Maximal asymmetry of bivariate copulas and consequences to measures of dependence

IF 0.6 Q4 STATISTICS & PROBABILITY
Florian Griessenberger, W. Trutschnig
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引用次数: 1

Abstract

Abstract In this article, we focus on copulas underlying maximal non-exchangeable pairs ( X , Y ) \left(X,Y) of continuous random variables X , Y X,Y either in the sense of the uniform metric d ∞ {d}_{\infty } or the conditioning-based metrics D p {D}_{p} , and analyze their possible extent of dependence quantified by the recently introduced dependence measures ζ 1 {\zeta }_{1} and ξ \xi . Considering maximal d ∞ {d}_{\infty } -asymmetry we obtain ζ 1 ∈ 5 6 , 1 {\zeta }_{1}\in \left[\frac{5}{6},1\right] and ξ ∈ 2 3 , 1 \xi \in \left[\frac{2}{3},1\right] , and in the case of maximal D 1 {D}_{1} -asymmetry we obtain ζ 1 ∈ 3 4 , 1 {\zeta }_{1}\in \left[\frac{3}{4},1\right] and ξ ∈ 1 2 , 1 \xi \in \left(\frac{1}{2},1\right] , implying that maximal asymmetry implies a very high degree of dependence in both cases. Furthermore, we study various topological properties of the family of copulas with maximal D 1 {D}_{1} -asymmetry and derive some surprising properties for maximal D p {D}_{p} -asymmetric copulas.
二元联结的最大不对称性及其对依赖性度量的影响
摘要本文主要研究连续随机变量X,Y,Y在一致度量d∞d_ {\infty}或基于条件的度量d p {D_p}意义上的极大不可交换对(X,Y) \left{ (X,Y)下的联结,}并通过最近引入的依赖性度量ζ 1 {}{}{\zeta _1}和{ξ }\xi来量化它们可能的依赖性程度{。考虑最大d∞}d_{\infty -不对称,我们得到ζ 1∈5,6,1}{\zeta _1}{}\in\left[\frac{5}{6},1\right]和ξ∈2,3,1 \xi\in\left[\frac{2}{3},1\right],在最大d 1 {D_1} -不对称的情况下,我们得到ζ 1∈3,4,1 {}{\zeta _1}{}\in\left[\frac{3}{4},1\right]和ξ∈1,2,1 \xi\in\left (\frac{1}{2},1 \right),这意味着最大不对称意味着在这两种情况下高度依赖。在此基础上,研究了极大d1d_1 -不对称的copuls族的各种拓扑性质,得到了极大{d1d_1} -不对称copuls族的一些令人惊奇的性质。{}{}{}
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来源期刊
Dependence Modeling
Dependence Modeling STATISTICS & PROBABILITY-
CiteScore
1.00
自引率
0.00%
发文量
18
审稿时长
12 weeks
期刊介绍: The journal Dependence Modeling aims at providing a medium for exchanging results and ideas in the area of multivariate dependence modeling. It is an open access fully peer-reviewed journal providing the readers with free, instant, and permanent access to all content worldwide. Dependence Modeling is listed by Web of Science (Emerging Sources Citation Index), Scopus, MathSciNet and Zentralblatt Math. The journal presents different types of articles: -"Research Articles" on fundamental theoretical aspects, as well as on significant applications in science, engineering, economics, finance, insurance and other fields. -"Review Articles" which present the existing literature on the specific topic from new perspectives. -"Interview articles" limited to two papers per year, covering interviews with milestone personalities in the field of Dependence Modeling. The journal topics include (but are not limited to):  -Copula methods -Multivariate distributions -Estimation and goodness-of-fit tests -Measures of association -Quantitative risk management -Risk measures and stochastic orders -Time series -Environmental sciences -Computational methods and software -Extreme-value theory -Limit laws -Mass Transportations
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