This study theoretically and empirically examines the impact of intangible capital on firm markups. The current research follows Altomonte et al. (2021) and first establishes a theoretical framework of intangible capital affecting firm markups. Accordingly, this study finds that an increase in intangible capital results in an increase in firm markups via the “production efficiency” channel but a decrease in firm markups via the “market-based pricing” channel. We use the data of Chinese manufacturing firms to further empirically study the influence of intangible capital on firm markups and its influencing mechanism. After a series of robustness and endogeneity tests, this research finds that intangible capital is conducive to increasing firm markups. Results of the empirical analysis also reveal that the positive impact of an increase in intangible capital on the markups of Chinese manufacturing firms via the “production efficiency” channel are higher than the negative impact of an increase in intangible capital via the “market-based pricing” channel. Moreover, the impact on the markups of different types of firms are not the same, with significant heterogeneity characteristics. This study provides micro evidence from a large developing country on how intangible capital affects the change in firm markups, thereby providing a new perspective on the economic effects of intangible capital.

We develop a deep-visualization framework for timing the factor zoo. Historical factor return trajectories are converted to two complementary image representations, which are then learned by convolutional neural networks (CNNs) to generate factor-specific timing signals. Using 206 equity factors, our CNN-based forecasts deliver significant economic gains: timed factors earn an average annualized alpha of about 6\%, and a high-minus-low strategy yields an annualized Sharpe ratio of 1.22. The outperformance is robust to transaction costs, post-publication decay, and factor category-level analysis. Interpretability analyses reveal that CNNs extract predictive signals from path boundaries and regime shifts, capturing patterns orthogonal to investor attention.

This paper examines how China allocates its newly accumulated foreign assets by analyzing the long-run relationship between net national savings, foreign exchange reserves, and outward direct investment (ODI). Using quarterly data from 2005 to 2023, a cointegrated vector autoregression framework shows that ODI—particularly through state-owned enterprises— has emerged as an important channel for recycling national savings abroad. Although short-run reserve fluctuations persist, sustained reserve accumulation has become less central to China’s external asset management. This study contributes to the literature by highlighting the institutional role of state ownership in shaping cross-border investment patterns and by identifying ODI as a strategic mechanism for channeling national savings internationally. The findings shed new light on China’s evolving approach to external asset allocation and its broader economic and geopolitical implications.

This study examines the economic consequences of China’s Three-Red-Lines policy, introduced in 2021 to cap real estate developers' leverage by imposing strict thresholds on debt ratios and liquidity. Developers breaching these thresholds experienced sharp declines in financing, land acquisitions, and financial performance. Privately owned developers(POE) are hit harder than state-owned firms (SOE), with larger drops in sales and higher default risk. Using granular project-level data, we show that the policy reduces developer sales primarily by curtailing new-project supply: breached developers launch fewer projects. On the demand side, homebuyers reallocate purchases from privately owned developers to SOEs, further widening the POE-SOE gap. The policy also reduced local governments’ land-transfer revenues and increased reliance on local government financing vehicles (LGFVs) for land purchases. These LGFV-acquired parcels exhibit very low subsequent development rates, which may increase local governments’off-balance-sheet debt risks.

This study develops a novel deep learning framework for bank distress prediction, designed to overcome the limitations of static network analysis and to enhance model interpretability. We propose a Spatio-Temporal Attention Network that uniquely captures the time-varying nature of systemic risk. Methodologically, it introduces two key innovations: (1) a dynamic interbank network whose connection weights are adjusted by the volatility of the Shanghai Interbank Offered Rate (SHIBOR), reflecting real-time market liquidity changes; and (2) a dual spatio-temporal attention mechanism that identifies critical time steps and pivotal contagion pathways leading to a distress event. Empirical results demonstrate that the model significantly outperforms traditional benchmarks across key metrics including accuracy and F1-score. Most critically, the architecture proves exceptionally effective at reducing Type II errors, substantially minimizing the failure to identify at-risk banks. The model also offers high interpretability, with attention weights visualizing intuitive risk evolution patterns. We conclude that incorporating dynamic, liquidity-adjusted networks is crucial for superior predictive performance in systemic risk modeling.

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.

