Longevity projections : incorporating sample and population information through the modelization of differences in common sample points
Objetos digitales
| Tag | 1 | 2 | Valor |
|---|---|---|---|
| LDR | 00000cam a22000004b 4500 | ||
| 001 | MAP20200033608 | ||
| 003 | MAP | ||
| 005 | 20201022112318.0 | ||
| 008 | 180802s20200000esp|||| ||| ||spa d | ||
| 040 | $aMAP$bspa$dMAP | ||
| 084 | $a6 | ||
| 100 | 1 | $0MAPA20200021087$aSalazar Vesga, Natalia | |
| 245 | 1 | 0 | $aLongevity projections$b: incorporating sample and population information through the modelization of differences in common sample points$cby Natalia Salazar Vesga |
| 260 | $aMadrid$bUniversidad Carlos III de Madrid$c2020 | ||
| 500 | $aTrabajo Fin de Master del Master en Ciencias Actuariales y Financieras de la Escuela de Postgrado de la Universidad Carlos III de Madrid. Tutores: José Miguel Rodríguez-Pardo del Castillo y Jesús Ramón Simón del Potro. Curso 2018-2020 | ||
| 520 | $aProjecting and understanding longevity has always been a major concern for both de- mographers and insurance companies. Having reliable projections of the mortality pat- terns at a country level allows governments to structure their pension schemes and public healthcare policies, and at a sample level, assists companies with the pricing of their life- insurance products as well as with the calculation of their Solvency Capital Requirement (SCR). Understanding mortality at a company level is not an easy task, due to the lack of a large series of data, the most common mortality projection models can not be ap- plied. This is the reason why insurers make use of more pragmatic approaches, generally at the cost of imposing safety margins on their estimations and overestimating death probabilities, which results in a higher cost of solvency capital and lower profitability for the business at hand. This document aims to explore a way in which population mortality models can be adapted to forecast the behavior of the insured population introducing a correction in the forecast of the general population that stems from the modelization of the differences between the two aforementioned groups. | ||
| 650 | 4 | $0MAPA20080555016$aLongevidad | |
| 650 | 4 | $0MAPA20080618070$aProyecciones demográficas | |
| 650 | 4 | $0MAPA20080570590$aSeguro de vida | |
| 650 | 4 | $0MAPA20080592011$aModelos actuariales | |
| 650 | 4 | $0MAPA20080590567$aEmpresas de seguros | |
| 650 | 4 | $0MAPA20080591830$aMargen de solvencia | |
| 650 | 4 | $0MAPA20080563974$aRentabilidad | |
| 650 | 4 | $0MAPA20080611613$aModelos probabílisticos | |
| 650 | $0MAPA20200021438$aAgeingnomics. Economia senior | ||
| 700 | 1 | $0MAPA20140014897$aRodríguez-Pardo del Castillo, José Miguel | |
| 700 | 1 | $0MAPA20160001525$aSimón del Potro, Jesús Ramón | |
| 710 | 2 | $0MAPA20080455026$aUniversidad Carlos III de Madrid | |
| 830 | 0 | $0MAPA20160014013$aTrabajos Fin de Master | |
| 856 | $qapplication/pdf$w1108357$yRecurso elctrónico / Electronic resource |