This paper develops a network to analyze inter-industry risk spillovers during high and low volatility periods. Our findings indicate that China's Industrials and Consumer Discretionary exhibit the greatest levels of spillovers in both high and low volatility states. Notably, our results demonstrate the "event-driven" character of structural changes to the network during periods of pronounced risk events. At the same time, the economic and financial network exhibits clear "small world" characteristics. Additionally, in the high volatility stage, the inter-industry risk contagion network becomes more complex, featuring greater connectivity and direct contagion paths. Furthermore, concerning the spillover connection between finance and the real sector, the real economy serves as a net exporter of risk. The study's findings can assist government agencies in preventing risk contagion between the financial market and the real economy. The empirical evidence and policy lessons provide valuable insights for effective risk management.

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.

This paper studies the impact of AI technology on the mutual fund industry. I develop a new measure of AI adoption based on hiring practices and find that this measure can predict fund performance. The funds with high AI ratio outperform non-AI funds, after I controlling for standard factors and fund characteristics. Further empirical evidence shows that funds with a high AI ratio tilt their portfolios toward high information intensity stocks, indicating that mutual funds benefit from AI technology adoption by improving their information capacity. Consistent with this channel, I find that the outperformance of these mutual funds mainly comes from better stock picking skills. Finally, AI technology adoption has a negligible effect on fund manager turnover.

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 digital transformation strategies have emerged as a primary approach for enterprises to enhance their Total Factor Productivity (TFP), it is crucial to empirically examine the impact of these strategies on TFP. For this purpose, this study considers these transformation strategies as a quasi-natural experiment and employees a propensity score-weighted difference-indifferences methodology on data from Chinese firms listed on the A-share market between 2007 and 2020. The key findings include: (1) digital transformation has a significant positive influence on TFP; (2) Generalized boosted regression trees analysis reinforces this finding after controlling for other TFP determinants; (3) notably, non-state-owned and technology-intensive enterprises exhibit a more distinct enhancement in TFP following digital transformation. These results underscore the need for firms to increase investment in research and development capabilities and digital competencies.

Despite nearly twenty years of privatization, mixed-ownership reform has been the mainstay of SOE reform in China in recent years. This raises the question of whether the financial performance of mixed-ownership firms (Mixed firms) is better than private-owned enterprises (POEs). Although Mixed firms suffer more from government intervention, unclear property rights, and interest conflicts between state shareholders and private shareholders, they can also benefit from the external resources controlled by the state. Therefore, the performance of Mixed firms is still unclear. Collecting data from the Chinese A-share listed market, we divide the firms into POEs, Mixed firms controlled by the state (MixedSOEs), and Mixed firms controlled by the private sectors (MixedPOEs). Measuring profitability using ROA and ROE, we find that on average, POEs perform better than Mixed firms, and MixedPOEs have a higher profitability than MixedSOEs. Within Mixed firms, more state shares are related to lower profitability, and more private shares are related to higher profitability. Using the NBS survey data, we further find that on average, SOEs exhibit the lowest profitability, with MixedSOEs and MixedPOEs in the middle, and POEs have the highest profitability. We try to address the endogeneity challenge in several ways and get similar results. Overall, our analysis provides new evidence on the financial performance of mixed-ownership firms.

By using a unique proprietary dataset and implementing the Wuhan (China) lockdown from January to April 2020 as a natural experiment, we find that individual mutual fund investors in Wuhan significantly reduced their trading frequency, total investment of their portfolios, and risk level of their invested funds during the lockdown period as compared to investors in other cities. These changes are stronger for older investors and are reversed soon after the lifting of the lockdown. Our results suggest that the elimination of face-to-face interaction among individual investors reduced their information sharing, which led to more conservatism in their financial trading. These results are not supported by the alternative explanations of limited investor attention and temporary changes in personal circumstances, including depression and/or income reduction, during the lockdown period. Finally, consistent with the theory of naïve investor trading, we also find that investors received higher trading returns during the lockdown.

In reality, we find assets traded in the transparent centralized market and opaque decentralized market. To explain the traders' choices of venues, we develop a model of dynamic learning and dynamic market choice between the centralized market and decentralized markets. With heterogeneous trader value correlation, we find that when asset sensitivity or volatility is sufficiently low, traders prefer the decentralized market; when asset sensitivity or volatility is intermediate, switching between centralized and decentralized markets can be the optimal market choice; when asset values are sensitive to volatile fundamentals, assets are traded only in the centralized market. We provide empirical evidence in support of the model predictions. We discussed the welfare implications of various market designs under endogenous market choices. We find that introducing post-trade transparency in the decentralized market improves welfare. Surprisingly, introducing pre-trade transparency in the decentralized market may decrease welfare as it increases traders' incentives to choose a decentralized market earlier and hurts future traders in the centralized market.

China historically paid more attention to improving patent quantities because policymakers wished to improve the patent qualities by stimulating patent quantities, and it focused on developing invention patents but paid little attention to utility model patents because many people believe that the quality of utility model patents is lower than that of invention patents. Varies studies discussed the issues of patent qualities, but little empirical evidence was developed to show the relationship between patent quantities and patent qualities or prove that the utility model patents’ quality is lower than the invention patents’ quality. An empirical analysis is helpful to find the impact of patent quantities on patent qualities, and comparing it with the impact of R&D investments on patent qualities will show which has a greater impact. By comparing them with invention patents’ quality, the statistical examination on the quality of utility model patents is also meaningful.

This study provides the first empirical evidence on the relationship between the chairman of the board of directors (COB) and corporate financial performance. Using a sample of Chinese A listed firms between 2008-2017, we find reliable evidence that the COB turnover improves corporate financial performance. Moreover, the existence of a majority shareholder (Majority) positively influences corporate financial performance, while firm nature (private majority shareholder or public majority shareholder)(Private) may not.