The global macroeconomic leverage ratios have witnessed a sustained upward trend in recent years, drawing renewed international attention to high debt levels and financial instability. According to BIS statistics, from March 2009 to December 2023, the non-financial corporate leverage ratio across G20 nations increased from 79.0% to 91.7%, while China's ratio surged more markedly from 99.4% to 134.7% during the same period. Particularly noteworthy is that China's non-financial corporate leverage ratio once approached 150% around 2015. As China's economy transitions into the “New Normal”, shifting development focus from rapid growth to quality enhancement has become imperative for sustaining healthy economic development. However, persistent corporate debt accumulation and financial system instability have significantly hindered this economic transformation. This context raises a crucial practical question: how to achieve effective deleveraging with minimal economic disruption while ensuring domestic financial stability, thereby establishing a robust foundation for industrial restructuring and upgrading. This is an urgent policy challenge demanding thorough exploration and innovative solutions.
Particularly under the current conditions where China's economy is facing “Triple Pressure” and “Three Periods Overlapping”, the profitability of the corporate sector is under stress. This has led some enterprises to increasingly rely on debt to maintain their cash flow balance and business operations, thus exhibiting the characteristics of firm type transformation revealed in Minsky's theory. Discussing the endogenous combination of deleveraging policies and macro policies based on Minsky's theory is also a significant theoretical issue that requires ongoing and in-depth study. In light of this, this paper constructs a DSGE model with “Ponzi Financing”, introducing heterogeneous entrepreneurial sectors with different financing characteristics and a financial sector with a “dual structure”. This model is used to systematically analyze the stabilizing effects under the application of deleveraging policies, macro-prudential policies, and their combined use.
The analysis results of this paper indicate that: (1) Structural deleveraging policies can play a good stabilizing role, but in the process of reducing the financing expansion capabilities of Ponzi enterprises, they need to be combined with appropriate macroprudential policies to achieve overall stability of the economy and financial system. (2) With the support of macroprudential policies, there is a relatively optimal implementation scheme for structural deleveraging policies, which involves first reducing the debt ratio of Ponzi enterprises to a reasonable level, then controlling their financing expansion capabilities, and finally promoting a return to the real economy. (3) The policy authority has different policy spaces at different stages of deleveraging: During the leverage reduction stage, policy adjustments need to be carefully balanced to avoid causing significant economic fluctuations; In the leverage control stage, the use of macro-prudential policies can be more flexible, and the policy space correspondingly increases; In the stage of shifting from “financial to real”, the policy space will be fully released, and the flexibility of policy implementation will be greatly enhanced.
The policy implications of the conclusions of this paper are: Although the main sources of economic and financial instability are the excessive indebtedness and investment by entrepreneurs and bankers chasing profits, and a reduction in investment is a crucial trigger for the “Minsky Moment”, this does not imply that loosening financing constraints can avoid potential economic and financial risks. On the contrary, arbitrarily easing financing constraints may lead to significant resource misallocation, thereby exacerbating the vulnerability of the economic and financial system. Therefore, loosening financing constraints is not a viable solution to the “Minsky Moment”. Theoretically, if we view the “Minsky Moment” as a deleveraging process accompanied by significant negative impacts, then policymakers should adopt differentiated strategies for high-debt entities, aiming to complete the deleveraging process with minimal negative impact. From the perspective of Minsky's theory, deleveraging should include at least two aspects: reducing the debt level of Ponzi financing enterprises and controlling their financing expansion capability. If policies can separately regulate the debt level and financing expansion capability of micro-agents, rather than simply prohibiting or reducing lending outright, the relevant market entities may be able to choose a more reasonable path to complete the deleveraging process at a relatively lower cost.

Recently, the scale of global debt has been continuously expanding. The fluctuations in default risk within local markets can spread rapidly across different markets and industries along trade, investment, and credit channels, posing potential threats to the stable development of various countries. In response, the Central Financial Work Conference held in October 2023 pointed out the necessity to “establish a long-term mechanism to prevent and defuse local debt risks” and to “prevent the cross-region, cross-market and cross-border transmission of risks”. In this context, it is of great academic value and practical significance to study the co-movement and diversification effect of international default risk in cross-market and cross-industry transmission. It not only contributes to identifying the co-movements of default risks across different markets, but also helps to find the weak links with large default risk exposure and vulnerability to external shocks, thus providing policy implications for realizing China's financial stability and high-quality economic development.
Based on the asymmetric breakpoint method, this paper adopts the default probabilities of corporate sectors in 23 countries (or regions) and 11 industries from 1995 to 2022 to construct global default risk networks, and then we capture the effects of default risk co-movement and default risk diversification respectively. The default probability data we use come from the Credit Research Initiative of the Asian Institute of Digital Finance, National University of Singapore (NUS-CRI).
Firstly, this paper constructs a static default risk network and studies the default risk contagion at country (or region) level. The results suggest that the Chinese mainland demonstrates strong resilience to externally transmitted default risk. At the same time, the default risk of the Chinese mainland's corporate sector shows a low correlation with the international market, and its risk dynamic is significantly influenced by domestic factors. Furthermore, this paper calculates the net relative centrality of each country (or region), revealing that the top three markets (Hong Kong SAR, China, Singapore, and the United Kingdom) all have international financial centers, and the financial sector may be an important hub for cross-market contagion of default risk.
