Various time-varying conditional Copula models to study the extreme co-movement (appreciate or depreciate heavily together) between European country currencies and the Chinese renminbi from June 1, 2008 to Nov.30, 2016.This dependence structure has rarely been studied in the literature.Our findings show very strong evidence of a structure break in the extreme co-movement probability since the beginning of2016, not only in the level but also in its dynamics.More specifically, the extreme co-movement probability between European currencies and the Renminbi generally increases significantly and has become more persistent since the beginning of 2016.Possible factors affecting the extreme co-movement probability are studied, including economic policy uncertainty, bilateral trade openness and financial integration.The results of our panel regression analysis show that throughout the whole sample, the impact of bilateral trade openness between Europe and China and economic policy uncertainty are significant.Before 2016, the effects of bilateral trade openness are quite sizable.However, since the beginning of 2016, the economic policy uncertainty, especially China's economic policy uncertainty, plays a key role.%2016年10月1日, 人民币正式加入国际货币基金组织的特别提款权篮子, 这是人民币国际化进程中的里程碑事件.人民币国际化为经济活动带来便利的同时, 也伴随着汇率风险传播的可能性, 这体现在不同货币汇率的极端联动性上.所谓极端联动性, 是指不同货币汇率同时大涨或大跌, 这不利于维持金融市场的稳定, 也会影响实体经济的有效运行.因此, 研究货币之间极端联动性的特征和原因有着重要意义.本文首先采用多种动态的Copula模型, 研究了欧洲地区主要国家货币汇率和人民币汇率之间从2008年到2016年间的极端联动现象.发现, 两个地区货币汇率的极端联动现象自2016年起有所增强.这不仅体现在极端联动的概率显著上升, 还体现在其持续时间的延长.为了解释该风险溢出现象背后的原因, 本文随后研究了影响极端联动概率的可能因素, 包括经济政策的不确定性, 中欧双边贸易的开放程度, 以及金融一体化的程度等.面板固定效应回归模型结果显示, 经济政策的不确定性对于中欧地区货币汇率的极端联动现象有着重要的影响, 其中中国经济政策的不确定性起主导作用, 尤其是在进入2016年之后.本文认为降低经济政策制定和实施过程中的不确定性将会有效地减少汇率风险的传播.
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