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作 者:唐勇[1,2,3] 李勇杰 朱鹏飞 TANG Yong;LI Yong-jie;ZHU Peng-fei(Fuzhou University,Fuzhou 350116,China;Putian University,Putian 351100,China;Fujian Provincial Key Laboratory of Fintech Innovation,Fuzhou 350116,China)
机构地区:[1]福州大学经济管理学院,福州350116 [2]莆田学院,莆田351100 [3]福建省金融科技创新重点实验室,福州350116
出 处:《电子科技大学学报(社科版)》2020年第5期77-89,共13页Journal of University of Electronic Science and Technology of China(Social Sciences Edition)
基 金:国家自然科学基金项目(71171056,71573042,71473039);福建省社科规划重大项目(FJ2017Z006);福建省自然科学基金项目(2017J01518);金融数学福建省高校重点实验室(莆田学院)开放课题(JR201804).
摘 要:【目的/意义】当市场面临重大冲击时,虽然不同行业指数在上涨与下挫过程中存在着类似趋势,但依然有着不同的波动特征与溢出特征。【设计/方法】利用GARCHSK模型刻画我国股票市场各行业不同阶矩的波动特征,并通过溢出指数从静态和动态角度测度2004~2018年期间我国股票市场行业间一阶矩、二阶矩和高阶矩风险溢出的强度和方向。【结论/发现】研究表明我国股市各行业指数具有明显的高阶矩波动特征,且各阶矩风险联动效应较强,单个行业的风险容易通过行业间的相互作用扩散到整个市场;当危机发生时,相比收益溢出指数较小的变化幅度,波动溢出指数能够及时对市场冲击做出反应,且高阶矩波动溢出指数能更准确地体现出不同行业的特质以及所受冲击的大小。[Purpose/Significance]In the event of great market volatility,despite similar trends shown by different sector indexes,they still demonstrate different characteristics of volatility and spillover in their ups and downs.[Design/Methodology]This paper adopts GARCHSK model to describe the volatility characteristics of different moments of various sectors in China’s stock market.Furthermore,this paper estimates the magnitude and direction of the first moment,second moment and higher moment risk spillover effects of sectors in China’s stock market between 2004 and 2018.[Findings/Conclusions]Results show that all sector indexes manifest significant characteristics of higher moment volatility,and strong risk linkage effect of each moment is more likely to spread the risk from one single sector to the whole market due to the interaction between sectors.When crisis breaks out,the volatility spillover indexes could reflect the market changes in a timely manner compared to the spillover indexes of returns,and the higher moment volatility spillover indexes can accurately reflect the features of and the shock to different sectors.
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