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.

We propose a time-varying framework for tail risk contagion based on conditional higher co-moments (Co-HCM), derived from a DCC-GARCH-MGH model that provides closed-form expressions for dynamic co-moments. Applying this CoHCM approach, we construct tail contagion networks across Belt and Road Initiative (BRI) stock markets. Our ffndings indicate that covariance-based metrics underestimate the ex-tent of epidemic transmission, while the CoHCM metrics reveal China’s pivotal role in spreading outbreaks and identify a distinct cluster of core transmission hubs, particularly during the 2015 Chinese stock market crisis. Dynamic contagion further exhibits cross-country heterogeneity that the Southeast Asian markets synchronize tightly with China during crises, while smaller and resource-driven markets display more inter-mittent contagion patterns. These ffndings highlight the importance of higher co-moment dependence for monitoring systemic risk in interconnected emerging markets.

This study investigates how venture capital (VC) reputation affects initial public offering (IPO) exits in the Chinese VC market using a two-sided matching mechanism. Research that distinguishes the sorting and influence effects of VCs in the Chinese market is lacking. To address this gap, Chinese VC transaction data, comprising 3,606 VC firms and 8,173 investment transactions, was used to construct a structural econometric model. The Markov Chain Monte Carlo Bayesian estimation techniques were employed to identify the sorting and influence effects of VC reputation. We demonstrate that the likelihood of IPO exits is considerably increased by VC reputation, whereas historical investment experience has a dampening effect on exit outcomes. The IPO success rates are significantly higher for firms in the biotechnology, electronics, medical, and late-stage industries. The difficulty of IPO exits increases with investment age. Compared to influence effects, sorting effects were the dominant mechanism. VCs with a high reputation systematically selected firms with potential advantages, such as high-quality management teams, to promote IPO success. This study’s novelty lies in its application of an endogenous two-sided matching solution to the Chinese VC market. Using a structural model, we discovered the importance of the reputation sorting effect in the Chinese VC market and refined the VC’s investment preferences in high-tech industries. This study’s practical significance lies in the findings that enterprises must pay attention to the sorting capabilities of VC institutions, the government can guide capital flows to efficient exit industries, and VC institutions should optimize the resource allocation structure.

Prevailing research, assuming developed financial markets, concludes that Chinese firms heavily rely on “short-term credit for long-term investment.”We challenge this view, arguing that China's vibrant informal financial system provides crucial alternative funding. Consequently, the severity of this maturity mismatch is likely overestimated. To investigate this, we examine strategic alliances as a representative informal institution. Our analysis confirms that such alliances significantly mitigate maturity mismatch, revealing that they enhance information sharing and reduce transaction costs. This provides initial evidence of informal institutions' critical role in addressing this issue. Given the prevalence of similar arrangements in China—like private lending and inter-corporate financing—our findings highlight the need to look beyond formal systems. This perspective not only recalibrates the understanding of corporate financing in China but also opens ample avenues for future research on informal finance's role in emerging economies.

We conduct a field experiment in China, o↵ering small business owners a conditional social media advertising subsidy. Beyond boosting business revenue and employment, the inter-vention significantly increases access to fintech credit: treated firms are more likely to open online stores and obtain online loans, while bank credit remains una↵ected. Our findings reveal a “fintech accelerator” mechanism—digital marketing drives sales growth that directly improves firms’ eligibility for fintech lending—demonstrating how targeted digital interven-tions can enhance financial inclusion and reshape credit allocation for small businesses.

This study examines the role of negative peer events, specifically initial bond defaults, in driving leverage manipulation of non-defaulting firms within the same region. Controlling for firm-specific time-varying characteristics, we find that initial bond defaults within a province are associated with an increase in leverage manipulation among non-defaulting firms. Two potential mechanisms underlying this relationship include increased financial constraints for these firms and elevated investor risk perception of the local bond market. The positive impact of bond defaults on leverage manipulation is more pronounced for financially constrained firms, firms with severe information asymmetry, and those affected by high-rated bond and principal defaults. We further show that companies that manipulate their debt ratios experience higher default risk. Our findings have important implications for transparent disclosure and highlight the negative effect of regional bond defaults on corporate financial reporting practices.

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A critical barrier to labor mobility arises from institutional constraints that im-pose discriminatory costs on migrants. Using China’s hukou system as a case study,we construct a novel, outcome-based measure of mobility frictions that infers thesediscriminatory costs. We document a systematic relationship between our frictionmeasure, migrants’ decisions to leave behind families (“partial migration”), remit-tances, and expenditure patterns. Our estimated spatial general equilibrium modelencompasses these features and examines how mobility frictions interact with tradeliberalization to shape migration, inequality, and welfare. Trade-exposed regionsbenefft from attracting migrants, while high-friction regions experience muted laborreallocation and smaller welfare gains.

This paper examines the impact of Exchange-Traded Fund (ETF) ownership on corporate earnings management. We find that ETF ownership is associated with a significant reduction in earnings management, and this result remains robust across a wide range of endogeneity tests and robustness checks. Further analyses reveal that ETFs exert a pronounced mitigating effect on sales manipulation, production manipulation, and expense manipulation. Mechanism tests indicate that ETFs curb earnings management by improving stock liquidity and strengthening external monitoring. We also find that the influence of ETFs is stronger in private firms, in firms with lower information transparency, and in firms with CEO duality, suggesting that ETFs serve as a more prominent external governance force when internal governance mechanisms are relatively weak. Overall, this study enriches the literature on the economic consequences of ETFs and provides new empirical evidence that financial innovation in emerging markets can help alleviate the information risk faced by investors.

We examine the information content of the call-put implied volatility spread (IVS) of Shanghai Stock Exchange 50 ETF options. Empirically, the IVS significantly and negatively predicts future SSE50 ETF returns at both weekly and monthly horizons. This predictability is robust both in-sample and out-of-sample, which stands in contrast to prior evidence from the U.S. options market. We explore several potential explanations and show that the IVS is closely linked to the option-cash basis. Its predictability is consistent with the model of Hazelkorn, Moskowitz, and Vasudevan (2023), where the option-cash basis reflects liquidity demand common to both options and underlying equity markets.