We revisit cross-asset time-series momentum (XTSM) and single-asset time-series momentum (TSM) in China's stock and bond markets. With a fixed-effects model, we find a positive momentum from bonds to stocks and a negative momentum from stocks to bonds, with both momentum persisting for no more than six months. By employing a cross-grouping method, we find that the choice of lookback periods and asset signals impacts the performance of XTSM and TSM. A comparison between XTSM, TSM, and time-series historical (TSH) portfolios reveals that XTSM outperforms in small/midcap stocks and government bonds, while its performance is weak in large-cap stocks and corporate bonds. A spanning test confirms that XTSM generates excess returns that other pricing factors can not explain. XTSM is more prone to momentum crashes. Increased market stress has similarly adverse effects on XTSM and TSM. Furthermore, Market illiquidity, IPO counts, new investor accounts, and consumer confidence index positively correlate with the returns of XTSM and TSM portfolios, while IPO first-day return and turnover rate correlate negatively. The effects of these sentiment indicators exhibit heterogeneity.

This study was conducted to understand better how rules influence China's energy performance; this research on these policies' efficacy that facilitating the transition to sustainable energy sources is of tremendous significance, particularly in light of the severe problems climate change poses. To determine whether or not strict regulations are beneficial to China's energy transition efforts, this research makes use of a substantial amount of data about China's environmental laws and environmental transition policies. This paper thoroughly analyses the impact of strict environmental regulations on various energy transition measures. These metrics include the availability of green energy, carbon emissions, and energy efficiency. The results provide insights into how environmental restrictions have affected China's transition to a different energy source. Policymakers and stakeholders may use this information to build efficient plans to expedite the transition to a low-carbon, renewable energy system in China and abroad.

Following the 18th National Congress of the Communist Party of China, the central government elevated the construction of ecological civilization to a central position within national strategy and introduced environmental governance indicators as mandatory criteria for evaluating officials, alongside GDP. These indicators served as an additional "threshold" for performance assessments. In the context of changes in the central government's development ideology and policies, this study utilizes matched data on the turnover of municipal party secretaries and local enterprise carbon emissions from 293 prefecture-level cities in China between 1990 and 2021. The research finds that turnovers of municipal party secretaries after the 18th National Congress have led to a significant reduction in carbon emissions from local enterprises, a trend that was not evident prior to the congress. This effect is more pronounced in situations where official turnover is primarily driven by promotion incentives, and less influenced by collusive behavior between the government and enterprises. Further analysis reveals that the decline in carbon emissions is more significant for private enterprises, non-heavy polluting enterprises, those located in the eastern region, and those in general prefecture-level cities, before and after municipal party secretary turnovers. This study enhances understanding of the relationship between the promotion incentives of Chinese officials and the carbon emissions of local enterprises, offering valuable insights for improving the official promotion assessment system and advancing local carbon reduction efforts.

We empirically examine how institutional investors react to adjustments in environmental policies in China. We observe a seemingly counterintuitive phenomenon: when environmental policies intensify, fund managers do not increase their holdings in high ESG-rated firms as might typically be expected; instead, they significantly divest from these firms. This behavior stems from the fact that, under stringent environmental policies, maintaining a high level of ESG investing leads to financial losses and fund outflows, especially in the short term, which impair fund managers’ compensation and raise career concerns. Further, within the context of environmental policy adjustments, our heterogeneity analysis tries to disentangle the true motivations behind institutional investors' ESG adoptions. We demonstrate that both pro-social preferences and financial incentives play pivotal roles, and that fund managers do not tolerate unlimited financial losses when ESG investing underperform. Our findings reveal the economic impact of environmental policies on institutional investors and shed light on the contentious and complex nature of the ESG concepts.

Central bank digital currency (CBDC) is intended to boost financial inclusion and limit threats to bank stability posed by private cryptocurrencies. Our study examines the impact of implementing CBDC on the bank stability of two countries in Asia and the Pacific, the People’s Republic of China (PRC) and India, that initiated research on CBDC within the last ten years (2013 to 2022). We construct a bank stability index by utilizing five dimensions, namely capital adequacy, profitability, asset quality, liquidity, and efficiency, using a novel “benefit-of-the-doubt” approach. Employing panel estimation techniques, we find a significant positive impact of adopting CBDC on bank stability and a moderating role of monetary policy. We also find that the effect is greater in India, a lower-middle-income country, than in the PRC, an upper-middle-income nation. We conclude that by taking an accommodative monetary policy stance, adopting CBDC favors bank stability. We confirm our results with various robustness tests by introducing proxies for bank stability and other model specifications. Our findings underscore the potential of adopting CBDC, when carefully managed alongside appropriate monetary policy, for enhancing bank or overall financial stability.

