behavior on anomalies.

This study highlights asymmetries in liquidity risk pricing from the perspective of heterogeneously informed traders facing changing levels of preference uncertainty. We hypothesize that higher illiquidity premium and liquidity risk betas may arise simultaneously in circumstances where investors are asymmetrically informed about their trading counterparts’ preferences and their financial firms’ timely valuations of assets . We first test the time-varying state transition patterns of IML, a traded liquidity factor of the return premium on illiquid-minus-liquid stocks, using a Markov regime-switching framework. We then investigate how the conditional price of the systematic risk of the IML fluctuate over time subject to changing levels of preference uncertainty. Empirical results from the Chinese stock market support our hypotheses that investors’ sensitivity to the IML systematic risk conditionally increase in times of higher preference uncertainty as proxied by the stock turnover and order imbalance. Further policy impact analyses suggest that China’s market liberalization efforts, contingent upon its recent stock connect and margin trading programs, reduce the conditional price of liquidity risk for affected stocks by helping the incorporation of information into stock prices more efficiently. Tighter macroeconomic funding conditions, on the contrary, conditionally increase the price of liquidity that investors require.

The process of internationalization of China’s banking industry began in 1917. After a hundred years of development, China’s banking internationalization has made great achievements. However, there is still a big gap between China’s banking industry and the financial institutions in some developed countries in the field of internationalization. In the process of internationalization, China's banking industry are now still facing the dilemma of backward development concept, lack of effective risk control system and international talents. This thesis mainly introduces the history, present situation and difficulties of the internationalization of China’s banking industry. The first part gives a description to the history of the internationalization of China’s banking industry, which starts in the year of 1917. An analysis of the current situation of China’s banking industry’ internationalization is given in the second part of this article. And the third part summarizes the difficulties that are faced by China’s banking industry.

Utilizing a dataset from 2013 to 2022 on China’s listed companies, we explored whether a hedge fund network could help explain the occurrence of Chinese stock crash. First, this study constructs a hedge fund network based on common holdings. Then, from the perspective of network centrality, we examine the effect of hedge fund network on stock crash risk and its mechanism. Our findings show that companies with greater network centrality experience lower stock crash risk. Such results remain valid after alternating measures, using the propensity score matching method, and excluding other network effects. We further document that the centrality of hedge fund network reduces crash risk through three channels: information asymmetry, stock price information content and information delay. In addition, the negative effect of hedge fund network centrality on crash risk is more prominent for non-SOEs firms. In summary, our research shed light on the important role of hedge fund information network in curbing stock crash.

This paper investigates whether Environmental, Social, and Governance (ESG) performance influences the stock idiosyncratic risk and extreme risk. We find that the ESG performance of listed companies significantly reduces the stock idiosyncratic risk and extreme risk. Furthermore, we identify that this mitigating effect is shaped by the nature of enterprise ownership and the firm life cycle. Through additional mechanistic analysis, we confirm that ESG performance affects the stock price volatility risk of listed companies by reducing levels of corporate earnings management and bolstering corporate reputation, thereby alleviating both idiosyncratic risk and extreme risk in stock prices.