CAS Monograph No. 1: Stochastic Loss Reserving Using Bayesian MCMC Models
In this monograph, author Glenn Meyers, FCAS, MAAA, CERA, introduces a novel way of testing the predictive power of two loss reserving methodologies. Using a database created by the CAS that consists of hundreds of loss development triangles with outcomes, the volume begins by first testing the performance of the Mack model on incurred data and the Bootstrap Overdispersed Poisson model on paid data.
As the emergence of Bayesian MCMC models has provided actuaries with an unprecedented flexibility in stochastic model development, the monograph then identifies some Bayesian MCMC (Markov Chain Monte Carlo) models that improve the performance over the above models.
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