Estimation and Model Selection of Copulas with an Application to Exchange Rates
Estimation and Model Selection of Copulas with an Application to Exchange Rates
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DOI：
10.26481/umamet.2007056
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
H. Manner
中科院分区：
文献类型：
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作者：
H. Manner
copula是多元分布函数的一部分，它完全捕获了感兴趣的变量之间的横截面依赖性，并且它们已经成为一种非常流行的工具，用于模拟不同于椭圆分布的线性相关性的依赖性。我们回顾了copula函数的理论，给出了一些例子，并描述了如何从这些函数中抽取随机数据。在广泛的蒙特卡罗研究中，讨论和比较了不同的估计和模型选择技术。我们发现，文献中未考虑的一个检验，即对条件联结变换后的数据进行的Jarque-Bera检验，在所提出的检验中具有最好的性质，而选择最佳拟合联结的最可靠准则是Akaike信息准则。我们用copulas对拉丁美洲货币对欧元的汇率收益进行建模，我们发现了对称依赖、过度上尾依赖和过度下尾依赖的证据。
Copulas are the part of a multivariate distribution function that fully captures the cross sectional dependence between the variables of interest and they have become a very popular tool to model dependencies different from the linear correlation of elliptical distributions. We review the theory of copula functions, present a number of examples and describe how to sample random data from these. Different techniques for estimation and model selection are discussed and compared in an extensive Monte Carlo study. We find that a test not considered in the literature, namely the Jarque-Bera test applied on transformed data from the conditional copula, has the best properties of the presented tests, but that the most reliable criterion for selecting the best fitting copula is the Akaike information criterion. We model exchange rate returns of Latin American currencies against the euro with copulas and we find evidence of symmetric dependence, excess upper tail dependence and excess lower tail dependence.