Wishart-gamma random effects models with applications to nonlife insurance

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MARC record
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040  ‎$a‎MAP‎$b‎spa‎$d‎MAP
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1001 ‎$0‎MAPA20080096434‎$a‎Denuit, Michel
24510‎$a‎Wishart-gamma random effects models with applications to nonlife insurance‎$c‎Michel Denuit, Yang Lu
520  ‎$a‎Random effects are particularly useful in insurance studies, to capture residual heterogeneity or to induce cross-sectional and/or serial dependence, opening hence the door to many applications including experience rating and microreserving. However, their nonobservability often makes existing models computationally cumbersome in a multivariate context. In this paper, it is shown that the multivariate extension to the Gamma distribution based on Wishart distributions for random symmetric positive-definite matrices (considering diagonal terms) is particularly tractable and convenient to model correlated random effects in multivariate frequency, severity and duration models. Three applications are discussed to demonstrate the versatility of the approach: (a) frequency-based experience rating with several policies or guarantees per policyholder, (b) experience rating accounting for the correlation between claim frequency and severity components, and (c) joint modeling and forecasting of the time-to-payment and amount of payment in microlevel reserving, when both are subject to censoring.
650 4‎$0‎MAPA20080586294‎$a‎Mercado de seguros
650 4‎$0‎MAPA20080663520‎$a‎Credibilidad
650 4‎$0‎MAPA20080545475‎$a‎Tarifas
650 4‎$0‎MAPA20080573935‎$a‎Seguros no vida
650 4‎$0‎MAPA20080602437‎$a‎Matemática del seguro
7001 ‎$0‎MAPA20170007913‎$a‎Lu, Yang
7730 ‎$w‎MAP20077000727‎$t‎The Journal of risk and insurance‎$d‎Nueva York : The American Risk and Insurance Association, 1964-‎$x‎0022-4367‎$g‎01/06/2021 Volumen 88 Número 2 - junio 2021 , p. 443-481