Next, this paper uses industry-level default probability to measure the cross-market contagion of default risk within each industry and the cross-industry contagion of default risk within each country (or region). We find that the positive co-movement effect is very significant in financial industry. Hence, financial sector is the key to breaking the chain of risk contagion. Nevertheless, the cross-market risk dynamics of utilities and consumer staples show a negative diversification effect, indicating these industries' potential value in international portfolio risk diversification.
Furthermore, this paper adopts the rolling estimation method to capture the dynamic evolution of the default risk network from February 1996 to June 2022. The results show that the impact of external shocks on positive and negative connection networks is asymmetric. Moreover, the trend in the density of positive connection network mirrors the trend in the number of global corporate defaults, which indicates that default events may be an important force driving the contagion of default risks.
In addition, this paper studies the default risk contagion under three global crisis events, namely Global Financial Crisis, European Sovereign Debt Crisis and the COVID-19 pandemic crisis. We find that the strength of positive co-movement of default risk rises significantly during the events mentioned above. The research on industry high risk period indicates that the rising risks in real estate sector in the Chinese mainland will increase risk co-movement among major domestic industries, but do not cause risk spillover to international markets. In contrast, a surge in risk of the U.S. real estate sector could trigger a positive linkage of global default risk. Further analysis of the high-risk period in the U.S. information technology industry shows that the negative impact of the risk in the U.S. information technology industry on the Chinese mainland is relatively limited.
Finally, this paper proposes several policy recommendations to guard against the default risk contagion. First, the default risk of financial industry should be closely monitored, and the national financial risk early warning system should be further improved. Second, policymakers should keep a wary eye on overseas risks and pay close attention to the fluctuation of default risks in East Asia. Third, regulators should make emergency response plans for domestic default events and ensure systemic risk in China under control.

Illegal fundraising, which refers to the behavior of absorbing funds from the general public by promising repayment of principal and interest or offering other investment returns without the permission of financial regulatory authorities or in violation of the financial supervisory regulations of the government, have long existed in China and severely disrupted the order of financial market. In recent years, the illegal fundraising activities have displayed a rising trend and the characteristics of large sums of money involved, numerous victims and widespread geographical impact became increasingly obvious. Therefore, intervening and cracking down on illegal fundraising activities, which have received considerable attention from policymakers and academics, is an important measure to prevent and resolve financial risks and maintain financial security.
Theoretically, the relationship of the rise of fintech on illegal fundraising risks is still ambiguous. On the one hand, financial crimes relying on information technology have greater concealment, higher propagation efficiency and wider scope, indicating that fintech development may exacerbate the illegal fund-raising risks. On the other hand, the advent of fintech can alleviate credit constraints by solving the information asymmetry with the help of technological innovation such as big data and machine learning algorithms and also improve households' financial knowledge. The vital role played by fintech in promoting financial inclusion can reduce the risks of illegal fundraising.
To empirically test these two competing hypotheses, this paper extracts data of criminal court cases on illegal fundraising from 286 prefecture-level and above cities in China from 2014 to 2021, as well as China Household Finance Survey data in 2015 to examine the impact of fintech development on illegal fundraising risks and the potential mechanism, by applying machine-learning techniques to identify the number of fintech patents in each prefecture. Specifically, we collected a total of 33,999 illegal fundraising court cases from 2014 to 2021, extracting useful information of each case such as the number of investors involved, the amount of money invested. The case-level data are aggregated to the prefectural-level and the density of cases and defendants involved are employed to measure the illegal fundraising risks. We use the number of fintech-related patents normalized by total number of authorized patents to proxy for fintech development. The estimation results of the two-way fixed effects model show that the development of fintech significantly reduces the number of illegal fundraising cases and defendants per million population. This negative effect remains robust after addressing endogeneity concerns through the use of Difference-in-Difference estimation and instrumental variable techniques, alternative variable measurements, sample refinements and other estimating methods.
Next, we explore the cross-sectional heterogeneity of our baseline results and investigate the effects of fintech on household behavior based on CHFS data to substantiate the channels through which fintech affects financial crimes. The results illustrate that the development of fintech patents related to data analysis have significantly negative effects on illegal fundraising risks and this effect is more pronounced for prefectures with lower credit availability. It is also shown that households residing in regions with higher density of fintech patents tend to have stronger financial literacy and the effects of fintech on reducing illegal fundraising risks are greater for households with poor financial knowledge. All these results demonstrate that the working channel through which fintech exerts its negative impact on illegal fundraising lies in that fintech development improves financial inclusion and alleviates the degree of households' credit constraints through data analysis technology innovation, as well as accumulates their financial knowledge, thereby reducing illegal fundraising risks.
The causal evidence provided in our paper on using fintech to prevent financial crimes not only expands the emerging research on the economic effects of fintech development and the growing literature on the determinants of illegal fundraising risks, but also provides a theoretical basis for the fundamental solution to combat illegal fundraising by adhering to the principle of prevention first by eliminating economic incentives, blocking as a supplement. From the perspective of policy prescriptions, our study implies that resolving financial risks and serving real economic growth should mainly rely on promoting high-quality financial development and improving financial inclusion through the deepening of the structural reform of the financial supply side.

