Farmland transfer in developing countries is characterized by informal contracts. Rich research typically attributes this phenomenon to the lack of property rights and rarely emphasizes the influence of land characteristics themselves. Utilizing plot-level data from 2017-2019 collected in Yangshan County, China, we evaluate the impact of land consolidation on the farmland transfer market transformation. We find that land consolidation has a positive impact on the transformation of farmland transfer markets, instead of its scale expansion. After land consolidation, the scope of transaction partners extends from relationship-based households to anonymous new agricultural operating entities; the transfer rent shifts from being free of charge to being paid; and the transfer duration shifts from short-term to long-term. Mechanism analysis reveals that land consolidation increases land value and reduces transaction costs by improving the endowment of farmland resources, thus driving the farmland transfer market transformation. Further exploration warns that market transformation caused by land consolidation may trigger non-grain farming, leading to a 15.2% reduction in the rice planting area and posing potential risks to food security. These findings enrich the existing studies that only focus on the impact of land rights reform, both theoretically and empirically. In practice, it has important policy implications for countries facing similar difficulties in the farmland transfer market as China.

This paper investigates whether and how independent director-affiliated corporate donations affect stock price crash risk in China. We find a significant positive relationship between affiliated donations and future crash risk. The relationship is more significant for firms with weak internal governance and limited external monitoring, when affiliated directors serve on the audit committee, and in non-state-owned enterprises. Overall, our findings suggest that the social ties built through affiliated donations undermine rather than enhance director monitoring, and that agency theory has more explanatory power than resource dependence theory for understanding the impact of affiliated donations on stock price crash risk.

This study investigates the impact of employee ownership on firms’ investment responsiveness to stock market feedback. Using data from Chinese listed firms, we find that employee ownership significantly enhances the sensitivity of corporate investment to Tobin’s q. This effect is more pronounced in firms with higher information asymmetry, greater labor intensity, weaker corporate governance, and higher financial distress risk. While employee ownership is linked to increased subsequent profitability volatility, it also mitigates financial mismatch and downside operating risk. Our findings also suggest that employee ownership drives a shift in corporate strategy, leading to more aggressive approaches and improved risk preferences. These results highlight the role of employee ownership in mitigating agency problems and enhancing firms’ ability to incorporate market information into investment decisions.

Investors’ prior experiences with a stock substantially affect their willingness to repurchase it. This paper explores the repurchase effect, a psychological bias in which investors are reluctant to repurchase stocks that have appreciated after a prior sale. To quantify this bias, we develop a novel stock-level measure, termed Repur, and investigate its implications for cross-sectional asset pricing. Our findings show that stocks with higher Repur tend to experience reduced future buying pressure from investors, which in turn results in lower subsequent returns. Economically, long-short portfolios based on Repur yield annualized abnormal returns exceeding 23% for equal-weighted and 11% for value-weighted risk-adjusted returns. Further analyses show that the pricing effect of Repur is more pronounced following periods of high investor sentiment, for stocks with greater arbitrage constraints, and for firms with smaller investor bases. Out-of-sample evidence from China confirms the significant pricing impact of the repurchase effect.

This study integrates microstructure theory with asset pricing to investigates how the idiosyncratic volatility (IVOL) puzzle operates through specialized liquidity risk channels in China’s A-shares market. We employ intraday transactions data to perform a novel decomposition of liquidity into its variable (informational) and fixed (transitory) components. We show that the anomalous negative relationship between IVOL and future returns emerges from the intricate interaction of liquidity risk exposure, information and arbitrage constraints, and measurement biases. Specifically, the variable component tied to informed trading and adverse selection exposes high-IVOL stocks to greater arbitrage risk during liquidity shocks, while the fixed component exacerbates their vulnerability to short-term market-making cost fluctuations. Our results reveal that the IVOL puzzle is not a statistical artifact but a rational pricing phenomenon driven by omitted liquidity risk, mediated by the country’s unique institutional environment and monetary conditions.

This paper investigates whether firm-level freight activity captures corporate fundamentals and predicts stock returns. Using smartphone geolocation data of truck drivers from 2019 to 2024, we construct a novel freight growth index (FGI) to quantify firms’ freight activity in the Chinese stock market. We find that firms’ freight growth is strongly associated with current operating performance and predicts future stock returns. A long-short portfolio sorted on FGI generates significant risk-adjusted monthly returns ranging from 57 to 72 basis points. Further evidence suggests that freight growth forecasts earnings announcement returns and is more predictive for firms with low information transparency. Moreover, freight growth provides incremental information in predicting stock returns beyond analyst forecasts. Our findings highlight that firm-level freight activity contains novel insights into firm fundamentals and stock pricing.

We interpret industry discount rates as proxies for value investment, grounded in Q theory, while capturing gambling preferences through salience theory. Integrating these perspectives, we propose a novel asset pricing model (ST-ICAPM) that unifies value investment and salience factors, evaluating its pricing efficacy across Chinese industries from 2004 to 2023. Empirical results show that investment factors tend to negatively predict future returns, while growth factors command risk premia. However, profitability factors exhibit limited explanatory power. Investor expectations are primarily driven by profit growth, emphasizing the need to enhance profit stability for a value-oriented market. Salience intensity, especially when measured via eigenvector centrality within industry networks, serves as a strong negative predictor of returns, emphasizing the importance of conceptual connections over purely economic linkages in shaping investor behavior. Robust tests confirm that the ST-ICAPM outperforms benchmark models (FF3, CARHART4, FF5, ICAPM, and STCAPM) in terms of pricing power. Our findings emphasize the need to promote value investing and restrain gambling behavior as essential strategies to cultivate a resilient capital market in China.

This study examines the role of financial derivatives in managing operational and financial risks within China's chemical manufacturing sector. While prior research has primarily focused on financial determinants of hedging decisions, we highlight the significant influence of operational metrics—particularly inventory levels and turnover rates—in shaping firms’ engagement in derivatives markets. Drawing from a sample of 289 publicly listed chemical firms from 2016 to 2022, we employ probit regression and K-means clustering to explore how operational and financial factors jointly determine derivatives adoption. Our empirical results reveal that operational metrics have a non-negligible impact on hedging decisions. Specifically, inventory and turnover rates emerge as primary determinants of firms' initiatives, while pre-tax operating profit remains significant from a financial perspective. The moderation analysis of cash flow reveals that financially constrained firms prioritize derivatives for operational risk mitigation, while resource-abundant firms employ them selectively for strategic optimization. Furthermore, our robustness tests, which control for geographical distinctions and the COVID-19 effect, confirm that firm-specific operational characteristics consistently dominate firms' hedging decisions despite regional heterogeneity. Finally, clustering analysis underscores the interplay between operational efficiency and capital robustness, showing that firms exhibiting superior operational efficiency and capital robustness demonstrate higher engagement in derivatives hedging. These findings contribute to the corporate risk management literature by expounding on the primacy of operational considerations in derivatives usage, particularly in asset-intensive industries. The study also provides practical implications for manufacturing firms navigating volatile market conditions, emphasizing that integrating operational and financial strategies is crucial for effective risk management.

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.

Using proprietary data from China’s interbank bond-pledged repo market, we show that the interest-rate risk and credit risk of the pledged bond are key determinants of repo pricing. From a bond-option perspective, we develop arbitrage-free models that anchor the repo yield curve to the pledged-bond yield curve. The fair repo haircut is interpreted as the per-unit price of a call option on the pledged bond. We extend this framework to incorporate bail-in or bail-out potential, which enhances the model’s empirical performance and provides a novel explanation for systematic repo cheapness and existence of negative haircuts.