Abstract:Stock market liberalization plays an essential role in China’s highlevel opening by optimizing the investor structure and improving market efficiency. Based on the heterogeneous agents model in the open economy, this paper explores the impact of the “ShanghaiHong Kong Stock Connect” program on irrational investor behavior and market efficiency. It is discovered that stock market liberalization influences the two representative irrational behaviors differently. The implementation of the “ShanghaiHong Kong Stock Connect” program has an insignificant impact on autonomous switching behavior but directly reduces herding. After the implementation of the “ShanghaiHong Kong Stock Connect” program, herding decreases when the RMB appreciates and when the Libor increases. This paper develops a market efficiency indicator incorporating both rational and irrational forces. It is found that the implementation of the “ShanghaiHong Kong Stock Connect” program improves the proportion of stock return volatility driven by fundamental force, thus increasing the efficiency of the local market. This paper extends the literature on stock market liberalization’s effect on microentities and provides an empirical basis for further liberalization.

Abstract:Strengthening and expanding the real economy’s foundation necessitates enhancing the capabilities and level of financial services targeted at the real sector. This study examines the governance effect of institutional investors’site visits on corporate financialization. Using comprehensive site visit data and detailed textual analyses for firms listed on the Shenzhen Stock Exchange, our empirical analysis shows robust evidence that institutional investors’ site visits significantly curbs firm financialization, as corroborated by rigorous sensitivity analyses and endogeneity tests. By undertaking thematic text analysis based on the interaction content, the study uncovers potential mechanisms through which institutional investors’ site visits influence the governance of firms financialization, notably by enhancing core business performance and encouraging innovation and research and development (R&D) investments. Heterogeneity analysis further reveals variations in the governance effects of site visits contingent upon factors of executive power and firm ownership nature. Grounded in the specific form of institutional investor engagement through site visits, these findings provide practical insights for encouraging firms to transition from an abstract focus to a concrete one, concentrating on core operations, and advancing the development of institutional investors.

Abstract:Based on a thought experiment that distinguishes between internal and external risks in financial transactions, this paper constructs an analytical framework to examine how external investors’risk perception affects the equilibrium outcomes in the securities market. A controllable and replaceable securities trading experiment is conducted to empirically test the theoretical hypothesis. The results indicate that investors are more sensitive to external risks. When external risks reach a critical threshold, changes in external investors’coping strategies can trigger abrupt fluctuations in market returns and trading volumes, demonstrating both price effects and quantity effects of external risks. The findings suggest that the fundamental cause of the “sharp rises and falls” in China’s securities market may lie in the moral hazards and opportunistic behaviors of corporate controllers.

Abstract:This study utilizes Gradient Boosting Regression Trees and Random Forest Agorithms to explore the predictive power of 64 features of six dimensions, which previous studies have identified as determinants of corporate tax avoidance. The results show that features of tax shelters have strong predictive power. Specifically, donation expenditure, total accruals, employment, and R&D expenditure emerge as the most influential predictors. However, external features have limited predictive power. Examining the relationships between key features and tax avoidance,this paper finds that, in general, donation expenditure and employment are negatively related to tax avoidance levels, while total accruals and R&D expenditure are positively associated with tax avoidance levels. However, in a few cases, employment is positively correlated with tax avoidance, and the correlations between tax avoidance and total accruals or R&D expenditure are weak. Interactive effectsexist between donation expenditure and return on total assets, total accruals and supervisory board size,employment and CEO tenure, and R&D expenditure and institutional ownership. Treebased machine learning algorithms have greater predictive power than linear regressions. Our results suggest that more attention should be paid to features of tax shelters in tax collection procedures and the design of intelligent tax systems, and that restricting tax shelters is crucial in policy making.

Abstract:The verticalization of large language models (LLMs) has become an important trend. In highly specialized and crossmarket contexts, such as crude oil futures, generalpurpose LLMs struggle to accurately interpret domainspecific terminology and complex semantics, and they are prone to lookahead bias. This paper proposes an integrated approach that combines LLMs with a domainspecific sentiment lexicon to measure the tone of crude oil news. By integrating the prior knowledge of a domain lexicon with the semantic understanding of LLMs, the proposed method enhances both the interpretability and predictive power of tone measures. Specifically, based on 93 004 Chinese and English crude oil news articles from InfoBank and Factiva between 2018 and 2022, this study constructs a vertical domain lexicon, refines high signaltonoise corpora, performs domainspecific pretraining on a general BERT model, and applies weakly supervised finetuning guided by futures return signs to generate an integrated tone index. Empirical results show that the tone measure derived from the proposed method significantly outperforms dictionarybased and general LLM methods in explaining and predicting Shanghai crude oil futures returns. Robustness tests confirm consistent results, and the method also exhibits superior outofsample predictive performance for 2023～2024. Further analysis reveals that the impact of news tone on crude oil futures returns is transmitted through investor attention as a mediating channel, and under the integrated framework, this mechanism aligns closely with economic logic in both direction and significance. Moreover, the risk spillover analysis indicates that the integrated tone measure effectively captures the tailrisk transmission from international news sentiment to China’s crude oil futures market. This study contributes by proposing a reproducible vertical application framework for financial large language models, revealing the dual role of news tone in market return formation and risk transmission, and providing new quantitative tools for risk identification and policy formulation in the crude oil futures market.

