Hyman Minsky (1919–1996), a prominent post-Keynesian economist, argued that capitalist financial systems are inherently unstable. During prolonged prosperity, firms and financial institutions increase leverage and adopt more fragile forms of financing, shifting from hedge to speculative and Ponzi finance. This gradual buildup of financial fragility can eventually trigger a sudden collapse of asset values—later termed a “Minsky moment.” After the 2007–2009 global financial crisis, Minsky’s ideas gained renewed attention, and current financial developments once again bring his insights to the forefront.

The China Securities Regulatory Commission is allowing firms to use externally financed funds for share repurchases, a recent measure to enable listed companies address valuation pressures and protect investors; however, its implications for corporate marketing decisions remain unclear. Using an event sample of Chinese listed firms that conducted open-market repurchases between 2009 and 2024, this study empirically examines how this market activity financed by different sources influence marketing decisions and explores the underlying mechanisms. The findings show that compared with firms using internal cash for repurchases, those relying on debt financing are inclined to resist myopic marketing decisions, and this negative relationship is pronounced under high analyst coverage and when privately owned listed firms are controlled by family entrepreneurs. These results remain robust after replacing the dependent variables and applying propensity score matching. Overall, this study shows that debt financing to support share repurchases has a long-term beneficial governance impact as it improves earnings quality and protects investor interests, and offers a new perspective on the relationship between financing-based repurchases and marketing myopia, and provides useful policy insights for evaluating the effectiveness of China’s refinancing regulations related to share repurchases, while guiding further refinement.

Bankruptcy abuse prevention has been criticized for increasing foreclosure rates, imposing negative impacts on housing markets, and aggravating the financial crisis. By contrast, this paper documents that bankruptcy abuse prevention reduces household debt overhang, a phenomenon harmful to home values and housing markets. Using a difference-in-differences analysis, we find that households in recourse states increased their home improvement and maintenance expenditures after the Bankruptcy Abuse Prevention and Consumer Protection Act, a period during which the households paid considerable attention to the downside risk of the housing market, and that the effects vary by home equity level. The results remain unchanged with alternative specifications and cannot be explained by credit changes, judicial and nonjudicial foreclosures, homestead exemption, house sales, or heterogeneous expectations. Last but not least, we use entropy balancing to eliminate the differences between the treatment and control groups and get similar results. 预防破产滥用的政策被认为推高止赎率、对住房市场造成负面影响以及加剧金融危机而饱受批评。与之相反，本文证明破产滥用预防能够缓解家庭债务积压（debt overhang）—— 而债务积压恰恰是一种损害房屋价值与住房市场的现象。采用双重差分（DID）分析，我们发现：在《破产滥用预防与消费者保护法案》（BAPCPA）实施后，**追索权州（recourse states）**的家庭增加了住房改善与维护支出；该时期家庭对住房市场的下行风险高度关注，且上述效应因房屋净值水平的不同而存在异质性。在多种替代设定下结果依然稳健，且不能被信贷变化、司法与非司法止赎、宅基地豁免、房屋销售或异质性预期所解释。最后，我们使用熵平衡（entropy balancing）方法消除处理组与控制组之间的差异，同样得到了一致的结果。

Firm survival, as a key indicator of regional economic resilience, has gained increasing attention in the context of global economic uncertainty and the deep adjustments in industrial structures. In the Pearl River Delta (PRD), a core region of China’s Guangdong-Hong Kong-Macau Greater Bay Area, the characteristics of firm life cycles are crucial for understanding spatial development inequalities and institutional effects in emerging economies. This study focuses on firms in the PRD, using full life-cycle data from registration, operation, to deregistration. An XGBoost regression model is employed, incorporating the SHAP explanation algorithm, to systematically analyze the main factors influencing firm survival. The results show that: (1) Firm establishment time is the primary factor influencing survival, with significant “survival threshold” and “growth leap” effects—mature firms exhibit a distinct survival advantage; (2) Among spatial structure variables, moderate industry specialization and diversity enhance firm survival rates, while excessive concentration and diversification show diminishing or negative returns, reflecting an “ecological threshold” effect; (3) External shocks have a significant suppressive impact on startups, while policy support and capital size show limited explanatory power; (4) The ownership structure, especially state-holding, has a positive moderating effect on firm survival in specific contexts, indicating that private enterprises’ flexibility and adaptability can compensate for institutional gaps. This study offers insights into the spatial heterogeneity of firm survival mechanisms, providing quantitative evidence for regional economic policy adjustments and firm resilience-building. Recommendations include promoting differentiated policies, optimizing industrial ecological spatial layouts, and piloting systems to enhance survival resilience, especially for mixed-ownership firms.

