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作 者:杨科[1,3] 刘鑫 田凤平[2] Yang Ke;Liu Xin;Tian Fengping(School of Economics and Finance,South China University of Technology,Guangzhou 510006,China;International School of Business and Finance,Sun Yat-sen University,Guangzhou 510275,China;Guangdong Laboratory of Artificial Intelligence and Digital Economy(Guangzhou),Guangzhou 510330,China)
机构地区:[1]华南理工大学经济与金融学院,广东广州510006 [2]中山大学国际金融学院,广东广州510275 [3]人工智能与数字经济广东省实验室(广州),广东广州510330
出 处:《系统工程学报》2025年第2期250-260,共11页Journal of Systems Engineering
基 金:国家自然科学基金资助项目(72201284,71991474);国家社会科学基金重大资助项目(19ZDA093);教育部人文社会科学研究规划基金资助项目(22YJA790077);广东省自然科学基金资助项目(2024A1515011002);中央高校基本科研业务费专项资金资助项目(QNTD202305).
摘 要:为防范和化解我国房地产业和银行业间的极端风险传染效应,以房地产指数和银行业指数数据为研究样本,在分位数回归框架下,构建多元多分位自回归风险价值模型,并运用分位数脉冲响应函数考察市场冲击对不同市场极端风险的动态影响过程.研究发现,在整个样本考察期,由于房地产业对银行业资金供给的高度依赖性,我国银行业对房地产行业具有单向的极端风险传染效应,而两者在平稳期和危机期具有显著不同的极端风险传染效应.这些研究结论可为我国房地产业和银行业的风险管控以及宏观调控政策的制定等方面提供经验证据.In order to prevent and resolve the extreme risk contagion effect between China’s real estate and banking sectors,this paper uses data from the real estate index and banking index in China as the research sample and employs the Multivariate and Multi-quantile Conditional Autoregression Value at Risk(MVMQ-CAViaR)model within the framework of quantile regression.Furthermore,the pseudo quantile impulse re-sponse function is used to study the effect of market shocks on the dynamic process of extreme risk in different markets.The results indicate that,during the entire sample period,due to the high dependence of real estate on the capital supply from banking,China’s banking sector exerts a unidirectional extreme risk contagion effect on the real estate industry.However,these two industries have significantly different extreme risk contagion effects in the stable period and the crisis period.Thesefindings can provide empirical evidence for the risk control of China’s real estate and banking industries and the formulation of macroeconomic control policies.
关 键 词:房地产业 银行业 风险传染 MVMQ-CAViaR模型 分位数回归
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