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Correlation mixtures of elliptical copulas arise when the correlation parameter is driven itself by a latent random process. For such copulas, both penultimate and asymptotic tail dependence are much larger than for ordinary elliptical…

Statistics Theory · Mathematics 2009-12-21 Hans Manner , Johan Segers

Given two multivariate copulas with corresponding tail dependence functions, we investigate the relation between a natural tail dependence ordering $\leq_{tdo}$ and the order $\leq_{loc}$ of local stochastic dominance. We show that,…

Probability · Mathematics 2023-02-07 Karl Friedrich Siburg , Christopher Strothmann

Measures of tail dependence between random variables aim to numerically quantify the degree of association between their extreme realizations. Existing tail dependence coefficients (TDCs) are based on an asymptotic analysis of relevant…

Applications · Statistics 2021-06-11 Davide Lauria , Svetlozar T. Rachev , A. Alexandre Trindade

Probabilistic forecasts comprehensively describe the uncertainty in the unknown future outcome, making them essential for decision making and risk management. While several methods have been introduced to evaluate probabilistic forecasts,…

Methodology · Statistics 2025-05-23 Sam Allen , Jonathan Koh , Johan Segers , Johanna Ziegel

Quantifying tail dependence is an important issue in insurance and risk management. The prevalent tail dependence coefficient (TDC), however, is known to underestimate the degree of tail dependence and it does not capture non-exchangeable…

Statistics Theory · Mathematics 2023-02-14 Takaaki Koike , Shogo Kato , Marius Hofert

Assessing dependence within co-movements of financial instruments has been of much interest in risk management. Typically, indices of tail dependence are used to quantify the strength of such dependence, although many of the indices…

Methodology · Statistics 2022-09-21 Ning Sun , Chen Yang , Ričardas Zitikis

We analyse circumstances in which bifurcation-driven jumps in AI systems are associated with emergent heavy-tailed outcome distributions. By analysing how a control parameter's random fluctuations near a catastrophic threshold generate…

Computers and Society · Computer Science 2025-03-27 Elija Perrier

By using a probabilistic technique based on the exponential change of measure we find a precise tail asymptotic behavior of some perpetuities with distributions close to the Dickman distribution.

Probability · Mathematics 2026-04-17 Alexander Iksanov , Oleh Iksanov

This paper investigates tail asymptotics of stationary distributions and quasi-stationary distributions (QSDs) of continuous-time Markov chains on subsets of the non-negative integers. Based on the so-called flux-balance equation, we…

Probability · Mathematics 2023-08-16 Chuang Xu , Mads Christian Hansen , Carsten Wiuf

The tail index, indicating the degree of fatness of the tail distribution, is an important component of extreme value theory since it dominates the asymptotic distribution of extreme values such as the sample maximum. In this paper, we…

Statistics Theory · Mathematics 2009-06-12 Moosup Kim , Sangyeol Lee

We investigate the relaxation of long-tailed distributions under stochastic dynamics that do not support such tails. Linear relaxation is found to be a borderline case in which long tails are exponentially suppressed in time but not…

Statistical Mechanics · Physics 2015-06-22 Christian Van den Broeck , Upendra Harbola , Raul Toral , Katja Lindenberg

Tail dependence refers to clustering of extreme events. In the context of financial risk management, the clustering of high-severity risks has a devastating effect on the well-being of firms and is thus of pivotal importance in risk…

Applications · Statistics 2016-07-19 Edward Furman , Alexey Kuznetsov , Jianxi Su , Ricardas Zitikis

Let $X$ and $Y$ be two independent random variables with corresponding distributions $F$ and $G$ supported on $[0,\infty)$. The distribution of the product $XY$, which is called the product convolution of $F$ and $G$, is denoted by $H$. In…

Probability · Mathematics 2019-01-08 Zhaolei Cui , Guancheng Jiang , Yuebao Wang

For purposes of Value-at-Risk estimation, we consider several multivariate families of heavy-tailed distributions, which can be seen as multidimensional versions of Paretian stable and Student's t distributions allowing different marginals…

Risk Management · Quantitative Finance 2011-12-20 Carlo Marinelli , Stefano d'Addona , Svetlozar T. Rachev

In this paper, we examine two problems on applied probability, which are directly connected with the dependence in presence of heavy tails. The first problem, is related to max-sum equivalence of the randomly weighted sums in bi-variate set…

Probability · Mathematics 2025-05-27 Dimitrios G. Konstantinides , Charalampos D. Passalidis

Count data are omnipresent in many applied fields, often with overdispersion. With mixtures of Poisson distributions representing an elegant and appealing modelling strategy, we focus here on how the tail behaviour of the mixing…

Statistics Theory · Mathematics 2023-05-29 Samuel Valiquette , Gwladys Toulemonde , Jean Peyhardi , Éric Marchand , Frédéric Mortier

There are many ways of measuring and modeling tail-dependence in random vectors: from the general framework of multivariate regular variation and the flexible class of max-stable vectors down to simple and concise summary measures like the…

Probability · Mathematics 2022-12-05 Anja Janßen , Sebastian Neblung , Stilian Stoev

The use of expectiles in risk management has recently gathered remarkable momentum due to their excellent axiomatic and probabilistic properties. In particular, the class of elicitable law-invariant coherent risk measures only consists of…

Statistics Theory · Mathematics 2023-03-21 Abdelaati Daouia , Simone A. Padoan , Gilles Stupfler

We show the equivalence of three properties for an infinitely divisible distribution: the subexponentiality of the density, the subexponentiality of the density of its L\'evy measure and the tail equivalence between the density and its…

Probability · Mathematics 2023-02-16 Muneya Matsui

We consider phase-type scale mixture distributions which correspond to distributions of a product of two independent random variables: a phase-type random variable $Y$ and a nonnegative but otherwise arbitrary random variable $S$ called the…

Probability · Mathematics 2017-05-16 Leonardo Rojas-Nandayapa , Wangyue Xie
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