Financial crises rarely erupt without warning; they are preceded by long periods of hidden fragility. Yet traditional market indicators such as the VIX capture only realized volatility, offering little foresight. This paper introduces the Stability Gap Model (SGM), developed iteratively from a simple intuition: fragility arises when risk-taking diverges from fundamentals and systemic buffers are insufficient. We trace the evolution of the model from its original formulation, through corrections and extensions, to its present form. The Classic SGM captures instantaneous imbalance, while the Beta SGM incorporates memory of past shocks. Empirical analysis demonstrates that the SGM provided clear early warnings ahead of the 2008 Global Financial Crisis, the 2011 Eurozone debt episode, the 2015 China/oil slowdown, and the 2018 tightening cycle, while also trending upward in 2019 before the COVID-19 crash. Furthermore, the paper demonstrates the model's utility in assessing fragility in hedge funds and proposes its application as a universal framework for stability analysis across diverse systems, from corporate finance to supply chains.

While government support programs are often effective at helping firms achieve their objectives, these programs may have unintended consequences. Motivated by this, this study empirically examines the impacts of receiving investments from government-guided funds (GGFs) on executive-employee pay gaps in Chinese public firms. The results from difference-in-differences analyses show that GGFs investments lead to a significantly greater widening of the pay disparities between executives and employees in recipient firms than in other firms after funding is granted. This widening gap is driven by a larger increase in executive compensation relative to employee wages. The mechanism analysis suggests that increased cash holdings associated with receiving GGFs create financial slack that facilitates managerial opportunism, ultimately resulting in greater pay gaps. These findings reveal an unintended consequence of GGFs, highlighting an overlooked agency cost of government financial support programs.

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 the stock market reaction in China to Trump’s tariff policy announcement on April 2, 2025. We find that the tariff policy reduced stock prices of Chinese firms except those in the agricultural sector. Large-cap stocks, value stocks, stocks of high profitability firms, and stocks of state-owned enterprises experienced smaller negative impacts. Stocks with higher institutional holdings by mutual funds and Social Security Funds exhibited higher resilience, possibly due to these investors' superior capability in selecting stocks and forecasting trade war risks. In contrast, stocks held by Qualified Foreign Institutional Investors (QFII) did not exhibit such resilience.

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 constructs a three-dimensional space model based on fund investment styles, using a sample of open-end equity and mixed funds from 2005 to 2021 to measure the degree of style convergence. The research explores how style convergence impacts fund managers’ window dressing behavior. The results indicate that, after accounting for the effects of fund performance, style convergence exacerbates window dressing behavior among fund managers. Specifically, this is reflected in fund managers increasing their holdings in winning stocks and selling off losing stocks, which indirectly highlights the intense competition within China’s open-end fund industry. The findings remain robust after a series of endogeneity and robustness tests. Further analysis reveals that style convergence contributes to the risk of client attrition, thereby intensifying the agency problem within the fund industry. The window dressing effect due to style convergence is particularly pronounced in funds managed by individuals with lower educational backgrounds, lower investment skills, smaller family sizes, and lower institutional investor ownership. The paper offers valuable insights into the agency problems arising from investment style convergence and provides guidance for mitigating fund managers' self-interested behavior.

This study investigates how mutual funds impact the stock market by ana-lyzing the relationship between mutual fund investment behaviours (holding and trading) and stock returns and realized volatility in the Chinese market. It is found that stocks widely held or bought by mutual funds can earn higher excess returns, and more importantly, the trading measures out-perform the holding measures, which is evident by the portfolio analysis and Fama-MacBeth regressions. Moreover, the proportional holding, pro-portional trading and shares trading measures positively and significantly predict future realized volatility. Meanwhile, a weak asymmetric effect in the share-trade measure is found.

We posit and demonstrate that, in China’s retail-dominated market, quantitative trading over-relies on non-fundamental signals, thereby crowding out fundamental information from stock prices and increasing crash risk. Using trading data from quantitative mutual funds and Chinese A-share firms during 2009-2023, we find that greater exposure to quantitative trading is associated with higher future crash risk. Mediation analysis further reveals that reduced information efficiency constitutes a key channel through which quantitative trading elevates crash risk. The effect is stronger for stocks with more retail investors, consistent with our proposed mechanism. Overall, we identify a novel potential risk of quantitative trading in underdeveloped emerging markets.

Do investors respond to what fund managers say, or how they look saying it? Using 2,000 live-streamed sessions by Chinese ETF managers and multimodal machine learning, we show that managers’ facial expressions, not their words, drive fund flows. A one-standard-deviation increase in positive facial affect raises next-day flows by 0.17pp (260% of mean). Vocal tone shows weak effects; textual sentiment shows none. Critically, facial expressions predict flows but not returns, indicating pure persuasion rather than information transmission. Effects strengthen when investors are emotionally vulnerable (down markets, retail-heavy funds) and persist 2-3 weeks before dissipating. Our findings challenge the emphasis on textual disclosure in finance and raise questions about investor protection as video communication proliferates.

This paper examines whether mandatory ownership disclosure aligns incentives or distorts in-vestor beliefs. Using a sample of 1,436 Chinese equity-oriented mutual funds from 2012 to 2023,we find that higher managerial and senior ownership are significantly associated with larger in-flows, suggesting that investors treat ownership as a quality signal. However, we find no evidencethat ownership forecasts superior future returns or risk-adjusted alphas. Mechanism tests showthat the ownership-flow effect is much stronger in low-marketing funds and that managers increaseownership after weak flows, a countercyclical pattern inconsistent with overconfidence and consis-tent with strategic remedial signaling. Overall, ownership disclosure appears to operate primarilythrough investor perception rather than information about managerial ability, weakening the linkbetween capital allocation and true skill in the mutual fund industry.