Does digital financial inclusion alleviate poverty? This study investigates this question by integrating the Digital Financial Inclusion Index of Peking University with microdata from the China Family Panel Studies (CFPS) to examine how the expansion of digital financial inclusion affects household multidimensional poverty in China. Anchored in Amartya Sen ’ s capability approach and operationalized through the Alkire–Foster (A–F) framework, the study identifies multidimensional poverty across five key dimensions: income, health, education, insurance, and living standards. Probit models are employed to estimate how digital financial inclusion influences both the likelihood and structure of multidimensional poverty, while instrumental variable techniques are used to address potential endogeneity. Beyond the average effects, the study further explores the mechanisms through which digital financial inclusion contributes to poverty alleviation, focusing on three channels—promoting household consumption, increasing financial investment, and enhancing access to credit. The results reveal that digital financial inclusion significantly mitigates multidimensional poverty, particularly by improving income, living standards, and health outcomes, though its effects on education and insurance are limited. These findings underscore the transformative role of digital finance in fostering inclusive growth, suggesting that policies expanding digital financial infrastructure and literacy can amplify its poverty-reducing effects and advance equitable development.

This study investigates how the development of digital finance influences the geographical distribution of corporate supply chains using data from Chinese A-share listed companies from 2010 to 2023. We examine whether digital finance enables firms to overcome traditional geographical constraints and adopt different supply chain distribution strategies. The analysis identifies two primary mechanisms through which digital finance influences supply chain geography: governance effects, which operate through enhanced risk management and information transparency, and financing effects, which function through alleviated capital constraints and trade credit provision. We further explore heterogeneous impacts across four dimensions: regional economic development, regional digital infrastructure, industry market competition, and enterprise lifecycle stages. By examining the geographical distribution of supply chains as an outcome of digital finance development, this study provides novel evidence on the micro-governance implications of digital finance. Our findings contribute to understanding how digital finance fundamentally changes the geographical constraints that have historically shaped supplier selection decisions and enables firms to develop more flexible supply chain configurations.

In view of the divergence of existing research results on the relationship between ESG and investment returns, this paper constructs an S-score metric, which comprehensively measures corporate sustainability performance. It further tests the applicability of a sustainability-based investment strategy using this metric in China's A-share market. Using Shanghai and Shenzhen A-shares from May 2016 to April 2024 as the research sample, the S-score is constructed across five dimensions: Profitability, Growth Opportunities, Investment Efficiency, Risk Mitigation, and ESG Performance. The S-score is calculated using Z-score standardization and entropy weighted. Strategy effectiveness was tested through univariate grouping, bivariate grouping, and Fama-Macbeth regression, further examining strategy performance under varying market conditions, holding periods, and information environments. The study finds that the S-score demonstrates significant discriminative power for cross-sectional stock returns. The hedge portfolio based on this metric achieved an annualized excess return of 7.943% after adjusting for the China three-factor (CH-3) model. Its predictive power remains robust after controlling for variables such as market capitalization and book-to-market ratio, delivering significant positive returns across bull and bear markets, extreme pandemic conditions, and holding periods of up to eight years. From a behavioral finance perspective, this paper reveals that explanations such as the gradual diffusion of information and investors' limited attention span help elucidate the profitability of the S-score strategy. The findings demonstrate the effectiveness of Sustainable Investing strategies in China's A-share market, indicating that ESG-integrated factor investing can optimize resource allocation. This research contributes empirical evidence on Sustainable Investing in emerging markets, providing insights for policy formulation and practical implementation while supporting the virtuous cycle between Sustainable Investing and long-termism.

This study documents a novel, culturally embedded calendar anomaly in the Shanghai Composite Index (SSE Composite) derived from the Nayin (纳音) Five Elements system—a traditional Chinese sexagenary calendrical framework. Utilizing daily data from 1990 to 2025, the analysis reveals a significant correlation between elemental two-year periods and market performance. Key findings include: Earth-Element Dominance: Earth periods exhibit a 100% positive return rate (4/4) with a mean return of +123.4%. The effect size is substantial (Cohen’s d=1.50) compared to non-Earth periods. Metal-Element Declines: Metal periods universally display a structural peak-and-decline morphology, with an average −30.4% late-cycle decline. Water-Element Momentum: Water periods systematically mirror the directional momentum of their predecessors with 100% accuracy (3/3). These patterns fail to replicate in the S&P 500, suggesting a unique cultural-behavioral channel where traditional metaphysical cycles modulate investor sentiment in the Chinese market. This research provides the first empirical validation of Nayin-based cyclicality in financial asset pricing, offering a predictive framework for institutional and individual investors focused on the China-specific market. Keywords: Calendar anomaly, Chinese traditional calendar, Nayin Five Elements, Shanghai Composite Index, Cultural behavioral finance, Sexagenary Cycle, Market Sentiment Declaration of Interest The author declares no conflict of interest. To ensure the objectivity of this research, the author further declares that he holds no active personal trading positions in the securities discussed. The author's personal trading account has been inactive with zero transactions over the past five years.

