Search Results (44)

This study examines how geographic distance to Vietnam’s centralized securities regulator—the State Securities Commission (SSC)—influences firm-level stock price crash risk. In emerging markets characterized by weak governance, corruption, and political connections, distance can erode monitoring effectiveness and heighten managerial incentives to conceal bad news. Using data on Vietnamese listed firms from 2010 to 2024, we find a robust positive association between a firm’s distance to the SSC headquarters in Hanoi and its future crash risk. The effect is stronger for non-state-owned enterprises (non-SOEs) and in provinces with high corruption, but disappears in SOEs and in more transparent regions, where state-related networks provide insulation from weak formal institutions. Exploiting the 2019 Securities Law as a quasi-natural experiment, we show that the distance effect was more pronounced before the reform, suggesting that improved formal regulation can partially offset geographically induced monitoring frictions. Additional tests reveal that the effect is amplified among firms listed on the Ho Chi Minh Stock Exchange (HOSE) and those with higher financial leverage. Our findings provide novel evidence on the spatial dimension of regulatory enforcement in emerging markets. We highlight geographic distance as a significant but previously overlooked source of crash risk, with implications for regulators in designing risk-based supervision and for investors in pricing location-driven risks. Full article

This study analyzes the relationship between country-level income inequality and stock price crash risk using a comprehensive cross-country panel of 117,017 firm-year observations from 45 countries spanning 2000–2022. We document that firms headquartered in countries with higher income inequality face a significantly greater likelihood of experiencing stock price crashes. Building on behavioral finance theory, we argue that income inequality exacerbates managerial incentives to withhold negative information, thereby increasing crash risk. We further show that this relationship is moderated by both country-level and firm-level mechanisms that influence information transparency. Specifically, stronger national transparency, greater institutional ownership, and lower excess cash weaken the positive association between income inequality and crash risk. Our results remain robust across alternative crash risk measures and endogeneity tests, including instrumental variable and propensity score matching approaches. These findings highlight income inequality as an important macro-level determinant of financial market instability and underscore the role of transparency and monitoring in mitigating its adverse effects on capital markets. Full article

Climate shocks are increasingly recognized as systemic stressors that disrupt financial stability and undermine sustainable development. Using a comprehensive panel of Chinese listed firms from 2007 to 2023, this study examines how physical climate shocks propagate through the financial system. Specifically, we investigate their impact on elevating stock price crash risk and impairing corporate sustainability. We construct a firm-level physical climate risk indicator by applying machine learning and text analysis to annual reports. The empirical evidence demonstrates that climate shocks significantly increase stock price crash risk, indicating heightened systemic vulnerability within the financial system. Mechanism analysis identifies two key transmission channels linking climate shocks to crash risk: tightened liquidity constraints and diminished risk-taking capacity. Furthermore, we find that firms with stronger green transformation efforts exhibit lower sensitivity to climate-induced crash risk. This highlights the crucial role of green initiatives in enhancing institutional and financial resilience. Additional analyses reveal that the rise in crash risk subsequently weakens corporate sustainable development performance. Overall, these findings provide micro-level evidence of how climate shocks generate asymmetric effects within the financial system. The study concludes with policy implications for strengthening climate resilience, stabilizing capital markets, and advancing sustainability in emerging economies. Full article

By employing the 2017 reform of China’s financial statement presentation as an exogenous shock, we evaluate how the change shapes the likelihood of stock price crashes. Our analysis indicates that firms affected by the reform exhibit notably higher crash risk after the new reporting format is adopted, and this finding remains consistent across multiple robustness checks. The increase in crash risk can be largely attributed to managerial incentives to manage earnings by reclassifying held-for-sale assets and other special items. Moreover, the reform exerts a stronger effect on firms that exhibit poor information transparency and receive little oversight from internal and external monitors. Full article

