Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/167909 
Year of Publication: 
2017
Citation: 
[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 5 [Issue:] 1 [Publisher:] MDPI [Place:] Basel [Year:] 2017 [Pages:] 1-21
Publisher: 
MDPI, Basel
Abstract: 
We consider the well-known stochastic reserve estimation methods on the basis of generalized linear models, such as the (over-dispersed) Poisson model, the gamma model and the log-normal model. For the likely variability of the claims reserve, bootstrap method is considered. In the bootstrapping framework, we discuss the choice of residuals, namely the Pearson residuals, the deviance residuals and the Anscombe residuals. In addition, several possible residual adjustments are discussed and compared in a case study. We carry out a practical implementation and comparison of methods using real-life insurance data to estimate reserves and their prediction errors. We propose to consider proper scoring rules for model validation, and the assessments will be drawn from an extensive case study.
Subjects: 
chain-ladder
claim reserving
bootstrap
generalized linear model
model validation
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
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