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Dependence Structure Analysis and VaR Estimation Based on China's and International Gold Price: A Copula Approach

机译:基于中国和国际黄金价格的依赖性结构分析与差值估算:一种Copula方法

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摘要

Since 2013, China has become the world's largest gold producer and consumer. To gain the corresponding global pricing power in gold, many actions have been taken by China in recent years, including the International Board at Shanghai Gold Exchange, Shanghai-Hong Kong Gold Connect and Shanghai Gold Fix. Our work studies the dependence structure between China's and international gold price and examines whether these moves are changing the dependence structure. We use GARCH-copula models to detect the dynamic dependence and tail dependence. The research period is set to contain the Financial Crisis in 2008, the dramatical plunge of gold price in 2013 and a series of black swan events in 2016. The empirical study shows that some event driven dependence structure breaks are statistically insignificant. And the time-varying Symmetrized Joe-Clayton copula is the best copula to model the dependence structure based on AIC value. Finally, an example of applications of this dependence structure is given by estimating the VaR of an equally weighted portfolio with a simulation-based method.
机译:自2013年以来,中国已成为全球最大的黄金生产国和消费者。为了获得金黄金的相应全球定价能力,近年来中国采取了许多行动,包括上海黄金交易所的国际委员会,上海 - 香港黄金联系和上海金修复。我们的工作研究了中国和国际黄金价格之间的依赖结构,并研究了这些动作是否正在改变依赖结构。我们使用GARCH-COPULA模型来检测动态依赖和尾部依赖。研究期限设定为遏制2008年的金融危机,2013年黄金价格的戏剧性暴跌以及2016年的一系列黑天鹅赛事。实证研究表明,一些事件驱动的依赖结构突破是统计上微不足道的。并且时变对称的joe-clayton copula是基于AIC值模拟依赖结构的最佳组合。最后,通过用基于模拟的方法估计同样加权的产品组合的VAR来给出这种依赖性结构的应用的示例。

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