While cities piloting China’s Social Credit System attract attention, rural areas in China are experimenting with reputation-based credit systems called ‘banks of virtue’. These local institutions unlock cheap loans and other benefits for citizens who prove virtuous character. Based on empirical data, this article investigates how banks of virtue combine techniques of metrics known from capitalist credit systems with an inherently localized and personal evaluation procedure. As hybrid forms of organizing access to credit, this article argues, banks of virtue of er an alternative, rural answer to the ‘right to credit’ that emerged in debates concerning capitalist economies. While they combine multiple goals of the national rural revitalization and Social Credit System strategies, such as the creation of a ‘civilized’ rural society and the allocation of credit to small businesses and households, their reliance on citizen participation casts doubts over their capacity to achieve these goals.

This study introduces a novel factor model based on self-attention mechanisms. This model effectively captures the non-linearity, heterogeneity, and interconnection between stocks inherent in cross-sectional pricing problems. The empirical results from the Chinese stock market reveal compelling ffndings, surpassing other benchmarks in terms of profftability and prediction accuracy measures, including average return, Sharpe ratio, and out-of-sample R2. Moreover, this model demonstrates both practical applicability and robustness. These results provide valuable evidence supporting the existence of the three aforementioned properties in crosssectional pricing problems from a theoretical standpoint, and this model offers a powerful tool for implementing profftable long-short strategies.

This study investigates the impact of the land rental market (LRM) on labor productivity in rural China. Particular attention is given to farm and non-farm labor productivity. Using 2012 household-level data and a multinomial endogenous switching treatment regression (MESTR) technique, we find that rural households renting-in farmland increased labor productivity in the farm sector by about 55%, while labor productivity in the non-farm sector decreased by about 6%. We also find that rural households renting-out farmland had lower labor productivity in both the farm and non-farm sectors by 13% and 9%, respectively. More family labor transferred from the farm to the non-farm sector after renting-out land.

This paper examines the effects of superstitious psychology on investors’ decision making in the context of Mercury retrograde, a special astronomical phenomenon meaning “everything going wrong”. Using natural experiments in the Chinese stock market, we find a significant decline in stock prices, approximately -3.14% in the vicinity of Mercury retrogrades, with a subsequent reversal following these periods. The Mercury effect is robust after considering seasonality, the calendar effect, and well-known firm-level characteristics. Our mechanism tests are consistent with model-implied conjectures that stocks covered by higher investor attention are more influenced by superstitious psychology in the extensive and intensive channels. A superstitious hedge strategy motivated by our findings can generate an average annualized market-adjusted return of 8.73%.

This paper investigates how noise trading behavior is influenced by limited attention. As the daily price limit rules of the Chinese stock market provide a scenario for the exhibition of salient payoffs, speculators elevate prices to attract noise traders into the market. Utilizing a series of distraction events stemming from mobile games as exogenous shocks to investors’ attention, we find that the gambler-like behavior, termed as “Hitting game” is crowded out. Consistent with our attention mechanism, indicators such as trading volume decline in response to these game shocks.

Drifting in the direction of earnings surprises for a prolonged period is a decades-puzzling financial anomaly, i.e., the “post-earnings-announcement drift” (PEAD). This paper provided a new simple measure of earnings surprise called ORJ. Based on ORJ, not only is the medium effect of investors’ attention on the relationship between earnings surprises and PEAD analyzed, but a tractable and profitable investing strategy is provided. Through comprehensive empirical analysis of the Chinese stock market, we found that i) both earnings surprises and investor attention can increase the degree of PEAD; ii) “good” (bad) earnings surprises strengthen (weaken) the degree of drift by attracting (decreasing) investor attention; it is asymmetric that the positive effects of “good” earnings surprises are stronger than that of “bad” earnings surprises on PEAD; and iii) the strategy obtains an average 6.78% return per quarter in excess of the market and only longs dozens of stocks . iv) Typical pricing factors such as the Fama-French three factors, illiquidity and company characteristics have little explanatory power for the returns of the strategy. This paper strongly shows the importance of monitoring overnight returns of earnings announcements to digging the unexpected information, reveals one mechanism of earnings surprises on PEAD and demonstrates the potential profitability of PEAD in the Chinese market.