As the largest exporter in the world, China currently still has as much as 54% of its “product-country” export as zero, indicating that China still has plenty of scope at that level to explore new trading partners at the product level. For example, in 2019, 670 out of the 5196 products produced and exported by China failed to be exported to the United States (such as passenger boarding bridges for airports, tank trailers, radar display tubes, etc.), and similarly 1234, 1146, 1024, 954, 879, and 870 products failed to be exported to Italy, France, the United Kingdom, Germany, Japan, and Canada, respectively. The traditional constant elastic trade theory, which explains ‘zero trade' primarily with fixed trade costs, ignores the important role of variable trade costs. China is the only country to have all industrial categories in the Industrial Classification of the United Nations. In order to better characterize the heterogeneity at the product level, this paper introduces the Almost Ideal Demand System (AIDS) preference into the international trade framework of firm heterogeneity and derives the Almost Ideal gravity equation that embodies heterogeneous price and income elasticity, which can theoretically explain bilateral zero trade and reveal the specific quantitative estimation method. Based on this model, this paper uses the data of China's export trade to 187 countries and 5196 categories of products from 2015 to 2019 to measure the distance how far export enterprises in each product market from opening a specific potential market, that is, the latent trade bias is used to measure the gap between the latent trade share of zero-trading countries and their friction-free trade hare.
This paper yields the following findings. (1) This paper uses latent trade estimated from a theoretical model to measure the distance between countries from no trade to trade. It also uses the interaction of idiosyncratic price and income elasticities with variable and fixed costs to explain bilateral zero trade. Empirical results show that the higher the per capita output (a proxy for quality) of China's exported products, the lower the hindering impact of bilateral trade costs (distance, tariffs, or market entry costs) or trade frictions on latent trade shares, and the lower the promoting impact of trade agreements or common languages on latent trade shares. At the same time, countries with higher income levels are more inclined to import products with higher productivity from China. Thus, China's exports have significant heterogeneous characteristics of product prices and income elasticities at an extensive margin. (2) The variance decomposition of latent trade bias shows that changes in bilateral variable trade costs (the sum of tariffs and distance costs) can explain 26% of zero trade deviations, which is higher than the explanatory power of fixed trade costs. Compared to capital-intensive industries, the impact of tariffs, distance, or trade agreement factors on zero trade is more significant in labor-intensive industries, whereas the income effect is less significant in labor-intensive industries. Conversely, high-tech capital-intensive industries are more affected by trade frictions and less affected by entry costs. (3) The results of the counterfactual policy simulation show that, compared to the reduction or subsidy of fixed costs, the reduction or subsidy of variable costs, especially distance costs, can increase the possibility of establishing new trading partners to a greater extent, and this trade promotion effect is stronger for traditional comparative advantage industries, products with relatively low per capita output, or trading partner countries, especially RCEP countries.
This paper has the following policy implications. (1) improve quality standards and regulatory systems to promote technological innovation and industrial upgrading of China's manufacturing industry, thereby cultivating new foreign trade momentum in emerging markets. (2) strengthen the construction of transportation infrastructure and logistics support facilities, continuously reduce variable trade costs, and continue to promote China's manufacturing industry in accessing new overseas markets with a higher level of openness. (3) for product markets with different industry characteristics, adopt differentiated foreign trade policies to promote stability and improve quality, first rely on traditional comparative advantage industries to open up new markets, and then gradually expand emerging strategic industries. (4) The government can identify small-scale markets with greater potential based on the product markets of different destination countries and refer to the model in this article to provide priority support, deepen trade cooperation with small-scale market countries, and guide Chinese enterprises to explore emerging markets. (5) improve the resilience of China's manufacturing supply chains, strengthen the diversified layout of the international market, and promote the development of new formats and trade models, to effectively deal with the uncertainties caused by trade frictions.
The marginal contributions are as follows. (1) Theoretically, this paper provides a basic framework and a policy evaluation tool to analyze the impact of variable trade costs on the extensive margin of trade by building an AIDS structural gravity model at the product level. At the same time, this article introduces the impact of “trade friction” as a new type of trade barrier, which could effectively describe the various barriers facing China's current exports. That is, this paper has important references and significance in promoting research on China's zero-trade issues. (2) Empirically, this article expands and quantifies the theoretical concept of “Latent Trade” in the literature at the product level and uses Tobit's structural regression and instrumental variable methods to estimate the model. It also empirically tests and compares the marginal impact on “zero trade” of Chinese product exports of variable trade costs (distance and tariff), fixed trade costs (market entry costs), trade frictions (no entry), and other factors. (3) In terms of policy implications, based on heterogeneity price and income elasticity at the product level, combined with the differentiated characteristics of China's export products, this article quantitatively evaluates the latent effects of China's extended marginal trade policy from the perspective of variable trade costs and fixed trade costs in a structural form. This paper focuses on bilateral zero trade at the product level. In addition, it quantifies the possibility of “zero to one conversion” through latent trade bias, that is, the difference between latent trade and frictionless trade share.

Supply chain security and smoothness is the key to strengthening modernization of industry chains and supply chains. However, there is still significant market segmentation in the process of building a unified domestic market, which hinders the free cross-regional circulation of resource factors. The Guidelines of the Central Committee of the Communist Party of China and the State Council on Accelerating the Construction of a National Unified Market released in 2022 set out the overall arrangements for this endeavor. The Guidelines emphasize that it is importance to urgently accelerate the construction of a national unified market, break down local protectionism and market barriers, ease key bottlenecks that hinder economic flows, and promote more extensively smooth flows of commodities, factors of production, and resources. Therefore, with regard to building a unified domestic market and upgrading the modernization of the industry chain and supply chain, understanding the impact of market segmentation on the two chains has important implications.
