Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Alice X. D. Dong"'
Publikováno v:
Risks, Vol 12, Iss 9, p 137 (2024)
We leverage telematics data on driving behavior variables to assess driver risk and predict future insurance claims in a case study utilising a representative telematics sample. In the study, we aim to categorise drivers according to their driving ha
Externí odkaz:
https://doaj.org/article/af7fd2e2b0114f98a37761c785437829
Publikováno v:
ASTIN Bulletin. 45:503-550
We develop quantile functions from regression models in order to derive risk margin and to evaluate capital in non-life insurance applications. By utilizing the entire range of conditional quantile functions, especially higher quantile levels, we det
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9b49c6b10bc365e2b7fd78593b84aca
https://doi.org/10.1017/asb.2015.8
https://doi.org/10.1017/asb.2015.8
Publikováno v:
Insurance: Mathematics and Economics. 59:258-278
Our article considers the class of recently developed stochastic models that combine claims payments and incurred losses information into a coherent reserving methodology. In particular, we develop a family of hierarchical Bayesian paid–incurred cl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::815e7fbcd48507ab51fa49046b4137cc
https://doi.org/10.1016/j.insmatheco.2014.09.011
https://doi.org/10.1016/j.insmatheco.2014.09.011
Autor:
Jennifer S. K. Chan, Alice X. D. Dong
Publikováno v:
Insurance: Mathematics and Economics. 53:355-365
A Bayesian approach is presented in order to model long tail loss reserving data using the generalized beta distribution of the second kind (GB2) with dynamic mean functions and mixture model representation. The proposed GB2 distribution provides a f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2d611ddcbc000f5a11dec91cb39cf389
https://doi.org/10.1016/j.insmatheco.2013.07.001
https://doi.org/10.1016/j.insmatheco.2013.07.001
Publikováno v:
SSRN Electronic Journal.
We develop quantile regression models in order to derive risk margin and to evaluate capital in non-life insurance applications. By utilizing the entire range of conditional quantile functions, especially higher quantile levels, we detail how quantil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fa4b6df3f0b47a49508a5f97099f3a13
https://doi.org/10.2139/ssrn.2394063
https://doi.org/10.2139/ssrn.2394063
Publikováno v:
SSRN Electronic Journal.
Our article considers the class of recently developed stochastic models that combine claims payments and incurred losses information into a coherent reserving methodology. In particular, we develop a family of hierarchical Bayesian paid-incurred-clai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6fed08671359d3a57d30a0b516288104
https://doi.org/10.2139/ssrn.2980405
https://doi.org/10.2139/ssrn.2980405