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学者姓名：黄志刚
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总量宽松货币政策难以在提振产出的同时兼顾风险防范,而定向调控货币政策能否兼顾二者,并纾解小微融资困境有待考证.文章构建包含银行对政策红利与坏账风险之间的权衡机制以及信贷偏好特征的DSGE模型,重点探讨定向降准与支小再贷款两类定向调控货币政策对小微企业的纾困效应.研究结果显示:从作用机制来看,定向调控货币政策通过信贷传导渠道与信号传递渠道均可促进经济增长,但二者在风险防控方面具有异质性.从纾困效应来看,定向降准对小微企业的纾困效果比支小再贷款政策更显著;从政策组合来看,总量宽松货币政策会削弱定向调控货币政策对小微企业的纾困作用,而定向调控货币政策之间搭配组合可进一步缓解小微企业融资困境并提高产出水平.此外,文章进一步从央行福利损失函数、政策前沿曲线以及社会福利分析等多重维度综合评判了定向调控货币政策的调控功效,进一步验证了研究结论的稳健性.
Keyword ：
DSGE模型 DSGE模型 信号传递渠道 信号传递渠道 信贷传导渠道 信贷传导渠道 稳增长 稳增长 防风险 防风险
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| GB/T 7714 | 李永建 , 黄祥钟 , 黄志刚 . 定向调控货币政策对小微企业的纾困效应研究 [J]. | 系统科学与数学 , 2025 , 45 (3) : 794-812 . |
| MLA | 李永建 等. "定向调控货币政策对小微企业的纾困效应研究" . | 系统科学与数学 45 . 3 (2025) : 794-812 . |
| APA | 李永建 , 黄祥钟 , 黄志刚 . 定向调控货币政策对小微企业的纾困效应研究 . | 系统科学与数学 , 2025 , 45 (3) , 794-812 . |
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It is an inevitable trend for the development of global digital economy to transform data into data assets and realize their transaction circulation. Aiming at the release of data value and the development of its transaction process, the concept of integrated score of data is proposed by combining integrated quality index containing four dimensions with data quantity. On this basis, data assets are priced according to the principle of profit maximization by constructing a nonlinear programming model. Among them, three types of pricing models are divided according to the heterogeneity of consumers' utility sensitivity, and the consumers' wiilingness to pay are adjusted based on business parameters using FAHP system. The proposed model is verified with the data of China's carbon emissions as the original data, combined with the KNN machine learning algorithm and a series of simulation analyses. In addition, multiple sets of heterogeneous data are tested. The results show that the quality, quantity and utility of data have an important impact on the pricing of data assets, and it is necessary to divide the utility sensitivity of consumers as well as take business parameters into consideration. The model proposed can also provide decision-making reference for data platforms.
Keyword ：
Accuracy Accuracy Business Business Costs Costs Data/Information Data/Information Data integrity Data integrity Data models Data models Evaluation/methodology Evaluation/methodology Feature extraction or construction Feature extraction or construction Financial Financial Machine learning Machine learning Marketing Marketing Mathematical models Mathematical models Model Validation and Analysis Model Validation and Analysis Nearest neighbor methods Nearest neighbor methods Pricing Pricing Sensitivity Sensitivity Simulation Output Analysis Simulation Output Analysis Training Training
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| GB/T 7714 | Lin, Juanjuan , Huang, Zhigang , Tang, Yong . Pricing for Data Assets Based on Data Quality, Quantity and Utility on the Perspective of Consumer Heterogeneity [J]. | IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING , 2025 , 37 (6) : 3641-3652 . |
| MLA | Lin, Juanjuan 等. "Pricing for Data Assets Based on Data Quality, Quantity and Utility on the Perspective of Consumer Heterogeneity" . | IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 37 . 6 (2025) : 3641-3652 . |
| APA | Lin, Juanjuan , Huang, Zhigang , Tang, Yong . Pricing for Data Assets Based on Data Quality, Quantity and Utility on the Perspective of Consumer Heterogeneity . | IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING , 2025 , 37 (6) , 3641-3652 . |
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This study constructs spillover indices from a volatility spillover network perspective using the Quantile Vector Autoregression (QVAR) model, capturing the RMB exchange rate's tail risk and time-frequency effects across varying shock sizes. Empirical results show that the QVAR-based spillover index more effectively captures the tail risk spillover effects across different quantiles. In the time domain, spillovers between RMB exchange rates are dynamic and particularly sensitive to extreme contingencies. In the frequency domain, RMB exchange rates demonstrate significant spillovers, primarily at low frequencies. During extreme upward events, dynamic observations show high-frequency spillovers surpassing low-frequency ones as dominant drivers in the tail spillovers of the RMB exchange rate. Additionally, the analysis of tail dependence indicators indicates a strong asymmetry in RMB exchange rate correlations, emphasizing market participants' heightened sensitivity to unfavorable shocks. These findings can serve as a reference for policymakers to strengthen risk management of the RMB exchange rate.
