Search Results (406)

An important element in the Constitution of the People’s Republic of China is the guarantee of gender equality in all fields. The principle is not reflected in terms of corporate governance and senior management, however. A study of the largest 400 companies listed on Chinese stock exchanges shows far fewer female board members and senior managers than male counterparts and only a small improvement over the course of a decade. A comparison of gender balances in terms of a range of variables, including stock exchange listing, industry type, and ownership type, reveals better balances in wholly privately owned firms than in those with controlling state interests. Subject to intervening government policies to promote state-owned enterprises over private sector counterparts, the pattern over the decade studied suggests there is a possibility privately owned enterprises may gradually displace state-owned companies in the largest 400 group and gender balances in senior roles in the largest 400 group will consequently improve. Full article

Chinese public building carbon emissions trading system (CETS) pilots have employed different carbon quota methods over more than ten years. However, there are few quantitative comparisons on CETS emission reduction effects in different pilots based on the carbon quota analysis. This paper first calculates the annual carbon quotas of public buildings based on carbon quota allocation methodologies from municipal policy documents. Then, the factors affecting the carbon quotas of public buildings are analyzed. Finally, the emission reduction effects are analyzed and compared between the pilots. The findings are concluded as follows: (1) Public building stock area and energy efficiency demonstrate significant effects on the carbon quota. (2) The average annual carbon quota deficits of public buildings were 929,800 tons in Beijing and 596,000 tons in Shanghai, while the carbon quota was an annual surplus of 296,400 tons in Shenzhen, indicating that carbon quota allocations in Beijing and Shanghai pilots are more conducive to promoting the active participation of high-emission enterprises. (3) The emission reduction effect in Beijing is most pronounced, followed by Shanghai and finally Shenzhen. Accordingly, the reasons for the difference in emission reduction effects are analyzed. This study contributes to the carbon quota allocation and emission reduction of public buildings. Full article

This paper applies the Multivariate Stochastic Volatility (MSV) model, alongside its extended DGC-t-MSV model, and integrates Bayesian methods with MCMC techniques to develop the DGC-t-MSV-BN model. This model is specifically designed to analyze the volatility spillover effects between stock and futures markets. Key findings are as follows: (1) Significant volatility spillover effects exist from futures market to stock market. Notably, the spillover effects among the Chinese carbon futures market and both the Chinese and international stock markets are stronger than those within the Chinese carbon futures market, as well as the international gold and crude oil futures markets. (2) A notable negative volatility spillover effect is observed between Chinese carbon futures market and the international stock market. Conversely, a significant positive volatility spillover effect exists in the Chinese carbon futures market and the Chinese stock market. (3) The Chinese carbon futures market, as an emerging sector, displays high volatility and immaturity, yet it is developing at a rapid pace. Full article

Tin is an indispensable metal for contemporary society owing to its extensive application. China is a major tin manufacturer and consumer worldwide. Nonetheless, the crucial characteristics of its tin metabolism remain limited. Therefore, a dynamic material flow analysis (MFA) from 2001 to 2022 was performed in this study to trace China’s tin flows and stocks. Findings show that China became a net tin exporter from a life cycle perspective, and annual tin consumption embodied in various final products varied between 49.3 kilo tons (Kt) in 2001 and 161.5 Kt in 2022, with home appliances and electronics being the dominant consumption sectors. A total of 913.3 Kt of tin became in-use stocks. In addition, the imported tin embodied in various final products varied between 13.9 Kt in 2001 and 21.6 Kt in 2022, with machinery being the dominant consumption sector. The exported tin embodied in various final products varied between 12.0 Kt in 2001 and 76.3 Kt in 2022, with machinery being the dominant consumption sector. Finally, this study proposes some suggestions, in view of the Chinese reality, like enhancing tin recycling, promoting tin geological prospecting, optimizing the structure of the tin trade, and promoting regional cooperation, to improve the supply security of tin resources. Full article

