Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Kris Peremans"'
Publikováno v:
Risks, Vol 6, Iss 4, p 108 (2018)
The chain ladder method is a popular technique to estimate the future reserves needed to handle claims that are not fully settled. Since the predictions of the aggregate portfolio (consisting of different subportfolios) do not need to be equal to the
Externí odkaz:
https://doaj.org/article/3161ac44c0814ea89065ea604f288f20
Publikováno v:
COMPUTATIONAL STATISTICS
© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. A robust Bayesian model for seemingly unrelated regression is proposed. By using heavy-tailed distributions for the likelihood, robustness in the response variable is attained. In additi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b117c84731d9ed85909de3055741f6ee
https://lirias.kuleuven.be/handle/123456789/661163
https://lirias.kuleuven.be/handle/123456789/661163
Publikováno v:
Risks, Vol 6, Iss 4, p 108 (2018)
Risks
Volume 6
Issue 4
Risks
Volume 6
Issue 4
The chain ladder method is a popular technique to estimate the future reserves needed to handle claims that are not fully settled. Since the predictions of the aggregate portfolio (consisting of different subportfolios) in general differ from the sum
Autor:
Stefan Van Aelst, Kris Peremans
© 2018 Elsevier Inc. Seemingly unrelated regression models generalize linear regression models by considering multiple regression equations that are linked by contemporaneously correlated disturbances. Robust inference for seemingly unrelated regres
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::253179316af891965ab41f2401b28690
http://arxiv.org/abs/1801.04716
http://arxiv.org/abs/1801.04716
Insurers are faced with the challenge of estimating the future reserves needed to handle historic and outstanding claims that are not fully settled. A well-known and widely used technique is the chain-ladder method, which is a deterministic algorithm
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::056c0ff7d3ab7205849717149c765b29
http://arxiv.org/abs/1701.03934
http://arxiv.org/abs/1701.03934