Keyword ：
Asymmetry Asymmetry Quantile connectedness Quantile connectedness RMB exchange rate RMB exchange rate Tail risk spillover Tail risk spillover
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| GB/T 7714 | Huang, Zhigang , Zhang, Weilan . Exploring the Spillover effects of tail risk fluctuations in the RMB exchange rate-The time-frequency and quantile connectivity perspective [J]. | RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE , 2024 , 72 . |
| MLA | Huang, Zhigang 等. "Exploring the Spillover effects of tail risk fluctuations in the RMB exchange rate-The time-frequency and quantile connectivity perspective" . | RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE 72 (2024) . |
| APA | Huang, Zhigang , Zhang, Weilan . Exploring the Spillover effects of tail risk fluctuations in the RMB exchange rate-The time-frequency and quantile connectivity perspective . | RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE , 2024 , 72 . |
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In recent years, the Chinese government has actively pursued the implementation of its 'dual -carbon ' strategy, concurrently establishing a national carbon emissions trading market. Accurate carbon price forecasts have become essential for policymakers and investors involved in related initiatives. Nevertheless, influenced by the interaction of various information sources, carbon trading prices exhibit non -linear and non-stationary characteristics, posing challenges for accurate prediction. Current research, centered around deep learning models, predominantly emphasizes intricate network structures, optimisation algorithms, and data decomposition. However, these models face a developmental bottleneck in extracting carbon price features and efficiently leveraging multi-source information. Consequently, novel ideas and methodologies are imperative. This study focuses on the Hubei and Guangdong regional carbon markets as research subjects. It develops a prediction framework based on a generative adversarial network model to capture the time -series change characteristics of carbon trading prices and the condition matrix. First, a generator prediction model is used to obtain the input matrix features and extract the time series features through a complex network to predict the carbon price data at the next moment using a fully connected layer. Second, a discriminator is utilised to distinguish between the actual values and the predicted values. The generator and the discriminator undergo continuous iterative training and alternate optimisation. This process aims to bring the generated prediction distributions closer to the actual sample data, resulting in more accurate final predictions. The empirical results convincingly show that the proposed model achieves unparalleled forecasting precision in both markets. The proposed model demonstrates the lowest MAE (0.804 and 0.839), lowest MAPE (0.023 and 0.018), lowest RMSE (1.174 and 1.383), and highest R 2 (0.971 and 0.989) across both markets, indicating superior predictive accuracy. Additionally, the proposed model consistently outshines traditional forecasting approaches across one-step, five-step, and ten-step forecasts, affirming its robustness and universal applicability in modelling carbon trading price series. The findings suggest that this study can aid policymakers in optimizing the carbon pricing system. Furthermore, it offers a reference for policymakers to comprehensively leverage external factors, such as regulating traditional energy prices, leveraging international carbon market experiences, and monitoring economic dynamics. This comprehensive strategy can streamline the exploration and management of carbon price fluctuations, ultimately strengthening the carbon market 's risk control system.
Keyword ：
Carbon emissions trading market Carbon emissions trading market Carbon price prediction Carbon price prediction Generative adversarial network Generative adversarial network Multi-source information Multi-source information
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| GB/T 7714 | Huang, Zhigang , Zhang, Weilan . Forecasting carbon prices in China's pilot carbon market: A multi-source information approach with conditional generative adversarial networks [J]. | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2024 , 359 . |
| MLA | Huang, Zhigang 等. "Forecasting carbon prices in China's pilot carbon market: A multi-source information approach with conditional generative adversarial networks" . | JOURNAL OF ENVIRONMENTAL MANAGEMENT 359 (2024) . |
| APA | Huang, Zhigang , Zhang, Weilan . Forecasting carbon prices in China's pilot carbon market: A multi-source information approach with conditional generative adversarial networks . | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2024 , 359 . |
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理论分析发现,资本市场定价偏离其内在价值会影响企业劳动投资效率,但在影响方向上存在促进还是抑制的不确定性.基此,利用2007-2019年中国A股非金融上市公司数据研究发现:实证结果支持了效率促进假说,资本市场错误估值每增加一个标准差,企业劳动投资效率将提高4.51％;机制检验表明,股价信息性和股权融资成本是两条促进作用渠道,前者表明管理者可以从股价中学习新的信息进而提高劳动投资决策效率,后者表明股价通过影响企业融资成本而提高劳动投资效率;资本市场错误估值既会抑制劳动过度投资,又会抑制劳动投资不足,对企业劳动投资效率的异质性影响表现为在股价高估、融资约束高和低壳溢价促进效应更显著.