Corporate social responsibility (CSR) plays a growing role in fostering transparency, stakeholder trust, and long-term firm sustainability, particularly in emerging markets. Firms that actively engage in CSR are more likely to disclose credible financial information, which can reduce the incentive to withhold adverse news and thereby limit stock price crash risk (SPCR). This study investigates the impact of CSR on SPCR, while also examining whether this relationship varies across different stages of the firm life cycle (FLC). The analysis is based on an unbalanced panel of listed non-financial firms from the Pakistan Stock Exchange (PSX), covering the period from 2009 to 2023. Financial data were obtained from the State Bank of Pakistan (SBP) and Securities and Exchange Commission of Pakistan (SECP), while market data were collected from the PSX. Employing fixed-effects robust regression models and two crash risk proxies, negative conditional skewness (NCSKEW) and down-to-up volatility (DUVOL), the results reveal a consistent and significant negative association between CSR and SPCR. This suggests that firms with stronger CSR engagement are less prone to extreme negative stock returns. However, the moderating effect of FLC is only evident at the introduction and decline stages, indicating that the effectiveness of CSR in reducing crash risk depends on a firm’s position in its organizational life cycle. These findings contribute to the literature on CSR and financial stability in emerging markets and offer practical implications for investors, managers, and policymakers seeking to promote risk-aware, socially responsible corporate strategies. Full article

In the digital economy, data assets have become key drivers of firm competitiveness and market stability. This study examines the association between data asset information disclosure and stock price crash risk. Using annual reports of Chinese A-share listed firms from 2010 to 2023, we construct a Data Asset Information Disclosure Index through textual analysis. A double machine learning framework is employed to flexibly control for high-dimensional confounders, and the results indicate that greater disclosure is associated with lower crash risk across multiple specifications. Generalized random forest analysis further highlights heterogeneous relationships, with disclosures on both internally used and transactional data assets showing stronger negative associations with crash risk. Mechanism evidence suggests that disclosure may facilitate information dissemination, strengthen investor confidence, and improve analyst forecast accuracy. The association is more pronounced in firms with weaker corporate governance, higher reporting transparency, more competitive industries, and in regions with less developed digital economies. An industry spillover pattern is also observed, whereby one firm’s disclosure is linked to reduced crash risk among peers. Overall, this study contributes to the literature on data asset disclosure and corporate risk management by providing empirical evidence from a major emerging market and by highlighting the potential relevance of enhanced transparency for digital governance and capital market resilience. Full article

Reducing stock price crash risk is vital for capital market stability, particularly in emerging economies such as China. This study investigates whether Employee Stock Ownership Plans (ESOPs) can mitigate crash risk by analyzing panel data from A-share listed firms between 2014 and 2022. In contrast to prior research that has largely centered on managers and controlling shareholders, we highlight employees as active participants in corporate governance. Employing firm, year, and industry fixed effects, together with propensity score matching and instrumental variable techniques, we find robust evidence that ESOPs significantly reduce crash risk. Mediation analyses indicate that this effect operates through reduced agency costs both between managers and shareholders and between controlling and minority shareholders, as well as enhanced corporate productivity. Moderation tests further show that ESOPs are most effective when investor attention is high and when exit threats from non-controlling major shareholders are stronger. Heterogeneity analyses reveal that ESOPs exert greater influence in non-state-owned enterprises, in eastern regions, in firms with higher employee participation, and when shares are sourced from the secondary market. By extending the observation window to nearly a decade and deploying multiple robustness checks, this study provides one of the most comprehensive examinations of ESOPs and crash risk to date. It contributes to the literature by reframing employees as central actors in market stability and offers actionable insights for managers, investors, and regulators seeking to enhance corporate governance and reduce systemic risk. Full article