As investment portfolios become increasingly diversified and financial asset risks grow more complex, accurately forecasting the risk of multiple asset classes through mathematical modeling and identifying their heterogeneity has emerged as a critical topic in financial research. This study examines the volatility and tail risk of gold, crude oil, Bitcoin, and selected stock markets. Methodologically, we propose two improved Value at Risk (VaR) forecasting models that combine the autoregressive (AR) model, Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model, Extreme Value Theory (EVT), skewed heavy-tailed distributions, and a rolling window estimation approach. The model’s performance is evaluated using the Kupiec test and the Christoffersen test, both of which indicate that traditional VaR models have become inadequate under current complex risk conditions. The proposed models demonstrate superior accuracy in predicting VaR and are applicable to a wide range of financial assets. Empirical results reveal that Bitcoin and the Chinese stock market exhibit no leverage effect, indicating distinct risk profiles. Among the assets analyzed, Bitcoin and crude oil are associated with the highest levels of risk, gold with the lowest, and stock markets occupy an intermediate position. The findings offer practical implications for asset allocation and policy design. Full article

Urbanization is accompanied by an increased use of building materials. However, the lack of high-resolution building material stock (BMS) maps limits our understanding of the relationship between BMS and urban heat. To address this, we estimated BMS across eight typical Chinese megacities using multi-source geographic data and investigated the relationship between BMS and land surface temperature (LST). The results showed that (1) the total BMS for the eight megacities was 9175.07 Mt, with Beijing and Shanghai having the largest shares. While BMS correlated significantly with population, growth patterns varied across cities. (2) Spatial autocorrelation between BMS and LST was evident. Around 16% of urban areas exhibited High–High clustering between BMS and LST, decreasing to 10% during the daytime. The relationship between BMS and LST is nonlinear, and also prominent at night, especially in Beijing. (3) Diverse building forms, especially building height, contribute to a nonlinear relationship between BMS and LST. Full article

Seahorse (Hippocampus spp.) is popular in the markets of traditional Chinese medicine, aquarium, and curio. In order to protect wild stocks and still meet the market demand, China attempted the large-scale cultivation of seahorses in the early 21st century and achieved it in the 2010s. However, in recent years, two new issues have gradually emerged in Chinese seahorse cultivation. One is that the juveniles are prone to disease during diet conversion, and the other is that the reproductive performance of broodstocks is significantly reduced. With the aim to provide some measures that can alleviate these issues, in the present study, we used lined seahorse (Hippocampus erectus, a species widely cultured in China) as the experimental subject and Astragalus polysaccharides (APSs) as the immunostimulant to test whether APSs could improve the immune-health status and reproductive performance of seahorses. The measured indices for reproductive performance included ovarian lipid content, assessment time required before mating for paired male and female seahorses, mating success rate, brood size, and newborn body height. The results showed that for juveniles during diet conversion, their body weight, survival rate, plasma immunocytokine contents (interleukin-2, interferon-α, and immunoglobulin M), and alpha diversity indices (Simpson and Pielou’s-e) of the intestinal microbiota were significantly higher than those of the control group after dietary APSs. For broodstocks, compared with the control group, the expression of lipid substances in the ovary was significantly upregulated, the assessment time was significantly shortened, and the body height of their newborns was significantly increased in the APS group. These results demonstrate that APSs could indeed improve the immune-health status and reproductive performance of seahorses, providing guidance for addressing existing issues in seahorse cultivation. Full article

This paper examines the firm-level carbon intensity of 83 constituent stocks in the Hang Seng Index, constructs two distinct indexes from the 20 firms with the highest and lowest carbon intensities, and analyzes the connectedness of their annualized daily volatilities with four key external factors over the past 15 years. Our findings reveal that low-carbon stocks—often represented by high-tech and financial firms—tend to exhibit higher volatility, reflecting their more dynamic business environments and greater sensitivity to changes in revenue and profitability. In contrast, high-carbon companies, such as those in the utilities and energy sectors, display more stable demand patterns and are generally less exposed to abrupt market shocks. We also find that oil price shocks result in greater volatility spillovers for low-carbon stocks. Among external influences, the U.S. stock market and Treasury yield exert the most significant spillover effects, while crude oil prices and the U.S. dollar–Chinese yuan exchange rate act as net volatility recipients. Full article

