Rank-based methods for modeling dependence between loss triangles-Reference-Cited by-同舟云学术

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Rank-based methods for modeling dependence between loss triangles

Published:2016-07-11 Issue:2 Volume:6 Page:377-408
ISSN:2190-9733
Container-title:European Actuarial Journal
language:en
Short-container-title:Eur. Actuar. J.

Author:

Côté Marie-Pier,Genest Christian,Abdallah Anas

Funder

Natural Sciences and Engineering Research Council of Canada (CA)

Fonds de Recherche du Québec - Nature et Technologies

Canadian Statistical Sciences Institute

Canada Excellence Research Chairs, Government of Canada (CA)

Publisher

Springer Science and Business Media LLC

Subject

Statistics, Probability and Uncertainty,Economics and Econometrics,Statistics and Probability

Link

http://link.springer.com/content/pdf/10.1007/s13385-016-0134-y.pdf

Reference41 articles.

1. Abdallah A, Boucher JP, Cossette H (2015) Modeling dependence between loss triangles with hierarchical Archimedean copulas. ASTIN Bull 45:577–599

2. Ajne B (1994) Additivity of chain-ladder projections. ASTIN Bull 24:311–318

3. Andrews DW (2000) Inconsistency of the bootstrap when a parameter is on the boundary of the parameter space. Econometrica 68:399–405

4. Arbenz P, Hummel C, Mainik G (2012) Copula based hierarchical risk aggregation through sample reordering. Insur Math Econ 51:122–133

5. Bargès M, Cossette H, Marceau E (2009) TVaR-based capital allocation with copulas. Insur Math Econ 45:348–361

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1. Rank-Based Multivariate Sarmanov for Modeling Dependence between Loss Reserves;Risks;2023-10-26

2. Copula based Bayesian data analysis of loss reserving;Communications in Statistics - Simulation and Computation;2022-02-02

3. Tweedie double GLM loss triangles with dependence within and across business lines;European Actuarial Journal;2021-05-06

4. On Fitting Dependent Nonhomogeneous Loss Models to Unearned Premium Risk;North American Actuarial Journal;2020-09-09

5. On unbalanced data and common shock models in stochastic loss reserving;Annals of Actuarial Science;2020-07-27

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