Keyword ：
劳动投资效率 劳动投资效率 股价信息性 股价信息性 股价融资效应 股价融资效应 资本市场定价 资本市场定价 错误估值 错误估值
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| GB/T 7714 | 于然海 , 黄志刚 , 季国民 et al. 资本市场定价对企业劳动投资效率的影响研究 [J]. | 亚太经济 , 2023 , (5) : 33-46 . |
| MLA | 于然海 et al. "资本市场定价对企业劳动投资效率的影响研究" . | 亚太经济 5 (2023) : 33-46 . |
| APA | 于然海 , 黄志刚 , 季国民 , 唐勇 . 资本市场定价对企业劳动投资效率的影响研究 . | 亚太经济 , 2023 , (5) , 33-46 . |
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Current consensus protocols for permissionless blockchain cannot balance security, performance and centralization issues. In the paper, we present a reputation based consensus, FPoR, which combines reputation, committee based consensus, PBFT, reward and penalization mechanisms. FPoR can balance scalability, security and decentralization, and promote fairness, increase participation and strengthen security. Experiment results show that FPoR is with high performance and scalability, which can be used for permissionless blockchain. FPoR can also be extended to permissioned blockchain applications. (c) 2022 The Authors. Published by Elsevier B.V. on behalf of The Korean Institute of Communications and Information Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keyword ：
Blockchain Blockchain Consensus protocol Consensus protocol Fairness Fairness PoR PoR Reputation Reputation
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| GB/T 7714 | Zhang, Tao , Huang, Zhigang . FPoR: Fair proof-of-reputation consensus for blockchain [J]. | ICT EXPRESS , 2023 , 9 (1) : 45-50 . |
| MLA | Zhang, Tao et al. "FPoR: Fair proof-of-reputation consensus for blockchain" . | ICT EXPRESS 9 . 1 (2023) : 45-50 . |
| APA | Zhang, Tao , Huang, Zhigang . FPoR: Fair proof-of-reputation consensus for blockchain . | ICT EXPRESS , 2023 , 9 (1) , 45-50 . |
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PurposeThe operational framework of external financing in the correlation between the gender of entrepreneurs and firm performance remains to be resolved. This study aims to investigate the mediating effect of external financing on gender-based disparities in private firm performance and to explore its heterogeneity within the Chinese context.Design/methodology/approachBased on national data from the 10th to 13th Chinese Private Enterprise Survey, this study used a bootstrap-based mediation effect model to analyze the role of external financing as a mediator in the relationship between entrepreneur gender and firm performance.FindingsThis study found that external financing is a constructive mediator between entrepreneur gender and firm performance. Heterogeneity analysis revealed that external financing plays a complementary mediation role in the impact of entrepreneur gender on performance in West China. In the tertiary industry, external financing acts as the sole mediator for the impact of gender on firm performance. Notably, this mediating effect is present in non-startups but not in startups.Practical implicationsThe findings suggest that external financing can improve the firm performance of female entrepreneurs. Governments and policymakers should strengthen financial support for female entrepreneurs in West China, tertiary industry and non-startup enterprises.Originality/valueThis paper contributes to the literature on gender and corporate governance by shedding light on the mediating role of external financing in the relationship between the gender of business owners and firm performance.
