摘要翻译：
本文研究了多元时间序列依赖结构中结构突变的检验和定年问题。我们考虑了基于常数Copula的依赖测度的累积和(CUSUM)型检验，如Spearman的秩相关和分位数依赖。渐近零分布不是封闭形式的，临界值是由一个I.I.D.估计的。引导过程。我们在一个模拟研究中分析了不同依赖度量设置下的大小和功率特性，如斜尾分布和胖尾分布。为了确定断点和判断两个估计的断点是否属于同一断点事件，我们提出了一个枢轴置信区间过程。最后，我们对上一次金融危机期间的十家大型金融公司的历史数据进行了检验。
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英文标题：
《Testing and Dating Structural Changes in Copula-based Dependence
Measures》
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作者：
Florian Stark and Sven Otto
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最新提交年份：
2020
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分类信息：

一级分类：Economics 经济学
二级分类：Econometrics 计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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一级分类：Statistics 统计学
二级分类：Applications 应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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英文摘要：
This paper is concerned with testing and dating structural breaks in the dependence structure of multivariate time series. We consider a cumulative sum (CUSUM) type test for constant copula-based dependence measures, such as Spearman\'s rank correlation and quantile dependencies. The asymptotic null distribution is not known in closed form and critical values are estimated by an i.i.d. bootstrap procedure. We analyze size and power properties in a simulation study under different dependence measure settings, such as skewed and fat-tailed distributions. To date break points and to decide whether two estimated break locations belong to the same break event, we propose a pivot confidence interval procedure. Finally, we apply the test to the historical data of ten large financial firms during the last financial crisis from 2002 to mid-2013.
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