A structural break test for extremal dependence in β-mixing random vectors
β-混合随机向量极端依赖的结构突变检验
We derive a structural break test for extremal dependence in |$\beta$|-mixing, possibly high-dimensional random vectors with either asymptotically dependent or asymptotically independent components. Existing tests require serially independent observations with asymptotically dependent components. To avoid estimating a long-run variance, we use self-normalization, which obviates the need to estimate the coefficient of tail dependence when components are asymptotically…