论文标题
基于Copula的依赖度量的测试和约会结构变化
Testing and Dating Structural Changes in Copula-based Dependence Measures
论文作者
论文摘要
本文与多元时间序列的依赖性结构中的测试和约会结构断裂有关。我们考虑了基于恒定的基于Copula的依赖度量的累积总和（CUSUM）类型测试，例如Spearman的等级相关性和分位数依赖性。渐近零分布以封闭形式不知道，临界值由I.I.D估算。引导程序。我们在仿真研究中分析了不同依赖度量设置（例如偏斜和脂肪尾分布）的大小和功率特性。迄今为止断裂点，并确定两个估计的休息位置是否属于同一休息事件，我们提出了一个枢轴置信区间程序。最后，在2002年至2013年中，我们将测试应用于十个大型金融公司的历史数据。
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.
