Beyond dimension two: A test for higher-order tail risk
Julia Schaumburg () and
No 80, Working Paper Series in Economics from Karlsruhe Institute of Technology (KIT), Department of Economics and Management
In practice, multivariate dependencies between extreme risks are often only assessed in a pairwise way. We propose a test for detecting situations when such pairwise measures are inadequate and give incomplete results. This occurs when a significant portion of the multivariate dependence structure in the tails is of higher dimension than two. Our test statistic is based on a decomposition of the stable tail dependence function describing multivariate tail dependence. The asymptotic properties of the test are provided and a bootstrap based finite sample version of the test is proposed. A simulation study documents good size and power properties of the test including settings with time-series components and factor models. In an application to stock indices for non-crisis times, pairwise tail models seem appropriate for global markets while the test finds them not admissible for the tightly interconnected European market. From 2007/08 on, however, higher order dependencies generally increase and require a multivariate tail model in all cases.
Keywords: decomposition of multivariate tail dependence; multivariate extreme values; stable tail dependence function; extreme dependence modeling (search for similar items in EconPapers)
JEL-codes: C01 C46 C58 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-rmg
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Journal Article: Beyond Dimension two: A Test for Higher-Order Tail Risk (2016)
Working Paper: Beyond dimension two: A test for higher-order tail risk (2014)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:kitwps:80
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