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

doi:10.16381/j.cnki.issn1003-207x.2016.10.001

中国管理科学 ›› 2016, Vol. 24 ›› Issue (10): 1-9.doi: 10.16381/j.cnki.issn1003-207x.2016.10.001

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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

姬强¹, 刘炳越^1,2, 范英³

1. 中国科学院科技政策与管理科学研究所能源与环境政策研究中心, 北京 100190;
2. 中国科学技术大学统计与金融系, 安徽合肥 230026;
3. 北京航空航天大学经济管理学院, 北京 100190

收稿日期:2015-08-12 修回日期:2016-03-28 出版日期:2016-10-20 发布日期:2016-12-27
通讯作者: 范英(1966-),女(汉族),河北阳原人,北京航空航天大学经济管理学院院长,博士生导师,研究方向:能源经济学、能源市场与碳市场、能源-环境-经济系统建模等,E-mail:ying_fan@263.net. E-mail:ying_fan@263.net
基金资助:
国家自然科学基金资助项目（91546109，71133005，71203210）

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

JI Qiang¹, LIU Bing-yue^1,2, FAN Ying³

1. Center for Energy and Environmental Policy research, Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, China;
2. Department of Statistics and Finance, University of Science and Technology of China, Hefei 230026, China;
3. School of Economics & Management, Beihang University, Beijing 100191, China

Received:2015-08-12 Revised:2016-03-28 Online:2016-10-20 Published:2016-12-27

摘要/Abstract

摘要： 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。

关键词: 尾部相依, 跨市场协同运动, 时变最优Copula模型

Abstract: 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.

Key words: tail dependence, co-movement across markets, time-varying optimal copula

中图分类号:

F830

姬强, 刘炳越, 范英. 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[J]. 中国管理科学, 2016, 24(10): 1-9.

JI Qiang, LIU Bing-yue, FAN Ying. Dynamic Dependence Between International Oil, Natural Gas and Exchange Market Based on a New Time-varying Optimal Copula Model[J]. Chinese Journal of Management Science, 2016, 24(10): 1-9.

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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

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

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