Keyword ：
External financing External financing Firm performance Firm performance Gender Gender Mediating effect model Mediating effect model
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| GB/T 7714 | Huang, Lingyun , Liu, Jiankun , Huang, Zhigang . Gender, external financing and firm performance: evidence from Chinese private firms [J]. | GENDER IN MANAGEMENT , 2023 , 39 (3) : 370-387 . |
| MLA | Huang, Lingyun et al. "Gender, external financing and firm performance: evidence from Chinese private firms" . | GENDER IN MANAGEMENT 39 . 3 (2023) : 370-387 . |
| APA | Huang, Lingyun , Liu, Jiankun , Huang, Zhigang . Gender, external financing and firm performance: evidence from Chinese private firms . | GENDER IN MANAGEMENT , 2023 , 39 (3) , 370-387 . |
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With the rapid development of the global economy and stock market, stock investment has become a common investment method. People's research on stock forecasting has never stopped. Accurately predicting the dynamic fluctuation of stocks can bring rich investment returns to investors while avoiding investment risks. Machine learning is a relatively important research field in artificial intelligence today, which is mainly used to study how to use machines to simulate human activities. In recent years, with the continuous development of the economy, machine learning under artificial intelligence has developed comprehensively in different fields, and it has been widely used in the field of the financial economy. Machine learning under artificial intelligence is currently widely used in stock market volatility dynamics and related research. This paper applied machine learning to the prediction of the dynamic relationship of Asian stock market volatility and established a model for predicting the dynamic relationship of stock market volatility under machine learning. By using statistical theory, linear support vector machines, generalizable bounds, and other algorithms, it provides the theoretical basis and feasibility analysis for the model. Through investigation and research, this paper found that compared with ordinary forecasting model methods, the stock volatility dynamic trend forecasting model based on machine learning has a relatively complete forecasting effect, and the accuracy of the machine learning forecasting model was up to 52%. The lowest was 39%, the average prediction accuracy was 46.5%, and the accuracy was improved by 16.8%. This showed that the introduction of machine learning prediction models in the dynamic prediction model of Asian stock volatility is relatively successful.
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| GB/T 7714 | Lee, Peiyuan , Huang, Zhigang , Tang, Yong . Trend Prediction Model of Asian Stock Market Volatility Dynamic Relationship Based on Machine Learning [J]. | SECURITY AND COMMUNICATION NETWORKS , 2022 , 2022 . |
| MLA | Lee, Peiyuan et al. "Trend Prediction Model of Asian Stock Market Volatility Dynamic Relationship Based on Machine Learning" . | SECURITY AND COMMUNICATION NETWORKS 2022 (2022) . |
| APA | Lee, Peiyuan , Huang, Zhigang , Tang, Yong . Trend Prediction Model of Asian Stock Market Volatility Dynamic Relationship Based on Machine Learning . | SECURITY AND COMMUNICATION NETWORKS , 2022 , 2022 . |
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With the development of blockchain and digital currencies, central banks all over the world are accelerating the process of CBDC development. However, it is still controversial on adoption of blockchain in CBDC design. In the paper, we analyze both functional and non-functional requirements of CBDC design, and make a literature review on blockchain based CBDC schemes. Analysis findings show that permissioned blockchain is more suitable for CBDC than permissionless blockchain. Besides, there are some challenges in blockchain based CBDC, such as performance, scalability, and cross-chain interoperability. Our analysis is timely and can provide guidelines for blockchain based CBDC design. (C) 2021 The Authors. Published by Elsevier B.V. on behalf of The Korean Institute of Communications and Information Sciences.
Keyword ：
Blockchain Blockchain CBDC CBDC Central bank digital currency Central bank digital currency Distributed ledger Distributed ledger Fiat money Fiat money
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| GB/T 7714 | Zhang, Tao , Huang, Zhigang . Blockchain and central bank digital currency [J]. | ICT EXPRESS , 2022 , 8 (2) : 264-270 . |
| MLA | Zhang, Tao et al. "Blockchain and central bank digital currency" . | ICT EXPRESS 8 . 2 (2022) : 264-270 . |
| APA | Zhang, Tao , Huang, Zhigang . Blockchain and central bank digital currency . | ICT EXPRESS , 2022 , 8 (2) , 264-270 . |
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在总结福建省新兴产业发展成效和存在问题等的基础上,提出福建省新兴产业发展思路与布局,针对重点产业梳理了其重点发展领域,并指出了"十四五"时期和"面向2035年"的重点方向,最后提出了保障目标实现的重点措施。
Keyword ：
产业集群 产业集群 发展战略 发展战略 新兴产业 新兴产业 福建省 福建省
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| GB/T 7714 | 尤政 , 付贤智 , 冯记春 et al. 福建新兴产业发展战略研究 [J]. | 学会 , 2021 , (08) : 11-18 . |
| MLA | 尤政 et al. "福建新兴产业发展战略研究" . | 学会 08 (2021) : 11-18 . |
| APA | 尤政 , 付贤智 , 冯记春 , 黄志刚 , 郭太良 , 周源 et al. 福建新兴产业发展战略研究 . | 学会 , 2021 , (08) , 11-18 . |
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