用尾轴测量非交换尾依赖性

IF 1.7 3区 经济学 Q2 ECONOMICS
ASTIN Bulletin Pub Date : 2021-01-28 DOI:10.1017/asb.2023.4
Takaaki Koike, Shogo Kato, M. Hofert
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引用次数: 2

摘要

摘要尾部依赖性的量化是保险与风险管理中的一个重要问题。然而,众所周知,普遍的尾依赖系数(TDC)低估了尾依赖的程度,并且由于它仅沿着主对角线评估极限尾概率,因此它没有捕获非交换尾依赖。为了克服这些问题,提出了两种新的尾部依赖度量,即最大尾部一致性度量(MTCM)和平均尾部一致性度量(ATCM)。这两种度量都是基于尾部copuls构建的,并且具有明确的概率解释,因为MTCM评估尾部所有可比较矩形中最大的极限概率,而ATCM是这些极限概率的归一化平均值。与TDC相比,所提出的措施可以捕获不可交换的尾部依赖性。本文还推导了各种copula的分析形式。一项真实的数据分析显示,股票指数的收益序列具有显著的尾部依赖性和尾部不可交换性,尤其是在金融危机时期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measuring non-exchangeable tail dependence using tail copulas
Abstract 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 tail dependence since it evaluates the limiting tail probability only along the main diagonal. To overcome these issues, two novel tail dependence measures called the maximal tail concordance measure (MTCM) and the average tail concordance measure (ATCM) are proposed. Both measures are constructed based on tail copulas and possess clear probabilistic interpretations in that the MTCM evaluates the largest limiting probability among all comparable rectangles in the tail, and the ATCM is a normalized average of these limiting probabilities. In contrast to the TDC, the proposed measures can capture non-exchangeable tail dependence. Analytical forms of the proposed measures are also derived for various copulas. A real data analysis reveals striking tail dependence and tail non-exchangeability of the return series of stock indices, particularly in periods of financial distress.
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来源期刊
ASTIN Bulletin
ASTIN Bulletin 数学-数学跨学科应用
CiteScore
3.20
自引率
5.30%
发文量
24
审稿时长
>12 weeks
期刊介绍: ASTIN Bulletin publishes papers that are relevant to any branch of actuarial science and insurance mathematics. Its papers are quantitative and scientific in nature, and draw on theory and methods developed in any branch of the mathematical sciences including actuarial mathematics, statistics, probability, financial mathematics and econometrics.
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