Research on Natural Disaster Risk Based on Garch Volatility and Monte Carlo Algorithm

Abstract

The purpose of this paper is to study the optimal decision problem of different agents. Firstly, the expression of the profit process of the insurance company is established, and then the loss caused by the natural disaster is fitted into the insurance formula using the double cross-verified natural disaster model. The first is the prediction model of random disaster loss based on Garch volatility test. The other is ridge regression, which combines the possible relevant factors and then makes the forecast. The two results were cross-verified by Garch volatility test again, and then risk assessment and scheme decision were made based on Monte Carlo algorithm and time value theory, and 50,000 simulations were carried out. By estimating the probability of frequency, the probability of bankruptcy under different premiums is obtained. This paper makes an empirical study of New Mexico and Henan in China. For the United States, the paper concludes that an average unit price of $34-35 per policy is appropriate. For Henan Province, this paper focuses on the implementation of natural disaster insurance, and carries out model simulation. The result shows that the premium price of 15% bankruptcy rate is 8 ~ 10 yuan, which is lower than the current policy price, proving that the policy has advantages.