On tail dependence parameters for non-continuous and autocorrelated margins

Fuente: arXiv
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Autor principal: Idowu, Victory
Formato: Preprint
Publicado: 2025
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author Idowu, Victory
author_facet Idowu, Victory
contents Tail dependence plays an essential role in the characterization of joint extreme events in multivariate data. However, most standard tail dependence parameters assume continuous margins. This note presents a form of tail dependence suitable for non-continuous and discrete margins. We derive a representation of tail dependence based on the volume of a copula and prove its properties. We utilize a bivariate regular variation to show that our new metric is consistent with the standard tail dependence parameters on continuous margins. We further define tail dependence on autocorrelated margins where the tail dependence parameter examine lagged correlation on the sample.
format Preprint
id arxiv_https___arxiv_org_abs_2502_01271
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle On tail dependence parameters for non-continuous and autocorrelated margins
Idowu, Victory
Statistics Theory
Tail dependence plays an essential role in the characterization of joint extreme events in multivariate data. However, most standard tail dependence parameters assume continuous margins. This note presents a form of tail dependence suitable for non-continuous and discrete margins. We derive a representation of tail dependence based on the volume of a copula and prove its properties. We utilize a bivariate regular variation to show that our new metric is consistent with the standard tail dependence parameters on continuous margins. We further define tail dependence on autocorrelated margins where the tail dependence parameter examine lagged correlation on the sample.
title On tail dependence parameters for non-continuous and autocorrelated margins
topic Statistics Theory
url https://arxiv.org/abs/2502.01271