Chain Ladder Method : Bayesian Bootstrap versus Classical Bootstrap

@inproceedings{Peters2009ChainLM,
  title={Chain Ladder Method : Bayesian Bootstrap versus Classical Bootstrap},
  author={Gareth W. Peters and Mario V. W{\"u}thrich and Pavel V. Shevchenko},
  year={2009}
}
The intention of this paper is to analyse the mean square error of prediction (MSEP) under the distribution-free chain ladder (DFCL) claims reserving method. We compare the estimation obtained from the classical bootstrap method with the one obtained from a Bayesian bootstrap. To achieve this in the DFCL model we develop a novel approximate Bayesian computation (ABC) sampling algorithm to obtain the empirical posterior distribution. We need an ABC sampling algorithm because we work in a… CONTINUE READING

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