国际油气价格与汇率动态相依关系研究:基于一种新的时变最优Copula模型

本文提出一个新的时变最优Copula模型，可以准确识别二元时间序列任意时点最优的相依结构。该模型构造了半旋转copula以刻画非对称的反向相依关系，并引入独立性的无分布检验证实相依关系的存在性。同时，我们对能源商品市场（原油、天然气）、外汇市场间动态相依关系进行了实证分析，实证结果表明跨市场相依结构类型确实是时变的，突发事件往往是相依结构突变的主因。另外，时变最优Copula模型的主要优势在于不仅能够捕捉相依方向和相依强度的动态性，还能有效捕捉相依结构类型的动态性。

Dynamic Dependence Between International Oil,Natural Gas and Exchange Market Based on a New Time-varying Optimal Copula Model

In this paper, a new time-varying optimal copula model is proposed to precisely identify the optimal dependence structure of bivariate time series at every time point. In this model, half-rotated copulas, i.e. C_R1G(u,v;θ)=v-C_OG(1-u,v;θ) and C_R2G(u,v;θ)=u-C_OG(1-u,v;θ), are constructed to capture the asymmetric negative dependence, especially for the negative extreme dependence, i.e. lower-upper tail τ^LU(α)=Pr(X< F_X^-1(α)|Y >F_Y^-1(1-α)) and upper-lower tail dependence τ^LU(α)=Pr(X >F_X^-1(1-α)|Y< F_Y^-1(α)) for a small α, e.g. 0.05. Meanwhile, the distribution-free test for independence is introduced to verify the dependent relationship and reduce the computation time. At last, the time-varying optimal copula model is employed to analyse the dynamic dependence between energy markets, i.e. crude oil and natural gas markets, and exchange market. It is found that for Brent-USDX pair the dependence is significantly negative, the proportion of half-rotated Gumbel copula is larger than that of the original Gumbel or rotated Gumbel, the lower-upper or upper-lower tail dependence is obviously larger than the upper-upper or lower-lower tail dependence especially in the crisis period, and above empirical results for GAS-USDX pair are similar but not very remarkable. However, the dependence between Brent and GAS is positive and the upper-upper or lower-lower tail dependence is larger than lower-upper or upper-lower tail dependence. Meanwhile, the types of dependence structureacross markets vary over time and that emergencies are usually the major cause of sudden changes in the dependence structure. Resulas 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 TVOC model canbe employed to predict the copula-dependence structure in a newway, which provides an analytical tool for market investors and risk managers to adjust their portfolio strategy, hedge the investment risk and guard against risk spillover and even a financial contagion.