Telling tales from the tails: High‐dimensional tail interdependence
提出了一个简单灵活的框架，用于分析高维数据中的尾部相互依赖性，并开发了统计检验方法，应用于S&P 250指数成分股的尾部依赖分析。
Summary We propose a simple and flexible framework that allows for a comprehensive analysis of tail interdependence in high dimensions. We use co‐exceedances to capture the structure of the dependence in the tails and, relying on the concept of multi‐information, define the coefficient of tail interdependence. Within this framework, we develop statistical tests of (i) independence in the tails, (ii) goodness‐of‐fit of the tail interdependence structure of a hypothesized model with the one observed in the data, and (iii) dependence symmetry between any two tails. We present an analysis of tail interdependence among 250 constituents of the S&P 250 index.