About the exact simulation of bivariate (reciprocal) Archimax copulas

Mai Jan-Frederik ()
Additional contact information
Mai Jan-Frederik: XAIA Investment GmbH, Sonnenstr. 19, 80331 München, Germany

Dependence Modeling, 2022, vol. 10, issue 1, 29-47

Abstract: We provide an exact simulation algorithm for bivariate Archimax copulas, including instances with negative association. In contrast to existing simulation approaches, the feasibility of our algorithm is directly linked to the availability of an exact simulation algorithm for the probability measure described by the derivative of the parameterizing Pickands dependence function. We demonstrate that this hypothesis is satisfied in many cases of interest and, in particular, it is satisfied for piece-wise constant Pickands dependence functions, which can approximate the general case to a given level of desired accuracy. Finally, the algorithm can be leveraged to an exact simulation algorithm for bivariate copulas associated with max-infinitely divisible random vectors whose exponent measure has norm-symmetric survival function, so-called reciprocal Archimax copulas.

Keywords: Archimax copula; extreme-value copula; Archimedean copula; max-infinitely divisible; simulation algorithm (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/demo-2022-0102 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:demode:v:10:y:2022:i:1:p:29-47:n:4

DOI: 10.1515/demo-2022-0102

Access Statistics for this article

Dependence Modeling is currently edited by Giovanni Puccetti

More articles in Dependence Modeling from De Gruyter
Bibliographic data for series maintained by Peter Golla ().