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作 者:夏佳佳 朱芬华[1] XIA Jiajia;ZHU Fenhua(School of Financial Technology,Anhui Business Vocational Technical College,Wuhu 241002,China)
机构地区:[1]安徽商贸职业技术学院金融科技学院,安徽芜湖241002
出 处:《成都工业学院学报》2023年第5期75-82,共8页Journal of Chengdu Technological University
基 金:安徽省教育厅人文社会科学研究重大项目(2022AH040341)。
摘 要:伴随着经济新常态,房地产及相关行业风险日益增加且趋于复杂,政府如果应对不当则较易引发系统性风险,而房地产供应链企业高度相关性以及信用违约网络搜索空间的巨大性对政府各项防范化解风险措施的实施提出了挑战。据此提出了房地产信用违约网络恢复模型框架,应用启发式搜索算法帮助政府开展救助,以有效防范化解金融系统性风险。选择60家A股上市企业财务数据作为研究样本,在随机生成违约场景后,根据2021年财务数据对信用网络恢复进行建模,实验结果表明:房地产供应链信用违约传染网络的恢复受到不同启发式策略的影响,而面向整体系统的启发式算法显著优于对单个企业实施的逐个救助。决策者应当充分考虑房地产供应链信用违约网络企业间的相互关联性,从而更有效的促进房地产供应链信用违约网络的恢复。With the new economic normal in China,real estate and related industries are increasingly risky and becoming more complex,if the government does not respond properly,it is likely to trigger systemic risks.while the high correlation of real estate supply chain enterprises and the huge search space of credit default networks challenge the implementation of various risk prevention and mitigation measures by the government.To address this challenge,a framework of real estate credit default network recovery model and applies heuristic search algorithms was proposed in this paper to help the government carry out bailouts to effectively prevent and mitigate financial systemic risks.60 A-share listed enterprises financial data was chosen as the research sample,and the credit network recovery was modeled based on 2021 financial data after randomly generating default scenarios.The experimental results show that the recovery of real estate supply chain credit default contagion network is affected by different heuristic strategies,and the heuristic algorithm for the overall system significantly outperforms the case-by-case bailout implemented for individual enterprises,and furthermore,the Policy makers should fully consider the interconnectedness among supply chain credit default network enterprises to more effectively promote the recovery of real estate supply chain credit default network.
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