Two-step risk analysis in insurance ratemaking

Seul Ki Kang, Liang Peng and Andrew Golub

Scandinavian Actuarial Journal, 2021, vol. 2021, issue 6, 532-542

Abstract: Recently, Heras et al. (2018. An application of two-stage quantile regression to insurance ratemaking. Scandinavian Actuarial Journal 9, 753–769) propose a two-step inference to forecast the Value-at-Risk of aggregated losses in insurance ratemaking by combining logistic regression and quantile regression without discussing the critical issue of uncertainty quantification. This paper proposes a random weighted bootstrap method to quantify the estimation uncertainty and an alternative two-step inference via weighted quantile regression.

Date: 2021
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DOI: 10.1080/03461238.2020.1863856

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