In the Chinese context, the term “overseas” refers to countries and regions outside the sovereignty and jurisdiction of China. Overseas listing is an important strategy for firms to integrate into global capital markets and enhance their corporate investment efficiency. Using data from 600 Chinese companies listed exclusively overseas and 860 domestically listed firms for the period 2009–2023, this study analyzes the impact of overseas listing on corporate investment efficiency using empirical research methods, underlying mediating mechanisms, and the moderating role of economic policy uncertainty. The findings show that overseas listing improves Chinese firms’ investment efficiency. Compared to listing on the United States securities market (Nshares), listing on the Hong Kong securities market, (H-shares) has a pronounced effect on enhancing investment efficiency. Enhanced information disclosure quality improves the investment efficiency of Chinese enterprises listed overseas. Economic policyuncertainty can strengthen the positive impact of overseas listing on corporate investment efficiency. This study shows that overseas listing improves investment efficiency of firms in developing countries and offers new insights into advancing micro-level opening-up in these countries.

Purpose: High investment efficiency is a key dimension of high-quality enterprise development. As critical nodes embedded in supply chain networks, corporate investment behaviors are profoundly shaped by the structural characteristics of their supply chains. Concentrated supply chain configuration, as one of the core structural features, has not yet been systematically examined in terms of its impact on corporate investment efficiency and the underlying mechanisms, leaving an important research gap. Design/methodology/approach: Based on a sample of China’s A-share listed enterprises from 2007 to 2023, this study empirically examines the effect of concentrated supply chain configuration on corporate investment efficiency. Findings: First, concentrated supply chain configuration exerts a significant inhibitory effect on corporate investment efficiency, a conclusion that remains robust after a series of tests. Second, mechanism tests indicate that this influence operates primarily through three channels: exacerbating financing constraints, crowding out working capital, and deteriorating the information environment. Third, heterogeneity analysis shows that both supplier concentration and customer concentration inhibit investment efficiency, with the latter having a slightly stronger negative effect. The adverse impact is more pronounced in over-investing enterprises, non-state-owned enterprises, smaller firms, and those in growth or decline stages. Furthermore, regional factor market development, external market power, and internal control quality are found to effectively mitigate the negative effect of concentrated supply chain configuration on corporate investment efficiency. Originality: This study extends the research on determinants of corporate investment efficiency from a supply chain structure perspective, providing new theoretical insights and empirical evidence for understanding corporate investment behavior in China.

The governmental governance environment significantly influences real corporate investment. Based on the data of listed A-share enterprises from 2010-2020,we adopt a heterogeneous timing difference-in-differences method to examine the impact of Open government data (OGD) on real corporate investment by leveraging the launch of OGD platforms. It is found that OGD significantly promotes real corporate investment. This conclusion remains robust after a series of tests for robustness and endogeneity, including parallel trend, placebo, heterogeneity treatment effect, and replacing variable. The analysis of the impact mechanism reveals that OGD influences real corporate investment by reducing enterprise uncertainty and alleviating financing constraint. The heterogeneity analysis indicates that OGD exerts a more pronounced investment promotion effect on non-state-owned enterprises, without political affiliations, regions characterized by intense government intervention, and areas exhibiting low social trust. This study contributes both conceptual insights for advancing the real economy with higher quality and practical recommendations to support the modernization of national governance structures and administrative effectiveness.

This paper examines the role of institutional investors in shaping pricing dynamics within China’s nascent infrastructure Real Estate Investment Trust market. Introduced in 2021, China’s REITs have rapidly gained policy and market attention as a tool for financing large-scale infrastructure projects through equity-based securitisation. Unlike mature REIT markets, China’s infrastructure REITs are characterised by a high concentration of institutional ownership dominated by state-owned financial institutions. Using panel data on first 9 REITs from May 2021 to April 2024, we find that institutional ownership significantly boosts the premium to net asset value. This effect operates primarily through two channels: reduced market liquidity and increased idiosyncratic return volatility, likely reflecting institutions’ trading activity and informational advantages. The findings highlight how institutional capital serves as a confidence signal in China’s emerging REITs ecosystem. The study contributes to the global REITs literature by offering insights from an emerging market context and provides policy recommendations to guide China’s REITs market development toward greater transparency, diversity, and long-term resilience.