This paper empirically examines the impact of interregional market segmentation on the construction firms' cross-regional supply chains by manually organizing data on major suppliers of Chinese listed firms from 2007-2019, and constructing a paired sample at the firm-supplier's province-year level. The results show that the more severe the market segmentation between regions, the lower the firms' purchasing proportion in paired regions, and the market segmentation hinders the construction of firms' cross-regional supply chain. We conduct a variety of tests on the endogeneity problem, all of which confirm the robustness of the conclusions. Moreover, the impact of market segmentation on firms' cross-regional supply chain is more pronounced for firms in competitive industries and firms with higher product uniqueness. We then examine the mechanisms and find that market segmentation can increase transaction costs between firms and cross-regional suppliers, increase the uncertainty in procurement lead time and the supply-demand imbalance between upstream and downstream firms, thereby hindering the construction of cross-regional supply chain. Economic consequence tests show that the reduction in cross-regional procurement by firms due to market segmentation increases firms' operating costs and reduces firms' profitability and total factor productivity. Finally, we examine the measures taken by firms to cope with market segmentation and find that improving vertical integration, utilizing digital technology, and with the help of cross-regional chamber of commerce can effectively weaken the negative impact of market segmentation on firms' cross-regional supply chain.
This paper provides a beneficial supplement to existing literature in two ways. First, this paper enriches the study of market segmentation and micro-firm behavior by expanding the research perspective from the firm to the supply chain. Existing studies on how market segmentation affects the economic activities of micro firms have mainly analyzed the import and export trade, vertical integration, innovation activities, and production efficiency of firms, and less involved in firms' supply chains. This paper explores the impact of market segmentation among local governments on cross-regional cooperation among upstream and downstream of supply chains, which combines market segmentation with corporate supply chain relationships, and expands the understanding of the economic consequences of market segmentation. Second, this paper enriches the related research on the influencing factors of corporate supplier selection. As an important part of supply chain management, supplier selection has received widespread attention, and most of the existing related studies are based on management to discuss the methods and criteria of supplier selection. From the perspective of economics, although some studies have mentioned that institutional risk affects firms' supplier selection decisions, most of them focus on inter-country institutional risk. Unlike the existing studies, this paper focuses on the impact of institutional risk across regions within a country on firms' supplier selection, complementing related research on the firms' supply chain management.
This paper identifies the important role of market segmentation on firms' cross-regional supply chain, providing policy inspiration for accelerating the construction of a unified domestic market and improving the modernization of supply chain. For local government departments, it is necessary to strictly implement the important spirit of the CPC Central Committee and the State Council on accelerating the construction of a national unified market, balance the relationship between the government and the market through institutional innovation, break down the division between regions, build a highly efficient and standardized, fair competition and fully open national unified market, promote the free flow of commodity factors, and provide a fair market environment for firms to build cross-regional supply chains. In addition, local government departments should also actively help with the development of cross-regional chamber of commerce, give full play to their proactivity in serving the real economy, and facilitate the construction of firms' cross-regional supply chains as well as engaging in cross-regional trade activities. For firms, it is necessary to promote the full integration of digitalization and supply chains, use digital technology to break through regional boundaries and optimize the supply chain structure. Firms should integrate digital technology into various stages according to their own production and operation needs, including procurement, inventory management, order tracking and so on, which can improve the organization efficiency and coordination between upstream and downstream, and enhance the supply chain competitiveness. Additionally, firms should actively establish and join cross-regional chamber of commerce, and leverage this important form to break through market segmentation constraints and improve supply chain efficiency.

In the 1990s, the socialist market economy system with Chinese characteristics was gradually established, and reforms in the fiscal and financial sectors continued to deepen, leading to changes in the ways and methods that local governments used to promote economic and social development. A prominent manifestation was that local governments no longer focused solely on developing local state-owned enterprises but instead prioritized in attracting non-local enterprise investment. Development models such as the “Southern Jiangsu Model” emerged, with regions beginning to compete to attract high-quality enterprise resources through infrastructure construction. Since 2008, with the support of proactive fiscal policies and loose monetary policies, local governments have relied on local government financing vehicles (LGFVs) to raise funds for infrastructure construction, providing strong financial support for improving the investment environment and promoting regional economic development. At the same time, local governments' use of LGFVs to incur debt formed a development model different from the past, characterized by the embedding of local government debt into investment attraction competition strategies, making it an important tool for local governments to implement development strategies. As local government debt acquired a competitive attribute, local governments have strong incentives to engage in correlated borrowing, leading to a peer effect in local government borrowing and resulting in disorderly expansion and risk accumulation of local government debt. Moreover, regions with higher debt often transfer debt repayment pressures to market entities through various means, crowding out social investment, which contradicts the original intent of development models like the “Southern Jiangsu Model”. Given this, it is necessary to deeply study the intrinsic relationship between local government correlated borrowing and non-local enterprise investment to provide references for achieving a long-term balance between stable growth and risk prevention.