Forecasting financial time series is challenging due to their intrinsic nonlinearity, high volatility, and complex dependencies across temporal scales. This study introduces MSGformer, a novel hybrid architecture that integrates multi-scale graph neural networks (MSGNet) with Transformer encoders to capture both local temporal fluctuations and long-term global trends in high-frequency financial data. The MSGNet module constructs multi-scale representations using adaptive graph convolutions and intra-sequence attention, while the Transformer component enhances long-range dependency modeling via multi-head self-attention. We evaluate MSGformer on minute-level stock index data from the Chinese A-share market, including CSI 300, SSE 50, CSI 500, and SSE Composite indices. Extensive experiments demonstrate that MSGformer significantly outperforms state-of-the-art baselines (e.g., Transformer, PatchTST, Autoformer) in terms of MAE, RMSE, MAPE, and R². The results confirm that the proposed hybrid model achieves superior prediction accuracy, robustness, and generalization across various forecasting horizons, providing an effective solution for real-world financial decision-making and risk assessment. Full article

In this article, an R-vine copula model is proposed to detect the nonlinear interrelationships between the oil market and five Chinese new-energy-related stock markets from 2017 to 2022, i.e., photovoltaic, new energy vehicles, energy storage, wind power, and nuclear power industries. Firstly, the transmission of downward and upward risk spillover effects (RSEs) is measured from the oil market to the five Chinese new-energy-related stock markets. Subsequently, a CoVaR backtesting methodology is developed to demonstrate the availability of the R-vine copula-CoVaR model. The empirical studies strongly show that the oil market exhibits a significant asymmetric RSE on the five Chinese new-energy-related stock markets. Furthermore, different Chinese new-energy-related stock markets have varying responses to the positive and negative impacts of the oil market. Specifically, the photovoltaic, energy storage, and wind power industries are more sensitive to such adverse effects. However, the new energy vehicle and nuclear power industries are more likely to be positively affected. Full article

In the context of global climate change and the escalating energy crisis, the development of new energy vehicles (NEVs) has become a critical strategy for China to foster green transformation and achieve its carbon neutrality goals. This study focuses on A-share-listed NEV companies in China from 2015 to 2023, specifically those listed on the Shanghai or Shenzhen Stock Exchange and subject to domestic regulatory standards and disclosure requirements. These firms were selected due to the representativeness, availability, and quantifiability of their data. A super-efficient-network SBM model based on undesirable outputs and the Malmquist index were employed to assess the static and dynamic green technology innovation efficiency of 260 NEV enterprises. Additionally, the Tobit regression model was applied to analyze the influencing factors. The findings reveal that the overall green technology innovation efficiency of Chinese NEV enterprises is relatively low and has exhibited a declining trend over the years. Furthermore, the efficiency of enterprises in the western regions surpasses that of those in the eastern and central regions. Key factors, including government support, enterprise scale, and R&D investment, significantly inhibit the green technology innovation efficiency of firms. Based on these findings, this paper recommends prioritizing the innovation of core technologies, addressing regional disparities in development, and implementing tailored policies to enhance the green technology innovation efficiency and economic performance of NEV enterprises. Full article

This study investigates the causal impact of stock price crash risk on the cost of equity (COE) in China’s segmented A- and B-share markets with an emphasis on ownership structures and market regimes. Employing a bootstrap panel Granger causality framework, Markov-switching dynamic regression, and panel threshold regression models, the analysis reveals that heightened crash risk significantly increases COE, with the effects being more pronounced for A-shares because of domestic investors’ heightened risk sensitivity. This relationship further intensifies in bull markets, where investor optimism amplifies downside risk perceptions. Ownership segmentation plays a critical role, as foreign investors in B-shares exhibit weaker reliance on firm-level valuation metrics, favoring broader risk-diversification strategies. These findings offer actionable insights into corporate risk management, investor decision making, and policy formulation in segmented and emerging equity markets. Full article

