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Beyond dimension two: A test for higher-order tail risk

Carsten Bormann, Julia Schaumburg () and Melanie Schienle

No 80, Working Paper Series in Economics from Karlsruhe Institute of Technology (KIT), Department of Economics and Management

Abstract: 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)
Date: 2016
New Economics Papers: this item is included in nep-ecm and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

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Related works:
Journal Article: Beyond Dimension two: A Test for Higher-Order Tail Risk (2016) Downloads
Working Paper: Beyond dimension two: A test for higher-order tail risk (2014) Downloads
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