This paper measures the level of local government correlated borrowing and, based on this, studies its impact on non-local enterprise investment and its mechanisms, while also analyzing the limitations of local government correlated borrowing from multiple dimensions. The research results show that when a region's level of correlated borrowing is higher compared to other regions, it significantly encourages non-local listed companies to invest locally, aiding in local economic growth. However, whether local government correlated borrowing can promote non-local enterprise investment is influenced by factors such as the use of debt funds, borrowing methods, and debt utilization efficiency. Further research indicates that local government correlated borrowing “crowds in” and “crowds out” non-local enterprise investment through local infrastructure and fiscal effort, with the “crowding-in effect” being stronger. The analysis of the limitations of local government correlated borrowing shows that its positive effects on non-local enterprise investment and local economic development have a threshold. Once local government debt exceeds this threshold, the direction of correlated borrowing's impact on non-local enterprise investment and local economic development reverses, turning negative.
The marginal contributions of this paper include: first, from the perspective of investment attraction, it deeply analyzes local government correlated borrowing behavior and finds that such borrowing “crowds in” or “crowds out” non-local capital through infrastructure levels and fiscal effort, with the “crowding-in effect” being stronger. Second, it thoroughly analyzes the limitations of local government correlated borrowing from multiple dimensions. This paper finds that the sustainability of the investment attraction effect of local government correlated borrowing is influenced by factors such as debt scale, use of debt funds, and utilization efficiency, and excessive reliance on local government debt to attract investment will prove counterproductive. Third, drawing on existing literature, this paper scientifically measures the level of local government correlated borrowing, providing a foundation for further in-depth research on local government correlated borrowing behavior. Fourth, from multiple perspectives, this paper examines the heterogeneity of the impact of local government correlated borrowing on non-local enterprise investment, providing evidence and references for scientifically evaluating local government correlated borrowing behavior and promoting continuous improvement of government investment and financing mechanisms.

The issue of financial asset allocation of Chinese corporations has drawn great attention from both the government and the academia. Attracted by high profit margins, many companies have chosen to allocate financial assets, aiming to promote business development through such activities. On one hand, the government must guard against the risks of “shifting focus from the real to the virtual economy” brought by corporate financial asset allocation, but on the other hand, it should guide financial markets to foster enterprise growth, thereby achieving the goal of “utilizing the virtual to support the real economy”. As a direct reflection of the market's evaluation of enterprise value, stock prices reflect investors' assessments and expectations of corporate behavior. Consequently, changes in a company's asset allocation can impact the long-term risk of stock price volatility. Against this background, an issue that urgently needs to be addressed is, accurately understanding the impact of corporate financial asset allocation on long-term risk of stock price volatility from the perspective of investor expectations. A deep understanding of this issue is thus essential for effectively regulating and mitigating the risks associated with corporate financial asset allocation, to create a positive interaction between financial markets and the real economy.
Building on the classic model of Grossman and Stiglitz (1980), this paper incorporates corporate financial asset allocation, investors' expectations of corporate financial asset allocation and their investment decisions into a unified theoretical framework, so as to analyze the impact of corporate financial asset allocation on the risk of long-term risk of stock price volatility. A key assumption is that investors have differentiated expectations regarding corporate financial asset allocation: investors with optimistic (pessimistic) expectations believe that an increase in the level of corporate financial asset allocation will enhance (reduce) the firm's stock value and its stability. Through mathematical deductions, propositions are derived, testable hypotheses are formulated and then empirically tested using data from Chinese listed companies from 2008 to 2022. We found that the impact of corporate financial asset allocation on long-term risk of stock price volatility exhibits “pro-cyclicality”: in markets dominated by investors with optimistic (pessimistic) expectations about corporate financial asset allocation, corporate financial asset allocation reduces (increases) the long-term risk of stock price volatility. Mechanism analysis shows that corporate financial asset allocation can alleviate the long-term risk of stock price volatility by clarifying investor expectations and by reducing overconfidence of investors, but it may increase the long-term risk of stock price volatility by curbing the development of enterprises' main businesses, and thus increase the pessimistic expectations of investors on corporate financial asset allocation.
Based on these findings, several policy recommendations are proposed. Firstly, at the investor level, investors should keep an active eye on the information about corporate financial asset allocation, correctly view the behavior of corporate financial asset allocation, and enhance their financial literacy. This helps avoid forming irrationally pessimistic expectations about financial asset allocation by some investors, thereby reducing the potential risks arising from financial asset allocation. Secondly, at the corporate level, companies should reasonably allocate financial assets, harness the positive role of financial assets, and achieve a win-win situation where financial services support the real economy. For companies with poor operating conditions, more caution should be exercised in dealing with the risks that financial asset allocation may bring about under the influence of pessimistic investor expectations, in order to prevent further deterioration of their capital market performance. Finally, at the regulatory level, regulatory authorities could refer to market sentiment indicators and adopt corresponding constraints to implement “pre-emptive regulation” from the perspective of investor expectations, preventing the increased long-term risk of stock price volatility under the influence of strong pessimistic expectations. Regulatory authorities should pay close attention to the changes in financial market sentiment, remain vigilant against the “pro-cyclicality” nature of financial asset allocation, and guard against the negative effects of financial asset allocation during economic downturns, particularly when irrationally pessimistic expectations dominate the market.