The global economy frequently experiences cycles of rapid growth followed by abrupt crashes, challenging economists and analysts in forecasting and risk management. Crashes like the dot-com bubble crash and the 2008 global financial crisis caused huge disruptions to the world economy. These crashes have been found to display somewhat similar characteristics, like rapid price inflation and speculation, followed by collapse. In search of these underlying patterns, the Log-Periodic Power-Law (LPPL) model has emerged as a promising framework, capable of capturing self-reinforcing dynamics and log-periodic oscillations. However, while log-periodic structures have been tested in developed and stable markets, they lack validation in volatile and developing markets. This study investigates the applicability of the LPPL framework for modeling financial crashes in the Brazilian stock market, which serves as a representative case of a volatile market, particularly through the Bovespa Index (IBOVESPA). In this study, daily data spanning 1993 to 2025 is analyzed to model pre-crash oscillations and speculative bubbles for five major market crashes. In addition to the traditional LPPL model, autoregressive residual analysis is incorporated to account for market noise and improve predictive accuracy. The results demonstrate that the enhanced LPPL model effectively captures pre-crash oscillations and critical transitions, with low error metrics. Eigenstructure analysis of the Hessian matrices highlights stiff and sloppy parameters, emphasizing the pivotal role of critical time and frequency parameters. Overall, these findings validate LPPL-based nonlinear modeling as an effective approach for anticipating speculative bubbles and crash dynamics in complex financial systems. Full article

In a few years, most investment firms will deploy Generative AI (GenAI) and large language models (LLMs) for reduced-cost stock trading decisions. If GenAI-run investment decisions from most firms are heavily coordinated, they could all give a “sell” signal simultaneously, triggering market crashes. Likewise, simultaneous “buy” signals from GenAI-run investment decisions could cause market bubbles with algorithmically inflated prices. In this way, coordinated actions from LLMs introduce systemic risk into the global financial system. Existing risk analysis for GenAI focuses on endogenous risk from model performance. In comparison, exogenous risk from external factors like macroeconomic changes, natural disasters, or sudden regulatory changes, is understudied. This research fills the gap by creating a framework for measuring exogenous (systemic) risk from LLMs acting in the stock trading system. This research develops a concrete, quantitative framework to understand the systemic risk brought by using GenAI in stock investment by measuring the covariance between LLM stock price predictions across three industries (technology, automobiles, and communications) produced by eight large language models developed across the United States, Europe, and China. This paper also identifies potential data-driven technical, cultural, and regulatory mechanisms for governing AI to prevent negative financial and societal consequences. Full article

ESG has emerged as a key non-financial indicator, drawing significant investor focus. Disparities in ESG ratings may skew investor perceptions, potentially endangering stock values and financial market stability. This paper examines the link between ESG rating divergences and stock price crash risk, drawing on data from six Chinese and global ESG rating agencies. Focusing on Shanghai and Shenzhen A-share listed firms, it analyzes information from 2015 to 2022 within the theoretical contexts of information asymmetry and external monitoring. This study finds that ESG rating divergence markedly elevates stock price crash risk, a relationship that persists through a series of robustness checks. Specifically, the mechanisms operate through two key pathways: increased reputational damage risk due to information asymmetry and reduced external monitoring due to weakened external governance. The results of the heterogeneity analysis indicate that ESG rating divergence exacerbates stock price crash risk more significantly for non-state-owned firms, firms with low levels of marketization, and firms in high-pollution industries. This study provides clear actionable strategic paths and policy intervention points for investors to avoid risks, firms to optimize management, and regulators to formulate policies. Full article

This study investigates the causal impact of stock price crash risk on the cost of equity (COE) in China’s segmented A- and B-share markets with an emphasis on ownership structures and market regimes. Employing a bootstrap panel Granger causality framework, Markov-switching dynamic regression, and panel threshold regression models, the analysis reveals that heightened crash risk significantly increases COE, with the effects being more pronounced for A-shares because of domestic investors’ heightened risk sensitivity. This relationship further intensifies in bull markets, where investor optimism amplifies downside risk perceptions. Ownership segmentation plays a critical role, as foreign investors in B-shares exhibit weaker reliance on firm-level valuation metrics, favoring broader risk-diversification strategies. These findings offer actionable insights into corporate risk management, investor decision making, and policy formulation in segmented and emerging equity markets. Full article

