A new strategy for finite-sample valid prediction of future insurance claims in the regression setting

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Authors: Liang Hong
Cited by: 0

Abstract

The extant insurance literature demonstrates a paucity of finite-sample valid prediction intervals of future insurance claims in the regression setting. To address this challenge, this article proposes a new strategy that converts a predictive method in the unsupervised iid (independent identically distributed) setting to a predictive method in the regression setting. In particular, it enables an actuary to obtain infinitely many finite-sample valid prediction intervals in the regression setting.

Fields of Study & Subjects

Probability and Risk Models Probability and Statistical Research Insurance and Financial Risk Management

Publication details

Journal / source
arXiv (Cornell University)
Publication date
29 January 2026
Document type
Preprint