《A new time-varying optimal copula model identifying the dependence across markets》

此片论文发表在2017年Quantitative Finance上。 作者采用一种时变最佳Copula模型（time-varying optimal copula model）来分析多个市场之间的依赖结构（美元指数，标普500，高盛商品指数（农业，能源，工业金属））。作者发现几个市场之间的依赖关系是动态变化的。

简介

This paper proposes a new time-varying optimal copula (TVOC) model to identify and capture the optimal dependence structure of bivariate time series at every time point. In the TVOC model, half-rotated copulas are constructed to measure the nonlinear and asymmetric negative dependence, and the distribution-free test for independence is introduced to verify the dependent relationship and reduce the computational time. The TVOC model is then employed to research the dependence structure between security and commodity markets. We find evidence that the dependence structures across different markets vary over time and that emergencies are usually the major cause of sudden changes in the dependence structure. We also show that the TVOC model captures the dynamic characteristics of the direction and intensity of the dependence as well as the dynamic characteristics of the types of dependence structure. In particular, the half-rotated copulas can accurately describe the asymmetric negative extreme dependence across different markets.