This study investigates whether and how the complexity of derivative use influences the stock price crash risk in China’s capital market, a critical question given the growing use of derivatives in emerging economies where governance structures and disclosure standards vary widely. While prior research has examined the binary effects of derivative usage, limited attention has been paid to the multidimensional complexity of such instruments and its informational consequences. Using a novel hand-collected dataset of annual reports from Chinese A-share-listed firms between 2010 and 2023, we develop and implement new indicators that capture both the economic complexity (diversity and scale) and accounting complexity (reporting dispersion and fair-value hierarchy) of derivative use. Our analysis shows that higher complexity is associated with a significantly lower likelihood of stock price crashes. This effect is especially pronounced in non-state-owned firms and those with weaker internal-control systems, suggesting that derivative complexity can enhance information transparency and serve as a substitute for other governance mechanisms. These findings challenge the conventional view that complexity necessarily increases opacity and highlight the importance of disclosure quality and institutional context in shaping the market consequences of financial innovation. Full article

The overvaluation of merger and acquisition (M&A) assets can lead to a decline in the performance of listed firms, an increase in the risk of goodwill impairment, and harm to the rights of minority shareholders, as well as to the sustainable development of firms. Based on stakeholder theory, this article constructs models to examine the impact of environmental, social, and governance (ESG) practices on the valuation of related party M&A assets and conducts an empirical analysis. We find that ESG practices significantly inhibit the overvaluation of related party M&A assets, and the digital economy can enhance this negative relationship. Mechanism analysis shows that this negative relationship is mediated through setting up stock performance compensation, reducing performance commitment growth rate, selecting reputable asset appraisal institutions and financial advisors, increasing analyst following and social media discussions, and reducing agency costs. Heterogeneity analysis shows that the inhibitory effect of ESG practices on the overvaluation of related party M&A assets is more obvious in non-horizontal M&A and non-state-owned enterprises. Furthermore, ESG practices can alleviate the stock price crash risk by reducing the overvaluation of related party M&A assets. The research conclusions provide a reference for ESG practices to better serve M&A activities and alleviate asset overvaluation in the digital economy era. Full article

Using a sample of S&P 500 stocks, this paper examines the investor sentiment spillover network between firms and assesses how the sentiment connectedness in the network impacts stock price crash risk. We demonstrate that firms with higher sentiment connectedness are more likely to crash as they spread more irrational sentiment signals and are more sensitive to investor behaviors. Notably, we find that the effect of investor sentiment on crash risk mainly stems from sentiment connectedness among firms rather than firms’ individual sentiment, especially when market sentiment is surging or declining. These findings remain robust after controlling for other determinants of crash risk, including stock price synchronicity, accounting conservatism, and internal corporate governance strength. Our results underscore the importance of sentiment connectedness among firms and provide valuable insights for risk management among investors and regulatory authorities involved in monitoring risk. Full article

The implementation of corporate social responsibility (CSR) in conjunction with proficient investor relations management (IRM) can enhance the reputation and appeal of enterprises, thereby fostering the sustainable development of enterprises. This paper examines the correlation between CSR and IRM by exploring the potential misinterpretation of socially responsible actions by listed companies as “hypocrisy”. We use the fixed effect model, moderating effect model and instrumental variable method to examine the correlation between CSR and IRM. The findings indicate that actively fulfilling corporate social responsibility can enhance interaction and communication between listed companies and investors in the capital market, thereby mitigating the risk of being perceived as “hypocrisy”. This positive effect is particularly pronounced when companies are experiencing poor operational performance. These conclusions remain robust even after conducting various tests to address endogeneity concerns. In terms of the underlying mechanisms, corporate social responsibility primarily enhances investor relations management through strengthening network communication and on-site interactions. Moreover, enterprises are more inclined to proactively interact with investors in the capital market when companies face severe financial difficulties, stringent financing constraints, or poor quality of information disclosure. Additionally, our study extends its analysis to elucidate how corporate social responsibility can mitigate the risk of stock price crashes from the perspective of investor relations management. Full article