Prevailing research, assuming developed financial markets, concludes that Chinese firms heavily rely on “short-term credit for long-term investment.”We challenge this view, arguing that China's vibrant informal financial system provides crucial alternative funding. Consequently, the severity of this maturity mismatch is likely overestimated. To investigate this, we examine strategic alliances as a representative informal institution. Our analysis confirms that such alliances significantly mitigate maturity mismatch, revealing that they enhance information sharing and reduce transaction costs. This provides initial evidence of informal institutions' critical role in addressing this issue. Given the prevalence of similar arrangements in China—like private lending and inter-corporate financing—our findings highlight the need to look beyond formal systems. This perspective not only recalibrates the understanding of corporate financing in China but also opens ample avenues for future research on informal finance's role in emerging economies.

Do investors respond to what fund managers say, or how they look saying it? Using 2,000 live-streamed sessions by Chinese ETF managers and multimodal machine learning, we show that managers’ facial expressions, not their words, drive fund flows. A one-standard-deviation increase in positive facial affect raises next-day flows by 0.17pp (260% of mean). Vocal tone shows weak effects; textual sentiment shows none. Critically, facial expressions predict flows but not returns, indicating pure persuasion rather than information transmission. Effects strengthen when investors are emotionally vulnerable (down markets, retail-heavy funds) and persist 2-3 weeks before dissipating. Our findings challenge the emphasis on textual disclosure in finance and raise questions about investor protection as video communication proliferates.

Periods of market crisis are often accompanied by heightened fear and information overload, which can induce information avoidance behaviors such as the ostrich effect. While prior research has documented investors’ tendency to avoid unfavorable information, little is known about how different information sources—and trust in those sources—jointly shape such behavior under extreme uncertainty. Drawing on Granular Interaction Thinking Theory (GITT) and employing Bayesian Mindsponge Framework (BMF) analytics, this study examines how investors’ regular securities-related information sources is associated with the ostrich effect during the 2022 market downturn in China, and how these associations are conditioned by trust. Using survey data from 1,451 Chinese individual stock investors, we model investors’ recalled frequency of temporarily disengaging from stock investing as an indicator of information avoidance. The results show that regularly consulting professional sources, financial newspapers, and online forums is associated with information avoidance, whereas reliance on personal relationships and company disclosures is not. Importantly, trust moderates these relationships in distinct ways. Higher trust in professional sources is associated with reduced information avoidance, while higher trust in financial newspapers and online forums amplifies avoidance behavior. Among all sources, the interaction between trust and information referral is strongest for financial newspapers. These findings suggest that trust does not uniformly mitigate fear-driven avoidance. Instead, when combined with high-entropy information sources, trust can exacerbate cognitive and emotional strain, increasing investors’ propensity to disengage. By highlighting the joint roles of informational entropy and trust, this study advances behavioral finance research and offers practical insights for investors, policymakers, and regulators seeking to improve decision-making resilience during periods of market crisis.

This paper examines how auction design can unintentionally facilitate bidder collusion in land market. Departing from the dominant view that attributes low land concession revenues to corruption, we highlight how features of auction structure enable bidder-side collusion, suppressing sale prices. Using a dataset of land auctions from 15 Chinese cities (2006–2016), we find that two-stage (listing) auctions are significantly more susceptible to collusion than one-stage formats. Empirical evidence shows that sales concluding at the (secret) reserve price occur disproportionately in two-stage auctions, even after controlling for land and market characteristics. We argue that the transparency and sequencing of two-stage auctions, while designed to enhance fairness, inadvertently reduce monitoring costs and facilitate tacit bidder coordination. Our findings underscore the need to jointly consider auction format and reserve price policy in designing land sales to enhance market efficiency and mitigate collusion risks.

This study applies large language models (LLMs) to measure technological links and examines its predictive power in the Chinese stock market. Using the BAAI General Embedding (BGE) model, we extract semantic information from patent textual data to construct the technological momentum measure. As a comparison, the measure based on traditional International Patent Classification (IPC) is also considered. Empirical analysis shows that both measures significantly predict stock returns and they capture complementary dimensions of technological links. Further investigation through stratified analysis reveals the critical role of investor inattention in explaining their differential performance: in stocks with low investor inattention, IPC-based measure loses its predictive power while BGE-based measure remains significant, indicating that straightforward information is fully priced in while complex semantic relationships require greater cognitive processing; in stocks with high investor inattention, both measures exhibit predictability, with BGE-based measure showing stronger effects. These findings support behavioral finance theories suggesting that complex information diffuses more slowly in markets, especially under significant cognitive constraints, and demonstrate LLMs’ advantage in uncovering subtle technological connections that traditional methods overlook.

Innovation is crucial for long-term corporate value and competitive advantage; however, it can misalign the interests of managers and investors. Balancing managers’ short- and long-term goals is a pivotal challenge in promoting innovation incentives. Therefore, this study examines innovative incentives for managers of publicly traded firms to address the issue of agency problems. The study focuses on economic value-added (EVA) reform implemented by China’s State-Owned Assets Supervision and Administration Commission (SASAC), which encourages EVA-driven R&D investments as the primary management metric. The policy effectively motivates key corporate managers by reducing capital costs and stimulating increased innovation. Following this policy’s implementation, notable innovation disparities exist between state-owned enterprises and firms not subject to the reform. Furthermore, innovation incentives significantly affect overconfident company managers, yielding positive effects on innovation.