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.

This study investigates the impact of RegTech adoption in the M&A regulatory review process on deal performance. Leveraging the staggered implementation of the SOEs Online Supervision System (SOSS) by China’s State-Owned Assets Supervision and Administration Commission (SASAC) across its central and 31 provincial offices from 2018 to 2021, we find that SOSS directly enhances SASAC’s decision-making efficiency and improves its capacity to screen and approve higher-quality M&A deals. More importantly, SOE-led M&A transactions exhibit higher announcement returns as well as improved long-run stock and operating performance following the system’s implementation. The positive impact of SOSS is more pronounced for acquirers with stronger technological infrastructure, in transactions characterized by low transparency and weak governance, and in provinces with more stringent external scrutiny. Overall, by addressing regulator-firm information asymmetry and reinforcing managerial accountability, SOSS improves regulatory effectiveness in overseeing major investment activities among SOEs.

This article examines the rapid growth of Real-World Asset (RWA) tokenisation in Asia, focusing on Hong Kong as an emerging regional hub. It analyses three sectoral case studies in renewable energy, real estate, and financial instruments to illustrate the practical applications, market implications, and regulatory challenges of RWA projects. As of September 2025, the global RWA market reached an estimated value of $30.91 billion and is projected to grow into a trillion-dollar market within the next decade. The article highlights Asia’s proactive regulatory initiatives aimed at developing clear tokenisation standards and promoting the sustainable and responsible growth of the virtual asset sector. Supported by regulatory sandboxes and institutional participation in leading financial centres such as Hong Kong and Singapore, the region has become a focal point of innovation in asset tokenisation. Following the introduction, Section 2 reviews the latest developments in RWA as a fast-emerging area of financial and legal practice. Section 3 presents three case studies, while Section 4 provides practical guidance for asset owners and investors. Section 5 discusses key regulatory models and the overseas expansion of Chinese enterprises through digital assets tokenisation, and Section 6 concludes with implications for regulators, investors, and policymakers.

Utilizing microevaluation data on the extent to which firms advance the achievement of the UN’s Sustainable Development Goals (SDGs) provided by Robeco, this paper examines the influence of corporate sustainability on stock price performance and its underlying economic mechanisms. The empirical results suggest that firms’ sustainability has a significant negative effect on excess returns, particularly the contribution of firms to the social dimension of sustainability. Firms’ SDG performance can alleviate financing constraints and reduce financial risk, but it does not significantly enhance financial performance, leading to market capital outflows from high SDG-performing firms, especially from individual investors. Furthermore, our results suggest that high SDG-performing firms are undervalued and do not increase the information content in their stock prices, which may be the main reason for the negative effect of SDG performance. We also conduct a series of heterogeneity tests, which show that firms from regions with high environmental regulatory intensity and less economic development, as well as heavily polluting firms and firms with poorer information environments, experience greater negative effects. These findings have implications for investors to properly understand corporate sustainability and for regulators to promote the development of a low-carbon economy.

This study aims to examine the causal effect of carbon regulatory risk on corporate bond yield spreads in emerging markets through empirical analysis. Exploiting China's commitment to peak CO2 emissions before 2030 and achieve carbon neutrality before 2060 as an exogenous shock to an unexpected increase in carbon regulatory risk, we perform a difference-in-difference-in-differences (DDD) strategy. We find that exposure to carbon regulatory risk leads to an increase in bond yield spreads for carbon-intensive firms located in regions with stricter regulatory enforcement. This positive relationship is more pronounced for firms with financing constraints, belonging to more competitive industries, and located in regions with a high marketization process. We further identify that higher earnings uncertainty and increased investor attention serve as two mechanisms by which carbon regulatory risk influences the yield spreads of corporate bonds. Moreover, the spread decomposition reveals that the rise in bond yield spreads after an increase in carbon regulatory risk is primarily driven by the rise in default risk rather than the rise in liquidity risk. Overall, our findings highlight the importance of considering carbon regulatory risk exposure in financial markets, especially in developing economies like China.

