Nonparametric Tail Copula Estimation: An Application to Stock and Volatility Index Returns |
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Authors: | Yuri Salazar Wing Lon Ng |
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Affiliation: | Centre for Computational Finance and Economic Agents (CCFEA) , University of Essex , Colchester , UK |
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Abstract: | In this study, we measure asymmetric negative tail dependence and discuss their statistical properties. In a simulation study, we show the reliability of nonparametric estimators of tail copula to measure not only the common positive lower and upper tail dependence, but also the negative “lower–upper” and “upper–lower” tail dependence. The use of this new framework is illustrated in an application to financial data. We detect the existence of asymmetric negative tail dependence between stock and volatility indices. Many common parametric copula models used in finance fail to capture this characteristic. |
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Keywords: | Copula Extreme value theory Nonparametric estimation Stock Tail dependence Volatility indices |
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