Estimating copulas for insurance from scarce observations, expert opinion and prior information : a bayesian approach
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| Tag | 1 | 2 | Value |
|---|---|---|---|
| LDR | 00000cab a2200000 4500 | ||
| 001 | MAP20120031050 | ||
| 003 | MAP | ||
| 005 | 20120711152431.0 | ||
| 008 | 120704e20120507esp|||p |0|||b|spa d | ||
| 040 | $aMAP$bspa$dMAP | ||
| 084 | $a6 | ||
| 100 | 1 | $0MAPA20120018112$aArbenz, Philipp | |
| 245 | 1 | 0 | $aEstimating copulas for insurance from scarce observations, expert opinion and prior information$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 | |
| 700 | 1 | $0MAPA20120018624$aCanestraro, Davide | |
| 773 | 0 | $wMAP20077000420$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 |