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基于分位数因子VAR模型的金融机构间特质风险关联研究 被引量:3

Idiosyncratic Risk Connectedness Among Financial Institutions:A Quantile Factor VAR Approach
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摘要 文章采用最新发展的QFVAR(Quantile Factor VAR)模型,借助市场因子消除误差项中的横截面相关性,从而研究中国36家上市金融机构间的特质风险关联,并通过分位数回归估计,考察了金融机构间的均值风险传染和尾部风险传染,最后从风险溢出和风险溢入角度,探讨了金融机构特质风险的主要来源.研究发现:1)金融机构特质风险关联会随着分位数发生显著变化,相较条件均值和条件中位数,特质风险在两侧尾部存在强烈的时变关联效应.2)特质风险的均值传染主要集中在部门内,而尾部传染则表现出明显的跨部门效应,其中右尾的风险传染强度更高.3)在金融市场平稳期,证券部门具有较高的特质风险溢出水平,而在金融市场危机期,银行部门具有较高的特质风险溢出水平.文章的研究结果对监管部门防范化解金融风险具有借鉴意义,有助于其从特质冲击角度,加深对金融风险传染机制的理解. Under the background of uneven and unstable economic recovery,the key to preventing and defusing financial risk is to capture the characteristics of risk connectedness among financial institutions.Different from the existing risk connectedness literature,this paper uses the QFVAR model to study the idiosyncratic risk connectedness among 36 listed financial institutions in China.The main conclusions are as follows:First,compared with the conditional mean and the conditional median,the connectedness level of idiosyncratic risk in both tails is higher and has time-varying characteristics.These important features of idiosyncratic risk connectedness are obscured in models estimated using conventional conditional mean estimators.Second,the mean contagion is mainly concentrated within sectors,while the tail contagion has cross-sector effects.The cross-sector contagion of the right tail is more obvious,mainly concentrated in large state-owned banks.Finally,during the market stable period,the securities sector has a higher level of risk spillover,while during the market crisis period,the banking sector has a higher risk spillover level.
作者 杜焱 欧阳资生 周学伟 DU Yan;OUYANG Zisheng;ZHOU Xuewei(School of Finance,Hunan University of Technology and Business,Changsha 410205;School of Business,Hunan Normal University,Changsha 410081)
出处 《系统科学与数学》 CSCD 北大核心 2023年第2期431-451,共21页 Journal of Systems Science and Mathematical Sciences
基金 国家社会科学基金重点项目(21ATJ009) 湖南省教育厅重点科研项目(18A294)资助课题。
关键词 特质风险 金融机构 尾部关联 因子结构 分位数回归 Idiosyncratic risk financial institution tail connectedness factor structure quantile regression
作者简介 通讯作者:周学伟,Email:xueweizhou@hunnu.edu.cn。
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