Research on Ruin Probability of Risk Model Based on AR(1) Time Series (Communications in Mathematical Research, 2020)
The insurance industry typically exploits ruin theory on collecteddata to gain more profits. However, state-of-art approaches fail to consider thedependency 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) timeseries, and propose a fine-gained insurance model which has a dependent datastructure. We leverage Newton iteration method to figure out the adjustmentcoefficient and evaluate the exponential upper bound of the ruin probability. Weclaim that our model significantly improves the precision of insurance modeland explores an interesting direction for future research.