The flow-performance relation in China’s mutual fund market differs from that in developed markets (e.g., the U.S.). We find that investors actively allocate capital to poorly performing funds, generating a negative relation at the bottom of return distribution. These flows are driven mainly by increased purchases rather than reduced redemptions. We then examine the mechanisms behind this anomaly. First, investors act on rational expectations of performance reversals, with this pattern being more pronounced among funds with higher activeness. Second, product differentiation attracts heterogeneous investors when performance is weak. Third, marketing and fund family effects serve as simple signals that amplify inflows. Overall, our study provides new empirical evidence on fund investor behavior and its economic consequences in an emerging market context.

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.

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.

Against the backdrop of potential irrational trading behaviours in financial markets, this study investigates the V-shaped disposition effect in the selling activities of portfolios managed by securities investment funds in China. Utilising quarterly holdings data (2018–2024) of Chinese securities investment funds, alongside daily turnover rates and closing prices of their fund-heavy stocks listed in China's A-share market, a Fama-MacBeth regression analysis is conducted. The empirical results provide robust evidence of a significant V-shaped disposition effect in these fund investments, primarily driven by speculative trading. Moreover, this effect significantly and positively predicts future stock returns of Chinese A-shares. This study enhances understanding of institutional investors' trading behaviours—particularly mutual funds in China—and their decision-making processes in financial markets.

随着监管部门与社会各界对于企业的ESG表现日益关注，本文考察拟上市企业（特别是IPO预期成功率较低的企业）是否有动机通过强化其ESG表现，从而增强其IPO成功概率。本文基于大语言模型对拟上市公司招股说明书所呈现的ESG绩效进行量化评估，并系统考察企业IPO预期成功率、招股说明书ESG绩效与IPO最终成功率之间的互动关系。研究发现：（1）企业IPO预期成功率越低，该企业越可能在其招股说明书中展现出较佳的ESG绩效；（2）企业的ESG绩效强化行为显著提升了其IPO通过概率。这一效应在证券监管部门更为关注企业社会责任时以及在高污染行业中更为显著。进一步分析表明，对于IPO预期成功率较低的企业，其招股说明书中的ESG表现无法有效预测其上市后的ESG绩效，这表明监管部门仍需警惕此类企业“漂绿”上市的风险。本文研究结论对于证券监管部门和投资者都具有重要的决策参考价值。

Using a novel and dynamic measure of fund-level herding that captures the tendency of a fund manager to imitate the trading decisions of the institutional crowd based on a sample of 3490 mutual funds in China for 21 years between 2003 and 2023, we find that funds with higher herding tendencies face significantly elevated delisting risks. Additionally, herding behavior is associated with shorter fund lifespans, smaller asset bases, and higher portfolio manager turnover rates. These results remain robust after employing a battery of methods to address endogeneity concerns. Collectively, our study demonstrates that herding substantially amplifies funds’ running risks.

在全球可持续投资理念日益强化的背景下，ESG披露逐步成为影响资本配置的重要因素。私募股权机构作为非公开市场的重要中介，其ESG披露行为是否会影响募资表现？本文以2010-2023年中国资产管理规模领先的961家私募股权机构为研究样本，研究其ESG披露对募资表现的影响及作用机制。研究发现，私募股权机构披露ESG报告可显著提升募资成功率与募资规模，该作用主要通过“声誉补偿”与“资本适配”机制实现。此外，开展全球化业务与公众环境关注度较高地区的机构，ESG披露的募资促进效应更为显著。进一步分析表明，正式的ESG报告披露相比于非正式ESG信息提及对募资表现推动作用更强。同时，项目层面结果表明，ESG披露不仅提升募资能力，也对应着更优的投资项目退出表现。本研究为评估ESG披露在非公开市场的有效性提供了经验证据，并为私募股权行业ESG规范化与绿色金融发展提供参考。

In the realm of financial stability, accurate credit default discrimination models are crucial for policy-making and risk management. This paper introduces a robust model that enhances credit default discrimination through a sophisticated integration of a filter-wrapper feature selection strategy, instance selection, and an updated version of majority voting. We present a novel approach that combines individual and ensemble classifiers, rigorously tested on datasets from Chinese listed companies and the German credit market. The results highlight significant improvements over traditional models, offering policymakers and financial institutions a more reliable tool for assessing credit risks. The paper not only demonstrates the effectiveness of our model through extensive comparisons but also discusses its implications for regulatory practices and the potential for adoption in broader financial applications.

Traditional decision tree models, which rely exclusively on numerical variables, often encounter difficulties in handling high-dimensional data and fail to effectively incorporate textual information. To address these limitations, we propose the Integrated Multivariate Segmentation Tree (IMST), a comprehensive framework designed to enhance credit evaluation for small and medium-sized enterprises (SMEs) by integrating financial data with textual sources. The methodology comprises three core stages: (1) transforming textual data into numerical matrices through matrix factorization; (2) selecting salient financial features using Lasso regression; and (3) constructing a multivariate segmentation tree based on the Gini index or Entropy, with weakest-link pruning applied to regulate model complexity. Experimental results derived from a dataset of 1,428 Chinese SMEs demonstrate that IMST achieves an accuracy of 88.9%, surpassing baseline decision trees (87.4%) as well as conventional models such as logistic regression and support vector machines (SVM). Furthermore, the proposed model exhibits superior interpretability and computational efficiency, featuring a more streamlined architecture and enhanced risk detection capabilities.