Study on the Applicability of Time-varying O-U Model in the Pricing of Agricultural Temperature Index Insurance

Abstract

Abstract:

The first part of the agricultural temperature index insurance pricing is to improve the accuracy of the temperature prediction. In this paper, the time series model is introduced in the speed of mean reversion to construct a time-varying O-U model. On this basis, we fit the characteristics of daily temperature variation in Wuhan, Dalian and Zhengzhou from 1951 to 2015 respectively, and examine the accuracy of model prediction. On this basis, Wuhan is taken as an example to calculate the income of both the insurer and the insured in a temperature index insurance contract. It is found that the time-varying O-U model can better fit the trend of temperature data, improve the prediction accuracy, boost the price of insurance contracts and increase the probability of farmers' income ending up positive. As a result, on the one hand, it can make the insurance company get higher premium income, thus reducing the cost of operation. On the other hand, although the farmers pay slightly higher premium, their incomes are more likely to end up positive.

Key words: weather derivatives, temperature index insurance, time-varying O-U model, speed of mean reversion

Li Yong, Shi Huan, Li Haiying. Study on the Applicability of Time-varying O-U Model in the Pricing of Agricultural Temperature Index Insurance[J]. , 2020, 32(4): 3-11.

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