Research on Ruin Probability of Risk Model Based on AR(1) Time Series

• 作者: Bolong Wang Dehui Wang Ronghua Zhu Tianxiang Shen Wenhao Li
• 来源期刊: 数学研究通讯
• 年，卷（期）: 2020,（4）
• 页码范围: 390-402
• 页数: 13页
• 语种: 英文
• DOI: 10.4208/cmr.2020-0053

摘要

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 coe?cient 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.

作者信息

序号	姓名	单位	发文数	被引次数	H指数	G指数
1	Wenhao Li		1	0	0.0	0.0
2	Bolong Wang		1	0	0.0	0.0
3	Tianxiang Shen		1	0	0.0	0.0
4	Ronghua Zhu		1	0	0.0	0.0
5	Dehui Wang		1	0	0.0	0.0