Marginal contributions of this paper are multifold. Firstly, this paper builds up a theoretical model from the investors' perspective, incorporating their differentiated expectations regarding corporate financial asset allocation, which allows for a more accurate modelling of the irrational behavior in the stock market. Secondly, it innovatively proposes that corporate financial asset allocation, by changing the asset structure, affects the precision of the information set relied upon by investors in their decision-making, thereby helping to mitigate the degree of investor overconfidence. Thirdly, it considers the signaling effect of financial asset allocation. Corporate financial asset allocation can clarify investor expectation, which in turn influences the long-term risk of stock price volatility. Finally, it finds that the impact of corporate financial asset allocation on the long-term risk of stock price volatility has a nature of “pro-cyclicality”, which helps provide valuable insights for regulatory authorities in implementing “pre-emptive regulation” of corporate financial asset allocation behaviors.

Preventing risks is a permanent theme in China's financial work. In particular, financial risk prevention and control must emphasize debt risk management, as debt risk is contagious and prone to triggering chain reactions, which would increase the likelihood of financial crises and give rise to systemic financial risks. As a pivotal component of China's capital markets, the bond market has assumed an increasingly critical role in debt risk containment. As the world's second-largest bond market, it serves as an irreplaceable institutional mechanism for advancing direct financing ratios, achieving leverage stabilization, and enhancing capital market efficiency. Consequently, investigating how debt risk mitigation frameworks influence corporate bond issuance dynamics and elucidating their transmission mechanisms hold profound implications for reconciling leverage stabilization objectives with systemic risk prevention. The marginal academic contributions and key findings of this study are summarized as follows.
Firstly, we examine the impact of the deleveraging policy on corporate bond issuance, revealing the divergence phenomenon in bond issuance between POEs and SOEs, which enriches the research on the economic consequences of the deleveraging policy. We find that the deleveraging policy significantly reduced the scale of bond issuance by POEs relative to SOEs, thereby exacerbating the bond issuance divergence between POEs and SOEs. Despite the increase in trade credit financing, which plays the role of alternative financing, for both SOEs and POEs, the deleveraging policy ultimately leads to a significant reduction in the scale of investment by both POEs and SOEs.
Secondly, we identify the mechanism of the effect of the deleveraging policy on the divergence of corporate bond issuance. This paper finds that, as a policy targeting SOEs, the deleveraging policy led commercial banks to significantly reduce lending to SOEs, thereby reducing the amount of bank loan financing for SOEs, which stimulated SOEs to increase bond issuance in the bond market to meet the capital gap. On the commercial banks side, they prefer to buy bonds issued by SOEs rather than POEs since the default risk of the latter is much bigger. Moreover, the deleveraging policy reinforced the default risk of bonds issued by POEs and raised issuance costs, thereby reducing the need for POEs to issue bonds.
Our research provides important insights for corporate financing as well as the development of bond markets and high-quality economic development in China.
Firstly, the authorities should take commercial banks as the key to increasing support for bond financing of POEs, who play an important role in stabilizing economic growth, increasing employment, and improving people's livelihoods. But even with many favorable policies, it is still difficult for private enterprises to issue bonds. Since 2021, the net bond financing of POEs has been consistently negative, and the proportion of bond issuance by POEs in the total credit bond issuance has significantly decreased. As the largest institutional investors in China's bond market, commercial banks, whose bond investment scale accounts for about half of the entire bond market, play a pivotal role in boosting bond market activity. Therefore, the authorities should urge commercial banks and other financial institutions to increase their investment in the bonds of POEs, restore the bond market's confidence in private enterprises, and promote the return of private enterprises to the bond market.
Secondly, the bond market should be used as a vehicle to cultivate patient capital and increase support for higher-risk enterprises such as those in the technology innovation sector. Amidst the continuous emergence of uncertain factors and persistent downward macroeconomic pressures, investors' risk expectations have been intensifying. Influenced by various factors, including debt risk prevention and control, investors' risk expectations for bond investments in the bond market have significantly increased. Motivated by risk aversion, investors are more inclined to invest in enterprises and bonds with lower risks, gradually squeezing out those with higher risks from the market. Therefore, the bond market should be used as a lever to cultivate patient capital, promote the development of a "tech version" of the bond market, increase financing support for higher-risk enterprises such as technology innovation enterprises, improve the structure of the bond market, and continuously advance the high-quality development of the bond market in order to drive technological innovation.
Thirdly, we should strengthen our understanding of the impact that negative shocks may have on financial markets and the real economy and address the balance between risk prevention and “stabilizing leverage”. In recent years, uncertainties have increased, and policy changes in major foreign economies have become more frequent and drastic, increasing the probability of negative shocks to China's economy. How to prevent and control systemic risks while promoting the high-quality development of the financial market and the real economy has become an important issue for China. This paper finds that the effect of debt risk prevention policy will be transmitted to the bond market through the bank credit market and will have a negative impact on the bond financing of private enterprises, which will in turn reduce the scale of enterprise investment. Therefore, the government should strengthen the understanding of the negative impact of various internal and external shocks on the financial market and the real economy, reasonably grasp the policy strength, strengthen the coordination between policies, and deal with the balance between risk prevention and “stabilizing leverage” to better promote the high-quality development of the economy.

