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Estimating copulas for insurance from scarce observations, expert opinion and prior information : a bayesian approach

Recurso electrónico / electronic resource
Registro MARC
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1001 ‎$0‎MAPA20120018112‎$a‎Arbenz, Philipp
24510‎$a‎Estimating copulas for insurance from scarce observations, expert opinion and prior information‎$b‎: a bayesian approach‎$c‎Philipp Arbenz, Davide Canestraro
520  ‎$a‎A prudent assessment of dependence is crucial in many stochastic models for insurance risks. Copulas have become popular to model such dependencies. However, estimation procedures for copulas often lead to large parameter uncertainty when observations are scarce. In this paper, we propose a Bayesian method which combines prior information (e.g. from regulators), observations and expert opinion in order to estimate copula parameters and determine the estimation uncertainty. The combination of different sources of information can significantly reduce the parameter uncertainty compared to the use of only one source. The model can also account for uncertainty in the marginal distributions. Furthermore, we describe the methodology for obtaining expert opinion and explain involved psychological effects and popular fallacies. We exemplify the approach in a case study.
650 1‎$0‎MAPA20090035034‎$a‎Modelización mediante cópulas
650 1‎$0‎MAPA20080591182‎$a‎Gerencia de riesgos
650 1‎$0‎MAPA20080586348‎$a‎Métodos de cálculo
650 1‎$0‎MAPA20080586447‎$a‎Modelo estocástico
650 1‎$0‎MAPA20080625894‎$a‎Métodos de estimación objetiva
7001 ‎$0‎MAPA20120018624‎$a‎Canestraro, Davide
7730 ‎$w‎MAP20077000420‎$t‎Astin bulletin‎$d‎Belgium : ASTIN and AFIR Sections of the International Actuarial Association‎$x‎0515-0361‎$g‎07/05/2012 Volumen 42 Número 1 - mayo 2012 , p. 271-290