STATE SPACE MODELS FOR IBNR RESERVES ESTIMATION: ROW-WISE STACKING THE RUNOFF TRIANGLE / ESTIMAÇÃO DE RESERVAS IBNR POR MODELOS EM ESPAÇO DE ESTADO: EMPILHAMENTO POR LINHAS DO TRIÂNGULO RUNOFF
AUTOR(ES)
RODRIGO SIMOES ATHERINO
DATA DE PUBLICAÇÃO
2008
RESUMO
This work deals with prediction of IBNR reserves under a different ordering of the non-cumulative runoff triangle. This is accomplished by stacking the rows, which results in a univariate time series with several missing values, whose corresponding sum is in fact the IBNR. Two estimation approaches, entirely based on state space methods and Kalman filtering, are developed, implemented with real data, and compared with some well established estimation methods for IBNR. The first approach consists in obtaining the conditional covariance matrix of the IBNR components, and the second tackles the IBNR estimation under an accumulation process. Three remarks emerge from the empirical results: (i)computational feasibility and efficiency; (ii)precision improvement for IBNR estimation; and (iii)flexibility in which concerns the IBNR modelling framework.
ASSUNTO(S)
filtro de kalman kalman filter espaco de estado state space
ACESSO AO ARTIGO
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