Tail Risk of Multivariate Regular Variation
نویسندگان
چکیده
Tail risk refers to the risk associated with extreme values and is often affected by extremal dependence among multivariate extremes. Multivariate tail risk, as measured by a coherent risk measure of tail conditional expectation, is analyzed for multivariate regularly varying distributions. Asymptotic expressions for tail risk are established in terms of the intensity measure that characterizes multivariate regular variation. Tractable bounds for tail risk are derived in terms of the tail dependence function that describes extremal dependence. Various examples involving Archimedean copulas are presented to illustrate the results and quality of the bounds.
منابع مشابه
Tail Approximation of Value-at-Risk under Multivariate Regular Variation
This paper presents a general tail approximation method for evaluating the Valueat-Risk of any norm of random vectors with multivariate regularly varying distributions. The main result is derived using the relation between the intensity measure of multivariate regular variation and tail dependence function of the underlying copula, and in particular extends the tail approximation discussed in E...
متن کاملLiving on the Multi - Dimensional Edge : Seeking Hidden Risks Using Regular Variation
Multivariate regular variation plays a role assessing tail risk in diverse applications such as finance, telecommunications, insurance and environmental science. The classical theory, being based on an asymptotic model, sometimes leads to inaccurate and useless estimates of probabilities of joint tail regions. This problem can be partly ameliorated by using hidden regular variation [Resnick, 20...
متن کاملAsymptotic Analysis of the Loss Given Default in the Presence of Multivariate Regular Variation
Consider a portfolio of n obligors subject to possible default. We propose a new structural model for the loss given default, which takes into account the severity of default. Then we study the tail behavior of the loss given default under the assumption that the losses of the n obligors jointly follow a multivariate regular variation structure. This structure provides an ideal framework for mo...
متن کاملAsymptotic Analysis of Multivariate Tail Conditional Expectations
Tail conditional expectations refer to the expected values of random variables conditioning on some tail events and are closely related to various coherent risk measures. In the univariate case, the tail conditional expectation is asymptotically proportional to the value-at-risk, a popular risk measure. The focus of this paper is on asymptotic relations between the multivariate tail conditional...
متن کاملAn Alternative Characterization of Hidden Regular Variation in Joint Tail Modeling
In modeling the joint upper tail of a multivariate distribution, a fundamental deficiency of classical extreme value theory is the inability to distinguish between asymptotic independence and exact independence. In this work, we examine multivariate threshold modeling based on the framework of regular variation on cones. Tail dependence is described by an angular measure, which in some cases is...
متن کامل