Co-dependence of extreme events in high frequency FX returns
构建了一个专门框架，研究高频多元外汇收益率中的极端事件，将单变量检验推广到多维，并量化了横截面和时间序列极端事件的相互依赖性，发现了极端收益的立方律、递增且非对称的依赖性以及联合对称尾部极端风险的标度性质。
In this paper, we investigate extreme events in high frequency, multivariate FX returns within a purposely built framework. We generalize univariate tests and concepts to multidimensional settings and employ these novel techniques for parametric and nonparametric analysis. In particular, we investigate and quantify the co-dependence of cross-sectional and intertemporal extreme events. We find evidence of the cubic law of extreme returns, their increasing and asymmetric dependence and of the scaling property of extreme risk in joint symmetric tails.