Stochastic Loss Reserving Using Bayesian MCMC Models
By Glenn Meyers
This monograph was revised and updated as CAS Monograph No. 8.
In Stochastic Loss Reserving Using Bayesian MCMC Models, 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.
The monograph includes supporting software for download and supporting data, which enables users to apply the methodologies described in the Meyers monograph.
About the Author
Glenn Meyers, FCAS, MAAA, CERA, PhD, retired from ISO in 2011 after a 37-year career as an actuary. He holds a BS in Mathematics and Physics from Alma College, an MA in Mathematics from Oakland University, and a PhD in Mathematics from SUNY at Albany. A frequent speaker at Casualty Actuarial Society (CAS) meetings, he has served, and continues to serve, the CAS and the International Actuarial Association on various research and education committees. He has also served on the CAS Board of Directors. Over the years, he has published articles in the Proceedings of the Casualty Actuarial Society, Variance, and the Actuarial Review. His research and other service contributions have been recognized by the CAS on numerous occasions. He has received the Woodward-Fondiller Prize on three separate occasions, the Dorweiller Prize twice, the DFA Prize, the Reserves Prize, the Matthew Rodermund Service Award, and the Michelbacher Significant Achievement Award. In retirement he still devotes a good portion of his time in pursuit of his passion for actuarial research.
ISBN 978-0-9624762-6-6
Published February 2014
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