Stone mastic asphalt (SMA) is the most widely adopted asphalt mixture on highway pavement in China. However, the cost of SMA is rising continually due to the increasing shortage of high-quality basalt aggregate. On the other hand, China’s steel slag and reclaimed asphalt pavement (RAP) stock is abundant, and steel slag has excellent strength and wear-resistant performance, which can fully or partially replace part of the basalt aggregate. The content of asphalt may be increased due to the porosity of the steel slag. If fine RAP rich in asphalt is also used for SMA, it can partially fill the voids of steel slag and reduce the amount of new asphalt and fine aggregate. For this objective, SMA 13 was designed with two particle sizes of coarse steel slag aggregate (5–10 mm, 10–15 mm) and one fine RAP (0–5 mm), named SR-SMA. The fundamental pavement performance of SR-SMA was evaluated through a wheel-tracking test, low-temperature beam bending test, freeze–thaw indirect tensile test, and four-point bending fatigue test. For comparison, the mix design and performance tests of two SMAs involving coarse steel slag and fine basalt aggregate (named SB-SMA), and coarse and fine basalt aggregates (named B-SMA), respectively, were conducted. The results indicated that SR-SMA (dynamic stability of 4865 passes/mm) shows the best rutting resistance, followed by SB-SMA (dynamic stability of 4312 passes/mm), and B-SMA (dynamic stability of 4135 passes/mm) comes in last. Additionally, the dynamic stability values of three SMAs have significant differences. SR-SMA has better low-temperature cracking resistance with a failure strain of 3150 με, between SB-SMA and B-SMA (failure strain values are 4436, 2608 με). Compared to B-SMA and SB-SMA, the moisture stability of SR-SMA is relatively poor but meets Chinese specification. While the fatigue resistance of SR-SMA is the worst among three SMAs, their differences are insignificant. Furthermore, SR-SMA reduces material cost by approximately 35% per ton compared to conventional B-SMA. Overall, SR-SMA is cost-effective and can be used as an alternative material to traditional B-SMA. Full article

This study investigates whether and how the complexity of derivative use influences the stock price crash risk in China’s capital market, a critical question given the growing use of derivatives in emerging economies where governance structures and disclosure standards vary widely. While prior research has examined the binary effects of derivative usage, limited attention has been paid to the multidimensional complexity of such instruments and its informational consequences. Using a novel hand-collected dataset of annual reports from Chinese A-share-listed firms between 2010 and 2023, we develop and implement new indicators that capture both the economic complexity (diversity and scale) and accounting complexity (reporting dispersion and fair-value hierarchy) of derivative use. Our analysis shows that higher complexity is associated with a significantly lower likelihood of stock price crashes. This effect is especially pronounced in non-state-owned firms and those with weaker internal-control systems, suggesting that derivative complexity can enhance information transparency and serve as a substitute for other governance mechanisms. These findings challenge the conventional view that complexity necessarily increases opacity and highlight the importance of disclosure quality and institutional context in shaping the market consequences of financial innovation. Full article

As the largest terrestrial carbon pool, forest ecosystems play a pivotal role in climate change mitigation through greenhouse gas regulation. This study estimated the carbon sequestration potential of arbor forests at the county-level scale in Mentougou District, Beijing, based on subcompartment vector data from forest surveys and employed the Intergovernmental Panel on Climate Change (IPCC) carbon stock–biomass difference methodology. Additionally, using 2020 as the baseline year, the research projected carbon sink potential and carbon sequestration–oxygen release values for 2030 and 2060 by applying the carbon stock change methodology and the carbon sequestration–oxygen release value methodology. The results showed that there is a total carbon stock of 2.198 million tonnes (Mt) C in Mentougou, with an average storage density of 33.4 t C/ha. Natural broadleaf forests constituted the dominant carbon pool (79.2%), followed by planted coniferous stands (11.9%), collectively accounting for 91.1% of the regional arboreal carbon storage. In the future, the district’s arboreal carbon stock is projected to reach 3.17 Mt C in 2030 and 4.82 Mt C in 2060, with cumulative sequestration reaching 0.97 Mt C and 2.63 Mt C, respectively. It is evident that the carbon storage dynamics in Mentougou were governed by three principal determinants: (1) natural broadleaf forests dominate carbon storage (1.559 Mt C) in Mentougou, exceeding planted coniferous stands by 6.7-fold; (2) carbon storage decreases progressively with younger age classes, while carbon density increases steadily with stand maturity; (3) mid-elevation slopes (600–1200 m) concentrate 48% of regional stocks, with shaded slopes being optimal carbon sinks, and slope position gradients reveal topography-driven carbon accumulation patterns, confirming scale-dependent material transport effects. The value of carbon fixation and oxygen release of existing arbor forests in Mentougou District was CNY 6.12 billion, and this is predicted to reach CNY 8.84 billion by 2030, with a further anticipated increase to CNY 13.45 billion by 2060. Our analysis provides empirical evidence and quantitative support for forestry carbon sink initiatives at the regional scale and thus promotes the achievement of dual-carbon goals proposed by the Chinese government. Full article