The Central Environmental Protection Inspector (CEPI) is a critical regulatory measure in China aimed at improving ecological quality. From a compliance cost perspective, we examine the impact of the CEPI on corporate environmental governance. The findings reveal an asymmetry in the CEPI's influence: it significantly promotes environmental governance efforts on the non-production side of enterprises, while having no substantial effect on the production side. Additionally, government environmental subsidies do not provide a resource incentive in the process of the CEPI influencing corporate environmental governance. However, local environmental governance pressure mitigates this asymmetry, leading the CEPI to significantly enhance environmental governance on both the production and non-production sides. Further analysis shows that under the synergistic effect of local environmental governance pressure, the CEPI encourages state-owned enterprises to focus on environmental governance on the production side, while non-state-owned enterprises tend to focus on the non-production side. Moreover, political connections reduce the positive impact of the CEPI on production costs under local environmental governance pressure. Finally, the CEPI also significantly encourages enterprises to expand their production scale. These findings offer valuable insights for refining the CEPI system to better promote corporate environmental governance.

Environmental disclosure in emerging markets remains poorly understood, despite its critical role in sustainability governance. Here, we analyze 42,129 firm-year environmental disclosures from 4,571 Chinese listed firms (2008-2022) using machine learning techniques to characterize disclosure patterns and regulatory responses. We show that increased disclosure volume primarily comprises boilerplate content rather than material information. Cross-sectional analyses reveal systematic variations across industries, with manufacturing and high-pollution sectors exhibiting more comprehensive disclosures than consumer and technology sectors. Notably, regional rankings in environmental disclosure volume do not align with local economic development levels. Through examination of staggered regulatory implementation, we demonstrate that market-based mechanisms generate more substantive disclosures compared to command-and-control approaches. These results provide empirical evidence that firms strategically manage environmental disclosures in response to institutional pressures. Our findings have important implications for regulatory design in emerging markets and advance understanding of voluntary disclosure mechanisms in sustainability governance.

China's tech companies are making waves with their recent achievements, including a "trifold" phone from Huawei and the revolutionary AI reasoning model from DeepSeek. Much discussion has centered on the founders of these companies and their ability to gain an edge on American rivals. But what is less appreciated or understood among foreign analysts of China’s tech giants is the role that innovation and transformation in corporate governance and organizational structure has played in these companies’ successes. Moreover, there are unique aspects of these companies from a corporate governance perspective that are not commonly seen in tech companies in other parts of the world or even within China itself. For instance, Huawei is 99% employee owned, while Alibaba is primarily governed by an "Alibaba Partnership." These unique corporate structures have arisen due to several factors, including the rapid changes to China’s regulatory landscape over the past three decades, distinct characteristics of Chinese business culture, geopolitical tensions and preoccupations with national security, and the “socialism with Chinese characteristics” model. In this article I overview some of the more distinctive corporate governance mechanisms of four Chinese tech companies: Huawei, Alibaba, Bytedance, and DeepSeek, and explain why these structures were adopted.

Shill bidding, the use of non-genuine bids to inflate prices, undermines auction market integrity. Exploiting China’s online judicial housing auctions as a laboratory, we identify 2% of participants as suspected shill bidders, affecting 8% of auctions. They raise price premium by 14.3%, causing an annual deadweight loss of ¥570 million for homebuyers. Mechanism analysis reveals they create bidding momentum and intensify competition. We establish causality using a difference-in-differences analysis leveraging a 2017 regulatory intervention and an instrumental variable approach using dishonest judgment debtors. These findings offer actionable insights for policymakers and auction platforms to combat fraud in online high-stake auctions.

We find evidence that firms engage in earnings management to potentially diminish environmental regulatory attention after the implementation of an automatic air pollutant monitoring system in China. Polluting firms increase their use of discretionary accruals and reduce the informativeness of earnings, compared to non-polluting firms. Polluting firms that are larger, more profitable, located near monitoring stations, and situated in less market-oriented regions exhibit heightened earnings management, consistent with the greater environmental regulatory exposure these firms face. The behavior is moderated by stronger customer-supplier relationships and lower market competition, when the cost of earnings management is higher. Our findings highlight the conflict between environmental and governance issues.