Year: 2024
Type: preprint
Abstract: A popular measure of association is the tail dependence coefficient which measures the strength of dependence in either the lower-left or upper-right tail of a bivariate distribution. In this paper, we develop the idea of quantile dependence, which generalizes the notion of tail dependence and could be used to detect dependence in specific regions of the domain of a joint distribution function. Properties of the proposed quantile dependence coefficient are studied and several examples illustrate our results.
Source: arXiv (Cornell University)
Authors: Dastbaravarde, A., Dolati, A.
Institution: Yazd University
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4391709830