While many studies document cross-stock predictability where returns of some stocks predict returns of other similar stocks, most evidence comes from US markets. Following Chen et al. (2019), we identify peer firms based on historical return similarity and construct a Peer Return Gap (PRG) measure, defined as the difference between a stock’s lagged return and its peers’ returns. Our empirical evidence from Chinese markets shows that past-return-linked peers strongly predict focal firm returns. A long-short portfolio sorted on PRG generates an equal-weighted monthly return of 1.26% (t = 3.81) and a Fama-French five-factor alpha of 1.10% (t = 2.86). These abnormal returns remain unexplained by several alternative factor models.

This study investigates the role of contextual cues in memory-based decision-making within high-stakes trading environments. Using trade records from a large Chinese brokerage firm and a novel dataset on COVID-19 quarantines, we find that quarantine periods trigger the recall of previously traded stocks, increasing the likelihood of subsequent orders for those stocks. The observed patterns align more closely with similarity-based recall than with alternative channels. Welfare analysis reveals that these memory-induced trades lead to an annualized loss of approximately 70 percentage points for the representative investor's portfolio. We also find evidence at the market level: when the geographical distribution of quarantine risks is recalled, the probability of recalling the cross-sectional stock return-volume distribution from the same day increases by 1.6 percentage points. This study provides causal evidence from a real-world setting for memory-based theories, particularly similarity-based recall, and highlights a novel channel through which COVID-19 policies affect financial markets.

We study tail-risk contagion in Belt and Road (BRI) stock markets by conditioning on shocks from China and global commodities. We construct time-varying contagion indices from conditional higher co-moments (CoHCM) estimated within a DCC-GARCH model with generalized hyperbolic innovations, and apply them to daily data for 32 BRI markets. The higher-moment index isolates two channels: a China-driven financial-institutional channel and a WTI-driven commodity-real-economy channel, whereas a covariance benchmark fails to recover this separation. Furthermore, the system-GMM estimates link the China-conditional channel to institutional quality and financial depth, and the WTI-conditional channel to real activity. In out-of-sample portfolio tests, the WTI-conditional signal improves risk-adjusted performance relative to equally weighted and mean-variance benchmarks, while the China-conditional signal does not. Tail-based measurement thus sharpens identification of contagion paths and yields information that is economically relevant for risk management in interconnected emerging markets.

Contrary to the US, Chinese stock markets exhibit negative overnight returns that appear to be highly affected by the extent of information asymmetry. China's "T+1" trading rule, which prohibits same-day selling, exacerbates adverse selection for uninformed buyers by limiting them to react to post-trade information. An information asymmetry-driven price discount thus emerges at market open, generating negative overnight returns, which further decrease with information asymmetry. Consistent with adverse selection, empirical evidence reveals lower overnight returns during market declines and high-volatility periods, with robust negative relationship between overnight returns and information asymmetry proxied by firm size, analyst coverage, and earnings announcement proximity. A model is introduced to rationalize our findings. This framework also sheds light on China's "opening return puzzle", the phenomenon that prices rise rapidly in the initial 30 minutes of trading, by showing how reduced adverse selection enables rapid price recovery during opening session.

Background: How to cope with the rapid growth of LTC (long-term care) needs for the old people without activities of daily living (ADL), which is also a serious hazard caused by public health emergencies such as COVID-2019 and SARS (2003), has become an urgent task in China, Germany, Japan, and other aging countries. As a response, the LTCI (longterm care insurance) system has been executed among European countries and piloted in 15 cities of China in 2016. Subsequently, the influence and dilemma of LTCI system have become a hot academic topic in the past 20 years.Methods: The review was carried out to reveal the effects of the LTCI system on different economic entities by reviewing relevantliterature published from January 2008 to September 2019. The quality of 25 quantitative and 24 qualitative articles was evaluated using the JBI and CASP critical evaluation checklist, respectively. Results: The review systematically examines the effects of the LTCI system on different microeconomic entities such as caretakers or their families and macroeconomic entities such as government spending. The results show that the LTCI system has a great impact on social welfare. For example, LTCI has a positive effect on the health and life quality of the disabled elderly. However, the role of LTCI in alleviating the financial burden on families with the disabled elderly may be limited. Conclusion: Implementation of LTCI system not only in reducing the physical and mental health problems of health care recipients and providers, and the economic burden of their families, but also promote the development of health care service industry and further improvement of the health care system. However, the dilemma and sustainable development of the LTCI system is the government needs to focus on in the future due to the sustainability of its funding sources.