英文摘要 |
"In response to climate change and price fiuctuations, crop revenue insurance has been a new trend in the implementation of agricultural insurance in various countries in recent years. Taiwan has also begun to plan banana revenue insurance. However, due to limited production and price data, it may affect the objective pricing of insurance. Therefore, probability statistics methods are used to simulate the characteristics of yield and price data and probability distribution to assist in the actuarial calculation of insurance premiums. Based on historical simulation of revenue loss, this paper refiects the characteristics of non-homogeneous Poisson process data, and combines Brownian motion to generate a large amount of price and yield data to estimate the frequency of loss and the extent of loss respectively to determine the pure premium. The empirical simulation results show that due to changes in production conditions and yield, the premiums of Kaohsiung-Pingtung and non- Kaohsiung-Pingtung regions are different, and the difference or divergence of premiums between regions in non-Kaohsiung-Pingtung regions is greater in Kaohsiung-Pingtung regions, refiecting in non-Kaohsiung-Pingtung regions both the yield variability and the price fiuctuation are relatively high. In addition, the difference in premiums between different protection levels is not proportional. The difference between 95% and 90% protection levels is usually larger than other levels, which means that most of the losses are more than 10%. Although the occurrences in losses more than 20% are less frequent, the disaster losses are greater, which means that 80% of the coverage needs to be included to make up for the less compensation of natural disaster relief." |