Strengthening the construction of digital government is an important measure for innovating government governance concepts and methods, forming a new pattern of digital governance, and advancing the modernization of the national governance system and governance capacity. Government service informatization is the foundation and prerequisite for building a digital government, and it is also an important component of digital government construction. Its core concept is to use information technology to break down “information silos” among government departments, eliminate data barriers between government and market entities, and develop efficient and collaborative digital governance. Existing research has shown that government service informatization can promote enterprise innovation, enhance investment efficiency, and drive high-quality economic development. The high-quality development of the bond market is a crucial component of such development, but few studies have explored the impact of government service informatization on the high-quality development of the bond market.
We use the National Pilot Policy for Information Benefiting the People as an exogenous shock and employ a difference-in-differences (DID) model to examine the impact of government service informatization on the high-quality development of the bond market. We find that compared with non-pilot areas, corporate bond credit risk in the pilot cities for Information Benefiting the People is significantly lower. Mechanism analysis reveals that government service informatization mitigates bond credit risk by alleviating information asymmetry, reducing institutional transaction costs, curbing the probability of corporate default, and improving bond liquidity. The heterogeneity analysis indicates that the effect of government service informatization on reducing bond credit risk is more pronounced in regions with higher environmental uncertainty, lower levels of government websites information disclosure, greater regional information barriers, and lower bond credit ratings. Further analysis shows that government service informatization helps improve bond pricing efficiency and helps curb credit rating inflation.
This paper makes the following contributions. First, taking the high-quality development of the bond market as the research perspective, this paper verifies the positive impact of government service informatization on the development of the corporate bond market. This finding enriches the research on the economic consequences of government service informatization from a financing perspective and provides valuable insights for the design of subsequent related studies. Second, from the perspective of big data empowerment, we explore the role of government service informatization in reducing bond credit risk, improving bond pricing efficiency, and curbing credit rating inflation, thereby enriching the literature on the factors influencing the high-quality development of the bond market. Third, we attempt to explore the information, service, supervision, and confidence empowerment of government service informatization, providing useful enlightenment on how government service informatization can accelerate the transformation of government functions, enhance service efficiency, improve social expectations, and promote the high-quality development of the bond market.
This paper offers the following policy implications. First, we emphasize the importance of advancing government service informatization to build an efficient, service-oriented government. The government should make full use of information technologies such as the Internet, big data, and cloud computing to comprehensively improve government services. Second, we highlight the need to fully develop and utilize government data and deepen the promotion of open data sharing. The government should promote the integration of multi-dimensional and multi-level data resources, improve the mechanism for sharing and disclosing government data, and fully release the value of data. Third, this paper stresses the active role that government service informatization can play in promoting the high-quality development of the bond market. By providing transparent and efficient government services, it can reduce the operational burdens on enterprises and improve the accessibility to government information resources, effectively reducing information frictions among market entities, ultimately contributing to the high-quality development of the bond market.

As the world's largest emerging market, China's stock market exhibits distinctive local characteristics with the T+1 trading mechanism as one of the prime example. First introduced in 1995, T+1 became a unique foundational system in China's stock market, standing apart from the mainstream global markets and representing a localized exploration of capital market infrastructure. It was originally designed to curtail rampant speculation in the market's early stages and maintain orderly trading. By restricting same-day sell orders by buyers, it lowered intraday trading frequency, effectively dampening speculative enthusiasm in early days. However, as the market matured and integrated more with the world, the limitations of T+1 have become increasingly apparent. Theoretically, T+1 can “cool down” the market by lowering trading frequency. But in a market with strong heterogeneity of beliefs, such external restrictions may exacerbate volatility and fuel speculation. In China's stock market, investors often hold widely divergent views and the market is flush with liquidity, so T+1 may have actually spurred speculative trading. Meanwhile, it prevents buyers from correcting mistakes in time, disadvantaging small and medium-sized investors. Furthermore, it heightens asymmetries of rights between investors in index futures and the spot market.
In recent years, the call for market reforms has grown more urgent. Ahead of the launch of the STAR Market (Sci-Tech Innovation Board) in 2019, whether to adopt T+0 or T+1 became a heated topic. In March 2021, the China Securities Regulatory Commission stated that T+0 trading involves numerous stakeholders and would have profound market impacts, thus requiring careful planning and thorough evaluation. While T+1 did play a positive role in the market's early stages, its suitability has been widely questioned amid demands for high-quality development in the capital market. However, China's capital market has operated under T+1 for so long that there is little comparative data under alternative settlement mechanisms, making it difficult for academic researchers to empirically evaluate its effects. Consequently, constructing a theoretical price model tailored to the Chinese context and quantifying the influence of T+1 have become key scholarly and practical challenges.
Against this backdrop, this paper introduces an implied put option framework that captures liquidity discounts embedded in stock pricing, splitting the stock price into its fundamental value and option value. Theoretically, we demonstrate the relationship between T+1 trading and overnight returns, and we empirically verify these findings using data from the Shanghai and Shenzhen A-share markets. We then further examine how arbitrage constraints moderate this relationship and use high-frequency index data to investigate the intraday decaying effect of the discount induced by T+1. Lastly, employing a Taylor expansion, we quantify the overnight return discount attributable to T+1. The results reveal: first, T+1 entails considerable institutional costs, distorts both intraday and overnight return distributions, and contributes to persistently negative overnight returns in China's stock market—with an estimated annual discount of 12.11% caused by T+1. Second, under T+1, stock prices reflect not only a company's fundamentals but also option-like liquidity discounts. Factors affecting this option value directly influence overnight returns: higher opening prices, greater historical volatility, and larger deviations between two consecutive days' opening prices tend to produce more negative overnight returns; meanwhile, a higher risk-free rate raises overnight returns. Arbitrage constraints amplify these negative relationships. Third, the option component embedded in the stock price peaks at the market open and then gradually decays throughout the trading day, leading, over the long run, to relatively lower open prices and higher close prices, and thus more negative overnight returns. High-frequency data show that T+1 increases trading volume at the open but does not lift overnight returns; in fact, it exacerbates negative returns. This reflects predominantly sell-side activity at the opening and suggests that T+1 amplifies investors' willingness to sell at the open.