This paper examines the different responses of local and foreign investors to host government risk perceptions in the context of extreme events. We develop COVID-19 attention indices that capture attention related to COVID-19 according to China Central Television (CCTV) news program and further construct the government’s risk perception (GRPC) measure about COVID-19. Given the cross-listed AH-shares in China, we find that GRPC caused the extreme movement of stock markets by applying the multi-quantile VaR Granger causality approach. The results show that the reaction of cross-listed stocks in the A-share market is more inflexible than that in the H-share market during the outbreak period of the pandemic, foreign investors follow GRPC as a weather vane than local investors, and both types of investors are more concerned about the pessimism of GRPC. In the period of epidemic normalization, local and foreign investors prefer the optimistic attitude conveyed by the Chinese government.

The asymmetric dissemination of information among financial firms in the financial market reflects their asymmetric response to the dissemination of both positive and negative information. However, it is worth studying whether this asymmetry will intensify or alleviate under different financial market conditions. Based on high-frequency minute stock price data of Chinese A-share listed financial firms from July 2020 to July 2023, we decompose the good and bad information, as well as the positive and negative volatility information in the return series. We utilize the quantile cross-spectral correlation method to construct an information overflow network at monthly intervals. We use the MVMQ-CAViaR model to estimate the value at risk (VaR) for various quantiles and build a risk spillover network that incorporates both positive and negative tail risk information, using the quantile dynamic SIM-COVAR-TENET model. We calculated the network dissemination efficiency of both good and bad information, including average speed, speed deviation, densest speed, and depth, to explore the changes in the asymmetry of good and bad information dissemination under different financial market conditions. We get that when the financial market is booming, financial firms’ asymmetric response to good and bad information will increase, and the firms will pay more attention to bad information. When the financial market declines, the asymmetric response of financial firms to good and bad information is diminished, and their sensitivity to both positive and negative information is heightened. In addition, the dissemination of bad information by firms in the five sub-financial industries across various markets exacerbates the asymmetric response of other financial firms to good and bad information. More importantly, the release of positive return information, negative volatility information, and highly negative tail risk information by the real estate financial firms all impact the asymmetric response of financial firms to good and bad information in a prosperous financial market. In recessionary financial markets, financial regulators can strategically release positive information to mitigate the decline in the financial market. Conversely, in a booming financial market, financial regulators should be cautious of the negative impact that bad information can have on financial firms, particularly in relation to the excessive growth of the real estate sector and the potential chain reaction of significant adverse events.

Amongst major economies, China has been taking a lead in the development of central bank digital currency (CBDC), which has generated widespread interest and impact around the globe. China’s CBDC, commonly known as e-CNY, is designed with several distinctive features, enabling it to compare favorably to other payment methods such as credit cards, mobile payment, unbacked cryptocurrency, and stablecoins. A variety of social, economic, political, and regulatory reasons can be identified to help explain China’s active pursuit of CBDC. However, the prospect of success will be affected by many factors and may vary between the domestic and international markets. This paper argues that the adoption of eCNY will likely succeed domestically, but may face more challenges in the international markets. The development of e-CNY seems to have created a catfish effect on other major economies in the race for CBDC. It is not fully clear, however, that the CBDC race will be better explained by the first-mover or the late-mover advantage theory. The CBDC project will have both public and private law implications, and several legal issues warrant particular attention in relation to the legal status of CBCD, the role and responsibility of the central bank, legal remedies for losses suffered by CBDC users from cybersecurity issues and operational problems, and the issue of data privacy and protection.

We investigate the impacts of anticipated government environmental audits (GEAs) on firm productivity. We use a 2009 policy set forth by China’s National Audit Office that required GEAs of local governments as an exogenous event to examine the effect of the policy announcement on firms’ total factor productivity (TFP). Our difference-in-differences tests indicate that TFP in heavily polluting firms improved more than other firms’ TFP after the announcement of the policy. We also find that to raise TFP, firms engage in green invention patents or receive government environmental subsidies. In addition, our cross-sectional analysis suggests that firms in regions where governments have strong environmental enforcement or that are in the eastern regions of China increase TFP more.