Conditional Tail Expectation Decomposition and Conditional Mean Risk Sharing for Dependent and Conditionally Independent Losses

Michel Denuit () and Christian Y. Robert
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Michel Denuit: Université catholique de Louvain, LIDAM/ISBA, Belgium

No 2022025, LIDAM Reprints ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

Abstract: Conditional tail expectations are often used in risk measurement and capital allocation. Conditional mean risk sharing appears to be effective in collaborative insurance, to distribute total losses among participants. This paper develops analytical results for risk allocation among different, correlated units based on conditional tail expectations and conditional mean risk sharing. Results available in the literature for independent risks are extended to correlated ones, in a unified way. The approach is applied to mixture models with correlated latent factors that are often used in practice. Conditional Monte Carlo simulation procedures are proposed in that setting.

Keywords: Weighted distributions; Size-biased transform; Mixture models; Archimedean copulas; Conditional Monte Carlo simulation (search for similar items in EconPapers)
Pages: 33
Date: 2022-01-01
Note: In: Methodology and Computing in Applied Probability, 2022, vol. 24, p. 1953-1985
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:aiz:louvar:2022025

DOI: 10.1007/s11009-021-09888-0

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