Testing the Multivariate Regular Variation Model
نویسندگان
چکیده
منابع مشابه
Tail Risk of Multivariate Regular Variation
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...
متن کاملA characterization of multivariate regular variation
• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version ...
متن کاملOn the multivariate variation control chart
Multivariate control charts such as Hotelling`s T^ 2 and X^ 2 are commonly used for monitoring several related quality characteristics. These control charts use correlation structure that exists between quality characteristics in an attempt to improve monitoring. The purpose of this article is to discuss some issues related to the G chart proposed by Levinson et al. [9] for detecting shifts in ...
متن کاملTail 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 کاملExtreme geometric quantiles in a multivariate regular variation framework
Considering extreme quantiles is a popular way to understand the tail of a distribution. While they have been extensively studied for univariate distributions, much less has been done for multivariate ones, primarily because there is no universally accepted definition of what a multivariate quantile or a multivariate distribution tail should be. In this paper, we focus on extreme geometric quan...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SSRN Electronic Journal
سال: 2018
ISSN: 1556-5068
DOI: 10.2139/ssrn.3274566