英文标题：
《Time-Varying Extreme Value Dependence with Application to Leading
European Stock Markets》
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作者：
Daniela Castro Camilo, Miguel de Carvalho, Jennifer Wadsworth
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最新提交年份：
2017
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英文摘要：
Extremal dependence between international stock markets is of particular interest in today\'s global financial landscape. However, previous studies have shown this dependence is not necessarily stationary over time. We concern ourselves with modeling extreme value dependence when that dependence is changing over time, or other suitable covariate. Working within a framework of asymptotic dependence, we introduce a regression model for the angular density of a bivariate extreme value distribution that allows us to assess how extremal dependence evolves over a covariate. We apply the proposed model to assess the dynamics governing extremal dependence of some leading European stock markets over the last three decades, and find evidence of an increase in extremal dependence over recent years.
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中文摘要：
在当今全球金融格局中，国际股票市场之间的极端依赖尤其令人感兴趣。然而，之前的研究表明，这种依赖性不一定随时间而稳定。当依赖性随时间或其他合适的协变量变化时，我们关心的是建模极值依赖性。在渐近依赖的框架内，我们引入了一个二元极值分布角密度的回归模型，该模型允许我们评估极值依赖如何在协变量上演化。我们应用所提出的模型来评估过去三十年来欧洲一些主要股票市场的极端依赖动力学，并发现近年来极端依赖性增加的证据。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Statistical Finance 统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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