Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Pietro Millossovich"'
Publikováno v:
Risks, Vol 12, Iss 4, p 60 (2024)
The analysis of residual life expectancy evolution at retirement age holds great importance for life insurers and pension schemes. Over the last 30 years, numerous models for forecasting mortality have been introduced, and those that allow us to pred
Externí odkaz:
https://doaj.org/article/0334bd7187184c30ac9999e917b1d811
Publikováno v:
Journal of Statistical Software, Vol 84, Iss 1, Pp 1-38 (2018)
In this paper we mirror the framework of generalized (non-)linear models to define the family of generalized age-period-cohort stochastic mortality models which encompasses the vast majority of stochastic mortality projection models proposed to date,
Externí odkaz:
https://doaj.org/article/931ba6b101b3444cb507b5908d737e9a
Publikováno v:
Risks, Vol 9, Iss 1, p 20 (2021)
The purpose of this paper is to conduct a market-consistent valuation of life insurance participating liabilities sold to a population of partially heterogeneous customers under the joint impact of biometric and financial risk. In particular, the het
Externí odkaz:
https://doaj.org/article/4ddad9c44de9494e937bab0990e59e9d
Publikováno v:
Risk Analysis. 41:2392-2414
In risk analysis, sensitivity measures quantify the extent to which the probability distribution of a model output is affected by changes (stresses) in individual random input factors. For input factors that are statistically dependent, we argue that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39e19b1e21cb14c7f90dc906136e326c
https://doi.org/10.1111/risa.13758
https://doi.org/10.1111/risa.13758
We introduce an approach to sensitivity analysis of quantitative risk models, for the purpose of identifying the most influential inputs. The proposed approach relies on a change of measure derived by minimising the χ 2 -divergence, subject to a con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99d6ee66148f1858ee78efe91f11561d
http://hdl.handle.net/11368/3000527
http://hdl.handle.net/11368/3000527
Publikováno v:
SSRN Electronic Journal.
We introduce an approach to sensitivity analysis of quantitative risk models, for the purpose of identifying the most influential inputs. The proposed approach relies on a change of measure derived by minimising the $\chi^2$-divergence, subject to a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::adb7672c28039fe47028606c8b2bf33d
https://doi.org/10.2139/ssrn.3762498
https://doi.org/10.2139/ssrn.3762498
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::db0d97eaa31c729552a14a764e7028ef
https://doi.org/10.2139/ssrn.3966204
https://doi.org/10.2139/ssrn.3966204
Publikováno v:
SSRN Electronic Journal.
The Scenario Weights for Importance Measurement (SWIM) package implements a flexible sensitivity analysis framework, based primarily on results and tools developed by Pesenti et al. (2019). SWIM provides a stressed version of a stochastic model, subj
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb8c7281510b4484cf1d7f0f6f5c1ab1
https://doi.org/10.2139/ssrn.3515274
https://doi.org/10.2139/ssrn.3515274
Silvana Pesenti, Alberto Bettini, Pietro Millossovich and Andreas Tsanakas present their alternative approach to sensitivity analysis.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::c37b82bba0176dd8cc8c1422260f8b2c
http://hdl.handle.net/11368/2960389
http://hdl.handle.net/11368/2960389
Autor:
Ree Yongqing Chen, Pietro Millossovich
Publikováno v:
European Actuarial Journal
This paper introduces a gender specific model for the joint mortality projection of three countries (England and Wales combined, Scotland, and Northern Ireland) of the United Kingdom. The model, called 2-tier Augmented Common Factor model, extends th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::861143548bb415c82fbfe631cfd9c1ec
https://doi.org/10.1007/s13385-017-0164-0
https://doi.org/10.1007/s13385-017-0164-0