Year: 2020
Author: Wenhao Li, Bolong Wang, Tianxiang Shen, Ronghua Zhu, Dehui Wang
Communications in Mathematical Research , Vol. 36 (2020), Iss. 4 : pp. 390–402
Abstract
The insurance industry typically exploits ruin theory on collected data to gain more profits. However, state-of-art approaches fail to consider the dependency of the intensity of claim numbers, resulting in the loss of accuracy. In this work, we establish a new risk model based on traditional AR(1) time series, and propose a fine-gained insurance model which has a dependent data structure. We leverage Newton iteration method to figure out the adjustment coefficient and evaluate the exponential upper bound of the ruin probability. We claim that our model significantly improves the precision of insurance model and explores an interesting direction for future research.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/cmr.2020-0053
Communications in Mathematical Research , Vol. 36 (2020), Iss. 4 : pp. 390–402
Published online: 2020-01
AMS Subject Headings: Global Science Press
Copyright: COPYRIGHT: © Global Science Press
Pages: 13
Keywords: Dependent structure moment estimation adjustment coefficient ruin probability.
Author Details
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