From both theoretical and empirical perspectives, this paper enriches the study of China's distinct financial system by analyzing how market mechanisms shape asset pricing, and it offers valuable practical insights for refining the country's stock market infrastructure. Specifically, this study illustrates how T+1 imposes asymmetric trading constraints that spur opening-hour sell pressure, skewing intraday supply-demand dynamics and creating a buyer's market for much of the trading session. Considering financial stability, replacing T+1 with T+0 in the short term is challenging. Instead, its negative effects can be mitigated by complementary measures that rebalance supply and demand. For instance, exchanges could introduce flexible single-stock options, providing investors with additional hedging tools.

China's capital markets are characterized by a dominant presence of retail investors, whose trading behavior is frequently blamed for various market anomalies. Contrary to conventional wisdom, this paper examines how the rational decision-making of retail investors actually contributes to the observed main fund anomaly. The paper demonstrates that this phenomenon stems from a rational information game between institutional and retail investors. Our analysis reveals that institutional investors employ large-order trades as informative signals, which retail investors choose to follow to minimize their information acquisition costs. This interaction explains why main fund indicators-derived from large trade data-possess significant predictive power for future returns and can generate substantial alpha when incorporated into investment strategies. The study identifies a novel mechanism behind the main fund anomaly, challenging the prevailing view that such anomalies necessarily result from retail investor irrationality. Our findings offer valuable implications for enhancing market efficiency and anomaly mitigation strategies.
Central to our framework is the recognition of information asymmetry in Chinese market, where retail investors face comparatively higher costs in obtaining reliable stock performance information. This environment creates a mutually beneficial “trading surplus” that incentivizes strategic interaction to enhance expected utility: institutions initiate positions through large orders, while retail investors optimally respond by following these signals and buy stocks from institutions. This sequential trading equilibrium generates superior outcomes for both parties compared to scenarios without large-order trading, ultimately producing the observed pattern where large trades systematically precede price increases.
The potency of this mechanism varies with “trading surplus” levels. When retail participation is high, institutions can confidently expect sufficient follow-on demand to support their positions, while retail investors benefit from reduced information costs. The trading surplus-comprising expected institutional gains from large-order trading and retail savings from signal following-becomes particularly substantial when large orders convey stronger information content, thereby intensifying the anomaly.
Our empirical investigation employs comprehensive A-share market data from 2010-2023, applying careful data filters to ensure robustness. We exclude ST/*ST stocks and the smallest decile by market capitalization to mitigate shell company effects, while implementing standard winsorization procedures (at 1%) to mitigate the effect of extreme values.
This study proposes and empirically tests the following hypotheses. First, we verify the existence of significant main fund anomalies in China's stock market (H1): Stocks with higher weekly net main fund inflows demonstrate significantly higher returns in the subsequent holding period. Empirical results confirm the positive predictive power of main fund flows at weekly frequency-a 1% difference in main fund exposure between two stocks predicts an average annualized return spread of 0.63% in the following week.
Second, to validate the information game mechanism between institutional and retail investors, we further examine how the main fund anomaly becomes more pronounced in stocks with “greater retail participation” and “stronger large-order signaling effects.” Regarding retail participation, we test through high-low main fund long-short portfolios: H2a posits that the positive correlation between weekly main fund inflows and subsequent returns strengthens during high-market-sentiment periods; H2b suggests this relationship intensifies for stocks with higher Baidu search indices. These hypotheses fundamentally reflect that stocks attracting greater retail attention (evidenced by elevated market sentiment or search frequency) exhibit higher relative retail investor participation.
Concerning the signaling role of large orders, we establish: H3a shows the main fund-return relationship strengthens for large-cap stocks, where informed traders more strategically employ large orders; H3b demonstrates this effect amplifies in stocks with higher institutional ownership. The underlying logic is that for large-cap, institutionally-dominated stocks, information holders preferentially use large orders to convey signals, thereby enhancing the informational content of these trades.
The study identifies high retail participation and information asymmetry as key drivers of the main fund anomaly—a manifestation of market inefficiency—and proposes several measures to enhance market efficiency. First, reducing information asymmetry through stricter disclosure requirements for listed firms and improved trading data transparency would help narrow the informational gap between retail and institutional investors. Second, encouraging retail investors to channel their investments through institutional intermediaries (e.g., mutual funds) could mitigate the inefficiencies arising from their inherent informational disadvantages, even though their trading behavior remains rational. Additionally, given that existing research faces challenges in linking large trades and main fund flows to institutional activity due to limited disclosure, our novel factor construction method provides a clearer connection, aiding both academic research and regulatory oversight. Beyond advancing the understanding of market anomalies, this work offers actionable policy insights to promote a more efficient and transparent stock market.