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About the exact simulation of bivariate (reciprocal) Archimax copulas

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  • Mai Jan-Frederik

    (XAIA Investment GmbH, Sonnenstr. 19, 80331 München, Germany)

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.

Suggested Citation

  • Mai Jan-Frederik, 2022. "About the exact simulation of bivariate (reciprocal) Archimax copulas," Dependence Modeling, De Gruyter, vol. 10(1), pages 29-47, January.
    • Handle: RePEc:vrs:demode:v:10:y:2022:i:1:p:29-47:n:4
    DOI: 10.1515/demo-2022-0102
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    References listed on IDEAS

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    1. Clément Dombry & Sebastian Engelke & Marco Oesting, 2016. "Exact simulation of max-stable processes," Biometrika, Biometrika Trust, vol. 103(2), pages 303-317.
    2. Capéraà, Philippe & Fougères, Anne-Laure & Genest, Christian, 2000. "Bivariate Distributions with Given Extreme Value Attractor," Journal of Multivariate Analysis, Elsevier, vol. 72(1), pages 30-49, January.
    3. Mai, Jan-Frederik & Scherer, Matthias, 2020. "On the structure of exchangeable extreme-value copulas," Journal of Multivariate Analysis, Elsevier, vol. 180(C).
    4. Charpentier, A. & Fougères, A.-L. & Genest, C. & Nešlehová, J.G., 2014. "Multivariate Archimax copulas," Journal of Multivariate Analysis, Elsevier, vol. 126(C), pages 118-136.
    5. Mai, Jan-Frederik, 2018. "Extreme-value copulas associated with the expected scaled maximum of independent random variables," Journal of Multivariate Analysis, Elsevier, vol. 166(C), pages 50-61.
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