英文标题：
《Dependencies and systemic risk in the European insurance sector: Some
  new evidence based on copula-DCC-GARCH model and selected clustering methods》
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作者：
Anna Denkowska, Stanis{\\l}aw Wanat
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最新提交年份：
2019
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英文摘要：
  The subject of the present article is the study of correlations between large insurance companies and their contribution to systemic risk in the insurance sector. Our main goal is to analyze the conditional structure of the correlation on the European insurance market and to compare systemic risk in different regimes of this market. These regimes are identified by monitoring the weekly rates of returns of eight of the largest insurers (five from Europe and the biggest insurers from the USA, Canada and China) during the period January 2005 to December 2018. To this aim we use statistical clustering methods for time units (weeks) to which we assigned the conditional variances obtained from the estimated copula-DCC-GARCH model. The advantage of such an approach is that there is no need to assume a priori a number of market regimes, since this number has been identified by means of clustering quality validation. In each of the identified market regimes we determined the commonly now used CoVaR systemic risk measure. From the performed analysis we conclude that all the considered insurance companies are positively correlated and this correlation is stronger in times of turbulences on global markets which shows an increased exposure of the European insurance sector to systemic risk during crisis. Moreover, in times of turbulences on global markets the value level of the CoVaR systemic risk index is much higher than in \"normal conditions\".
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中文摘要：
本文的主题是研究大型保险公司之间的相关性及其对保险业系统性风险的贡献。我们的主要目标是分析欧洲保险市场相关性的条件结构，并比较该市场不同制度下的系统性风险。通过监测2005年1月至2018年12月期间八家最大保险公司（五家来自欧洲，最大的保险公司来自美国、加拿大和中国）的每周回报率，可以确定这些制度。为此，我们使用时间单位（周）的统计聚类方法，将从估计的copula DCC GARCH模型中获得的条件方差分配给这些时间单位。这种方法的优点是，无需先验地假设若干市场制度，因为这一数字是通过聚类质量验证确定的。在每个已确定的市场制度中，我们确定了目前常用的CoVaR系统性风险度量。从执行的分析中，我们得出结论，所有考虑的保险公司都是正相关的，这种相关性在全球市场动荡时期更为强烈，这表明欧洲保险业在危机期间暴露于系统性风险的风险增加。此外，在全球市场动荡时期，CoVaR系统性风险指数的价值水平远高于“正常情况”。
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分类信息：

一级分类：Economics        经济学
二级分类：General Economics        一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Quantitative Finance        数量金融学
二级分类：Economics        经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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