Blanchet, J., Lam, H., Tang, Q., & Yuan, Z. (2019). Robust Actuarial Risk Analysis. North American Actuarial Journal, 23(1), 33–63. https://doi.org/10.1080/10920277.2018.1504686

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Abstract

This article investigates techniques for the assessment of model error in the context of insurance risk analysis. The methodology is based on finding robust estimates for actuarial quantities of interest, which are obtained by solving optimization problems over the unknown probabilistic models, with constraints capturing potential nonparametric misspecification of the true model. We demonstrate the solution techniques and the interpretations of these optimization problems, and illustrate several examples, including calculating loss probabilities and conditional value-at-risk.

Authors
Jose Blanchet, Henry Lam, Qihe Tang, Zhongyi Yuan
Publication date
2019/1/2
Journal
North American Actuarial Journal
Volume
23
Issue
1
Pages
33-63
Publisher
Routledge