Abstract:With the vigorous development of financial technology, online consumer credit lending has become a key area of financial innovation, attracting significant attention from both the academic and industry communities. Why do online lending borrowers pay high interest rates to borrow money, and what impact will these loans have on their consumption? The relationship between borrowers’lending behavior and their consumption behavior warrants indepth exploration and research. This paper conducts an empirical study on the consumption behavior of borrowers with the characteristic of “Robbing Peter to Pay Paul” on a large domestic online lending platform, based on their real lending data. The research findings are as follows: First, overall, online lending has a stimulating effect on borrowers’total Taobao consumption before borrowing. Second, compared with borrowers who do not exhibit the pattern of “Robbing Peter to Pay Paul”, borrowers with this characteristic show a significant increase in both total Taobao consumption and nonessential consumption in the short period before borrowing. This indicates that they have certain economic and consumption capabilities and are more inclined to purchase nonessential goods and engage in upgraded consumption. Third, borrowers exhibiting the characteristic of “Robbing Peter to Pay Paul” display a phenomenon of “preconsumption”, often consuming first and borrowing later. This study attempts to explore the relationship between borrowers’lending behavior and consumption behavior from the perspective of borrowers’borrowing motives, which has important academic value and practical significance for clarifying borrowers’borrowing motives and assisting regulators in strengthening the supervision of the online consumer credit lending industry.

Abstract:The top management team, comprising directors, supervisors, and executives (DSEs), is the primary group responsible for corporate financial misconduct. By applying knowledge graph embedding (KGE) to DSE profiles, this paper constructs a novel fraud propensity indicator (PIFT) that captures semantic similarity across three dimensions(personal) basic traits, governance structure, and cross tiesfrom a holistic perspective. Empirical tests using Logit and binary Probit models reveal that Higher PIFTs are associated with a greater likelihood of financial violations, and that, compared to singledimension indicators, PIFT demonstrates superior predictive power. Further analyses show that nonindependent directors play a dominant role in driving PIFT’s effectiveness, that the proportion of fraudulent firms in the same industry strengthens PIFT’s impact, and that higher regional legal enforcement enhances the link between PIFT and fraud risk, while state ownership remains insignificant. This study establishes a new starting point for applying knowledge graph embedding in corporate finance research, following the standard empirical financial research paradigm.

Abstract:The essence of governance lies in enriching the people. The steady advancement of common prosperity stands as a central objective in the new era, with digital finance offering a novel pathway toward its attainment. Enterprises, serving as key entities that adopt digital finance, generate social wealth, and fulfill social responsibilities, act as critical microlevel agents and operational hubs in translating the empowerment of digital finance into tangible outcomes for common prosperity. From a microenterprise perspective, this study examines the impact of digital finance on common prosperity. The findings reveal that a stronger inclination toward digital finance adoption at the enterprise level correlates with better performance in advancing common prosperity. Grounded in New Structural Economics and PrincipalAgent Theory, the mechanism analysis is conducted from two dimensions: Overall prosperity and shared prosperity. The results indicate that digital finance facilitates enterprise participation in common prosperity by enhancing material wealth creation, improving primary distribution, providing fiscal support for redistribution through taxation, and promoting corporate social responsibility. Furthermore, it is confirmed that overall prosperity serves as the material foundation for shared prosperity. This research offers theoretical insights and policy implications for fostering the development of digital finance and realizing its potential in driving progress toward common prosperity.

Abstract:Manufacturing agglomeration and energy conservation and emission reduction serve as important levers and target functions for highquality development in China, significantly influenced by the level of digital innovation and the uncertainty of economic policy. Based on the dual role of digital innovation and the hierarchical moderating effect of economic policy uncertainty, this study utilizes panel data from Chinese provinces and employs: A spatial Durbin model combined with multiscenario analysis to conduct an indepth exploration of the impact of manufacturing agglomeration on carbon emission performance. The study finds an ‘N’shaped curve relationship between manufacturing agglomeration and carbon emission performance, indicating a winwin situation for economic growth and carbon emission performance once manufacturing agglomeration reaches a certain threshold. Digital innovation plays a dual role: As an outcome, there is an inverted ‘U’shaped curve relationship between digital innovation and carbon emission performance; as a process, it positively moderates the relationship between manufacturing agglomeration and carbon emission performance, with a stronger positive moderating effect under higher economic policy uncertainty scenarios. Further analysis shows that, under different scenario combinations, manufacturing agglomeration exhibits differentiated characteristics affecting carbon emission performance. This research provides valuable policy insights for promoting highquality development of regional manufacturing in China, achieving dual carbon targets, and facilitating Chinesestyle modernization.

Abstract:With the increasing complexity of the supply chain, the supply chain members aim to find ways to establish longterm cooperation which is an effective means of sharing benefits and mitigating risks. Renegotiationproof contract plays an important role in longterm cooperation. This paper investigates the twoperiod cooperation between the manufacturer and retailer, considering that the retailer’s types (i.e., demand types) change stochastically across periods under demand uncertainty. This paper models three types of longterm contracts under asymmetric information and examines the optimal renegotiationproof contract. The results show that the serial correlation of the retailer’s types influences the optimal renegotiationproof contract. Specifically, as the correlation increases, the optimal renegotiationproof contract consists of a separate contract with full commitment, a separate contract with commitment and renegotiation, and a pooling contract with commitment and renegotiation, respectively. The separate contract with full commitment is consistent with the optimal renegotiationproof contract when the correlation is small, since the information obtained in the first period cannot be used to design the contract in the second period when the retailer’s type changes significantly over periods. The separate and pooling contracts with commitment and renegotiation can be updated with the firstperiod signal. However, the pooling contract with commitment and renegotiation is the optimal renegotiationproof contract when the manufacturer prefers the secondperiod expected profit over that of the first period.