Hostname: page-component-76fb5796d-wq484 Total loading time: 0 Render date: 2024-04-27T04:28:02.722Z Has data issue: false hasContentIssue false

MULTIVARIATE COMPOSITE COPULAS – CORRIGENDUM

Published online by Cambridge University Press:  24 January 2022

Rights & Permissions [Opens in a new window]

Abstract

Type
Corrigendum
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of The International Actuarial Association

In the original publication of Xie et al. (Reference Xie, Fang, Yang and Bu2021), an error occurred within the Conclusions section of the published article. The corrected text is reproduced below:

The multivariate composite copula has a clear probability structure and enjoys tractable theoretical properties, such as marginality, monotonicity, linearity, symmetry, and exchangeability. Moreover, it enjoys the characteristic of uniform convergence when the component copulas or the bivariate functions in the vector are uniformly convergent. The multivariate composite copula also has the reproduction property for its component copulas by choosing some special vectors. Some known copulas belong to the family of multivariate composite copulas, such as the family of Archimedean copulas, the Bernstein copula, the composite Bernstein copula, and the max-copula. Empirical results have shown that the multivariate composite copula fits the empirical data of one-year Chinese treasury bond and five-year Chinese treasury bond well on both the tail parts and the whole region. Hence, the multivariate composite copula has a great deal of advantages and flexibility in the potential applications.

The authors apologize for this error.

References

Xie, J., Fang, J., Yang, J., & Bu, L. (2021). MULTIVARIATE COMPOSITE COPULAS. ASTIN Bulletin, first published online November 3 2021. DOI: https://doi.org/10.1017/asb.2021.30.CrossRefGoogle Scholar