Salience theory has been proposed as a new stock trading strategy. Therefore, to assess the validity of this proposal, a complex decision trading system was constructed based on salience theory, a variational mode decomposition (VMD) model, a bidirectional gated recurrent unit (BiGRU) model, and high-frequency trading. The system selected 30 Chinese new energy concept stocks, ranked the stocks using salience theory, and selected the top and bottom three stocks for two portfolios. Twelve stages were established, after which the VMD and BiGRU models were applied to the predictions. The final predicted returns for the high ST group A (GA) were 194.06% and for the low ST group B (GB) were 165.88%. This paper validated the powerful utility of salience theory and deep learning to analyze Chinas new energy market. And it explains the issues and questions raised by previous researchers.

Utilizing the removal of the bank lending interest rate floor (IRFD) in China as an exogenous shock of banking liberalization, we find that IRFD leads to a significant rise in firms’ cost of equity capital, which is consistent with the prediction from the MM theory. The identified effects are more pronounced among firms with weaker ex-ante corporate governance and more severe ex-ante agency problems. We also find that IRFD witnesses an increase in the amount of acquired bank loans, a decrease in the average interest rate, and an increase in free cash flow. Further evidence also suggests IRFD provokes a drop in firms’ investment quality. Overall, our findings highlight an unexplored role of banking sector deregulation on firms’ cost of equity capital.

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.

Chinese enterprises are currently facing unprecedented economic transformations accompanied by a diverse array of challenges. This article delves into these challenges and provides management recommendations to assist companies in addressing these pressing issues. First, China's economic growth is gradually slowing, prompting companies to explore new avenues for growth, such as diversifying their products and markets, enhancing research and development, and expanding into emerging markets. Second, the uncertain global trade landscape has impacted exports and supply chains, necessitating diversified supply chains, new trade partnerships, and proactive strategies to navigate potential trade policy changes. Additionally, the pressure of technological innovation cannot be underestimated, urging companies to increase R&D investment, collaborate with other enterprises on research, and recruit and nurture high-quality tech talent. Furthermore, with the Chinese government's growing focus on environmental concerns, companies need to invest in clean production technologies, build sustainable supply chains, and actively fulfill their social responsibilities. Other challenges including rising labor costs, intellectual property protection, financial risks, regulatory compliance, talent recruitment and retention, and digital transformation all require proactive responses. By adopting proactive management strategies, Chinese enterprises can thrive in this era filled with both opportunities and risks, achieving sustainable growth and enhanced competitiveness.

As a vital documentation for assessments, rewards and punishments in terms of political promotions, the intellectual property pilot city policy (IPPC), an strategic incentive measure to enhance innovation capacities at the city and firm level, may play a prominent role in innovation fostering in China. Yet patent bubbles that focus more on quantity over quality have been thrown into doubt, as local cadres and firms shall pay more attention to the easier observable low-quality innovation performance amid the pressure of political task. this paper conducts an investigation that drew upon listed firm data from 270 prefecture-level cities and employs a PSM-DID design to evaluate the IPPC policy effectiveness on innovation quality and innovation quantity. The results are obvious: The policy have boosted the number of innovations, but has a limited effect on improving the quality of innovation. We further apply a hierarchical liner modeling approach to deal with the stratified cityand firm-level data and to verify the mechanism through which policy distortions may affect corporate innovation. There also gives evidence that the IPPC policy comes into effect mainly through financial subsidies, institutional supply and the intensity of IPR protection at the local scale. This report concludes by proposing further policy implementations for the future optimization of China’s innovation strategies.

The study explores the impacts and processes of traditional Confucianism on the green technology innovation behavior of organizations from the perspective of the informal system, using samples of Chinese A-share listed companies from 2003 to 2022. The findings indicate that Confucianism has a significant promotional effect on green technological innovation, which remains robust after using the cross-multiplier term between the number of regional Confucius temples and the mean ESG of firms as an instrumental variable to mitigate the endogeneity problem and a series of tests. According to mechanistic research, Confucianism works largely through two channels: reducing agency conflicts and raising environmental consciousness. Further investigation reveals that there is a substitution impact between Confucianism in the informal institution and environmental legislation in supporting green technology innovation in firms. To encourage green technological innovation in enterprises, it is critical to emphasize the integration of informal and formal systems, as well as to fully use traditional culture’s governance efficacy in supporting the enterprise green transformation.

The opening of high-speed rail (HSR) has significantly boosted business development in China. This study constructs a credit rationing model based on the theory of information asymmetry, and takes the opening of HSR as a quasi-natural experiment to empirically examine its impact on the investment and financing decisions among firms with different risk profiles using data from A-share listed companies from 2005 to 2019. The findings reveal that HSR opening significantly reduces corporate short-term loans while increasing long-term loans, without affecting loan costs. Lowriskfirms, as opposed to high-risk ones, experience notable reductions in short-term loan amounts and extended loan terms post-HSR opening. This is attributed to HSR mitigating information asymmetry between banks and firms. Additionally, HSR opening suppresses "short-term debt for long-term use" behaviors, thereby enhancing investment efficiency and quality. The study empirically supports the idea of leveraging HSR's economic stimulus in terms of firm investment and financing.

The emergence of deep learning has yielded substantial advancements in computer vision, hence offering novel opportunities for the interdisciplinary exploration of finance and computer science. This paper adopts a cognitive dissonance theory viewpoint to investigate the impact of managers face emotion on market performance and risk in Chinese listed companies from 2016 to 2022. We employ deep learning model to analyze managers’ facial emotion. We find that the more positive facial expressions of managers in earnings conference call predict better market performance, lower volatility and share price crash risk. This study deepens the application of cognitive dissonance theory.

We construct a stock learning index in China A-share market, which is based on a theoretical model of information and investment choice. The higher the learning index value, the more thoroughly the individual stock is learned. Our study shows that a stock with a high learning index will have a lower expected future return compared to a stock with a low learning index. Additionally, decomposition of predictive power shows that the predictive power of the learning index mainly comes from the persistence of its own predictive power, while the rest cannot be explained by changes in the volume of news (proxy for information flow). Moreover, the learning index can explain many market anomalies in China A-share market.

This paper examines the effects of superstitious psychology on investors’ decision making in the context of Mercury retrograde, a special astronomical phenomenon meaning “everything going wrong”. Using natural experiments in the Chinese stock market, we find a significant decline in stock prices, approximately -3.14% in the vicinity of Mercury retrogrades, with a subsequent reversal following these periods. The Mercury effect is robust after considering seasonality, the calendar effect, and well-known firm-level characteristics. Our mechanism tests are consistent with model-implied conjectures that stocks covered by higher investor attention are more influenced by superstitious psychology in the extensive and intensive channels. A superstitious hedge strategy motivated by our findings can generate an average annualized market-adjusted return of 8.73%.