One commonly adopted practice in classifying retail and institutional orders is based on order size. Due to the increasing use of small orders by institutional investors, size-based classification can lead to an error rate over 20%. To improve the accuracy of the order size algorithm, we study the order patterns and uncover a higher tendency of retail investors trading in multiples of 500 shares. We modify the original order size algorithm by incorporating the feature of share roundedness. The modified algorithm substantially improves the accuracy of identifying retail and institutional investors in China. Order imbalances derived from the modified algorithm better predict future stock returns.

We examine the financial and real implications of bank CEOs’ social minds induced by female socialization on sustainable loans. We find evidence of an economically sizable and statistically significant bank CEO-daughter effect in lending behaviours, controlling for borrower industry as well as bank characteristics. In specific, the “greenness” of a bank is significantly higher, when the lead bank CEO parents a first-born daughter compared to an otherwise lender. Looking at the specific lending contracts written by banks, we find that lead banks whose CEOs parent a first-born daughter provide loans with lower spread, fewer financial covenants, and less likely to require collateral, for borrowers with better Corporate Social Responsibility (CSR) performance. Furthermore, we find that bank CEOs’ parenting experience with first-born daughters would predict borrowing firms’ future CSR performance positively, suggesting banks with CEOs raising a first-born daughter would promote the corporate social activities of borrowers.

This study explores the role of sentiment in predicting future stock return volatility in the Chinese A-share market. Specifically, we conduct a composite sentiment index capturing both investor and manager sentiment. The former is measured by overnight returns, and the latter is measured by a textual tone based on the information in the Management Discussion and Analysis section of the annual reports. Empirically, we find that the composite index is positively associated with subsequent stock realized volatility and the result remains robust after controlling for a set of firm characteristics and state ownership. Besides, the result also shows that investor attention can help dissect the sentiment—volatility relation.

This paper presents an innovative Comprehensive Growth Dynamic Model (CGDM). CGDM is designed to simulate the temporal evolution of an event, incorporating economic and social factors. CGDM is a regression of logistic regression, power law regression, and Gaussian perturbation term. CGDM is comprised of logistic regression, power law regression, and Gaussian perturbation term. CGDM can effectively forecast the temporal evolution of an event, incorporating economic and social factors. The illicit trade in wildlife has a deleterious impact on the ecological environment. In this paper, we employ CGDM to forecast the trajectory of illegal wildlife trade from 2024 to 2034 in China. The mean square error is utilized as the loss function. The model illuminates the future trajectory of illegal wildlife trade, with a minimum point occurring in 2027 and a maximum point occurring in 2029. The stability of contemporary society can be inferred. CGDM's robust and generalizable nature is also evident.

This paper studies the transmission of monetary policy to the stock market through investors’ discount factors. To isolate this channel, we investigate the effect of US monetary policy surprises on the ratio of prices of the same stock listed simultaneously in Hong Kong and Mainland China, and thereby control for revisions in cash-flow expectations. We find this channel to be strong and asymmetric, with the effect driven by surprise monetary policy interest rate cuts. A 100 basis point surprise cut results in a 30 basis point increase in the ratio of stock prices over 5 days. These results suggest significant slow-moving reductions in stock market risk premia following accommodating monetary policy surprises.

This paper reconciles the debates on carbon return estimation by introducing the concept of equity duration. We demonstrate that emission level and emission intensity yield divergent results for green firms, driven by inherent data problems. Our findings reveal that equity duration effectively captures the multifaceted effects of carbon transition risks. Regardless of whether carbon transition risks are measured by emission level or emission intensity, brown firms earn lower returns than green firms when the equity duration is long. This relationship reverses for short-duration firms. Our analysis underscores the pivotal role of carbon transitions’ multifaceted effects on cash flow structures in understanding the pricing of carbon emissions.

Using iterative experiments to uncover causal links between critical policy details and outcomes helps to optimize policy design. This paper studies a large-scale staged fiscal stimulus program conducted during the COVID-19 pandemic, in which a provincial government in China disbursed digital coupons to 8.4 million individual accounts in consecutive waves and updated the program design each time. We find that ruling out unproductive program features leads to a pattern of increasing treatment effects over the waves and that program design matters more than the size of the fiscal stimulus in boosting spending. Our results show that (i) general coupons with no constraints on where the vouchers can be redeemed are more effective than specialized coupons in stimulating consumption in the targeted sectors; (ii) coupon packets with fewer denominations and shorter redemption windows tend to be more effective; and (iii) low-income residents and non-local residents are equally or even more responsive to the coupon program than other groups. Our results illustrate that generating variations in iterative policy experiments, combined with a timely assessment of individuals’ responses to marginal incentives, optimizes program design.

In order to clarify the effect and mechanism of servitization level and digital transformation on the performance of listed sporting goods manufacturing enterprises in China, the index of the degree of digital transformation is constructed based on the data of 31 sporting goods manufacturing enterprises listed on Shanghai and Shenzhen A shares and the New OTC Market in China, taking the proportion of service business income in enterprise operating income as the index of servitization level, by analyzing the semantic expression of national policy related to digital economy and collecting "digital" category keywords in enterprise annual report with the help of crawler technology, then, the influence of servitization level and digital transformation on enterprise performance is discussed, and whether digital transformation plays a moderating effect between servitization and enterprise performance is tested. The results show that the servitization level suppresses the performance of listed sporting goods manufacturing enterprises, and there is a "Servitization Paradox" phenomenon. The degree of digital transformation has a positive U-shaped impact on enterprise performance, and at the same time, digital transformation has a weak positive moderating effect on servitization level and enterprise performance.

Using data from Chinese A-share listed firms from 2015 to 2022, we employ a difference-indifferences model to empirically examine the impact of bankruptcy regimes, marked by the establishment of bankruptcy courts, on firms’ total factor productivity (TFP). The results show a significant decline in TFP among firms in regions following the establishment of bankruptcy courts. This finding remains valid after a series of robustness tests. Mechanism tests reveal that establishing bankruptcy courts increases firms’ risk aversion incentives by endowing creditors with excessive rights. Consequently, firms tend to reduce liabilities, curtail R&D investment, and accumulate liquid assets as coping measures, ultimately contributing to a decline in TFP. Furthermore, this effect is more pronounced for firms with high financial risk. However, the improvement of the market mechanism can alleviate the negative impact of bankruptcy courts excessively strengthening creditor protection. Specifically, when firms are located in regions with weak government intervention and strong financial development, as well as in market environments with low uncertainty and strong competition, this negative impact can be mitigated. These findings provide fresh insights into the dual nature of creditor protection and offer valuable references for governments to improve the bankruptcy legal system.

Using subsidiary-level data of 3,863 Chinese nonfinancial listed firms, we find their capital expenditures increase with foreign sales, and the difference arises from the investments of the firms’ foreign subsidiaries. We show that the foreign sales-foreign investment association becomes more sensitive when the economic policy uncertainty (EPU) increases in the domestic market. However, foreign EPU does not play such a significant role. We provide one possible explanation that due to global diversification, MNEs can hedge foreign EPU using their international subsidiary network, resulting in the overall investments unchanged. However, given China’s tight regulatory capital controls, the MNEs may be less able to hedge the domestic EPU, so that they reallocate investments from the domestic markets to the foreign markets, consistent with the transaction cost assumption underlying the real options theory. Robust tests show that access to foreign capital, profitability and institutional factors have little explanatory power over the MNEs’ foreign investment.