A family of transformed copulas with singular component
Jiehua Xie, Jingping Yang, Wenhao Zhu

TL;DR
This paper introduces a new family of bivariate copulas created by transforming existing copulas with increasing functions, highlighting their singular components and tail dependence properties, with implications for dependence modeling.
Contribution
It proposes a novel class of transformed copulas with singular components, providing conditions for their validity and analyzing their dependence properties.
Findings
Identified conditions for transformed functions to be valid copulas.
Demonstrated the existence of singular components along the main diagonal.
Derived tail dependence coefficients for the new copulas.
Abstract
In this paper, we present a family of bivariate copulas by transforming a given copula function with two increasing functions, named as transformed copula. One distinctive characteristic of the transformed copula is its singular component along the main diagonal. Conditions guaranteeing the transformed function to be a copula function are provided, and several classes of the transformed copulas are given. The singular component along the main diagonal of the transformed copula is verified, and the tail dependence coefficients of the transformed copulas are obtained. Finally, some properties of the transformed copula are discussed, such as the totally positive of order 2 and the concordance order.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsFinancial Risk and Volatility Modeling · Stochastic processes and financial applications · Statistical Distribution Estimation and Applications