The relationship between economic decentralization and regional economic growth has attracted wide academic attention. However, existing literature rarely explores the validity and applicability of decentralization theory from the perspective of location endowments. This study takes China’s county-to-city reform - a decentralization policy - as a point of entry to construct a decentralization model incorporating location endowments. Using county-level panel data from 1992 to 2009 and employing a difference-in-differences (DID) approach, the study evaluates the impact of county-to-city reform under the constraint of location endowments on county-level economic development. The findings reveal that the policy effects of local decentralization are constrained by location endowments. Specifically, in regions with poorer location endowments, county-to-city reform significantly inhibits local economic development. Indeed, mechanism analysis further indicates that in such disadvantaged regions, local decentralization under the county-to-city reform generates a “political resource curse” effect, which hinders economic growth through three channels such as distorted fiscal expenditure structures, corruption, and misallocation of land resources. The conclusions of this study provide a valuable perspective for understanding the conditions under which decentralization theory holds, while also offering rigorous empirical evidence for government agencies to design more targeted decentralization policies.

Investors and forecasters often extrapolate from past returns, but whether this reffects behavioral bias or efficient information processing remains unclear. We address this questionby inferring Chinese mutual fund managers’ market expectations from textual analysis oftheir commentaries and linking them to portfolio choices and performance. Extrapola-tion is state-dependent: it is stronger when growth is above trend and idiosyncratic riskis relatively more important. It is associated with weaker market timing and strongerstock picking, leaving overall performance unchanged. Our findings support a rational-inattention model of expectation formation, in which managers shift scarce attentionbetween aggregate and stock-speciffc information as the relative importance of differentrisks change.

We investigate how the loss of informative salient signals in financial markets influences stock return volatility, using the 2024 intraday disclosure reform of the mainland China-Hong Kong Stock Connect program as a natural experiment. The reform eliminated the real-time disclosure of northbound capital (NC) flows on trading platforms, rendering NC trading information invisible to Chinese investors during market hours. We find that the removal of NC signals induces increased investor belief dispersion and intensifies informed trading, thereby amplifying intraday volatility in NC-eligible stocks. Moreover, this effect is more pronounced for stocks with higher investor attention, indicating that attentive investors suffer stronger anchor loss when NC signals disappear. In contrast, lottery-type stocks and stocks with alternative NC trading clues exhibit weaker volatility responses, since the presence of strong alternative signals reduces the effect of NC signal loss. These findings highlight the informational role of insightful salient signals in stabilizing stock returns.

Straddle Option is a financial trading tool that explores volatility premiums in high-volatility markets without predicting price direction. Although deep reinforcement learning has emerged as a powerful approach to trading automation in financial markets, existing work mostly focused on predicting price trends and making trading decisions by combining multidimensional datasets like blogs and videos, which led to high computational costs and unstable performance in high-volatility markets. To tackle this challenge, we develop automated straddle option trading based on reinforcement learning and attention mechanisms to handle unpredictability in high-volatility markets. Firstly, we leverage the attention mechanisms in Transformer DDQN through both self-attention with time series data and channel attention with multi-cycle information. Secondly, a novel reward function considering excess earnings is designed to focus on long-term profits and neglect short-term losses over a stop line. Thirdly, we identify the resistance levels to provide reference information when great uncertainty in price movements occurs with intensified battle between the buyers and sellers. Through extensive experiments on the Chinese stock, Brent crude oil, and Bitcoin markets, our attention-based Transformer-DDQN model exhibits the lowest maximum drawdown across all markets, and outperforms other models by 92.5% in terms of the average return excluding the crude oil market due to relatively low fluctuation.

Traditional information asymmetry theories suggest that greater corporate transparency should reduce investor disagreement. Using Chinese mutual fund holdings, we document the opposite pattern: transparency amplifies disagreement among institutional investors. Mechanism tests show that transparency discourages herding while intensifying private information acquisition among fund managers. The effect is stronger for growth-oriented and high-skill funds, and during periods of elevated market sentiment, and among firms with lower credibility, excessive disclosure frequency, and greater investor attention. Further analysis indicates that this transparency-induced disagreement stems from informed trading rather than noise, thereby enhancing price informativeness and market efficiency. Overall, the evidence reveals the dual nature of transparency as both an informational input and a behavioral catalyst that increases disagreement in financial markets.

This study develops a comprehensive methodological framework for identifying and quantifying investor echo chambers in online stock discussion forums. Motivated by a dynamic model of endogenous echo chamber formation, which formalizes how investors optimally allocate attention and update beliefs under cognitive and informational constraints, we construct a two-layer multiplex investor network that integrates common-attention similarity and semantic similarity to jointly capture the informational and cognitive linkages among investors. This framework enables the systematic examination of how shared information sources and convergent opinions emerge within investor communities. We compute both community-level and individual-level (node-level) echo-chamber intensity by integrating measures of social homophily, semantic reinforcement, and community insularity. At the firm level, we further aggregate these micro-level indicators using attention-weighted indices, community concentration (HHI), and semantic polarization metrics to characterize how echo-chamber dynamics manifest in firm-related discussions. In addition, we propose a general empirical panel framework to examine the relationship between investor echo-chamber intensity and firm-level outcomes. Overall, this paper provides a methodological foundation for the broader Investors’ Echo Chamber Project, offering scalable tools for network-based behavioral analysis and laying the groundwork for future research linking online social dynamics, financial market efficiency, and corporate decision-making.