Research On Pricing And Risk Management Of Meteorological Insurance And Weather Derivatives Based On Big Data

In the past economic development,all aspects of society and people's production and life have been affected by the risk of weather factors.Combined with the current situation of China's economic development,it is well known that the damage caused by catastrophic weather is heavy,but the losses caused by general weather factors also account for a large proportion.Faced with this situation,foreign countries have developed weather insurance and weather derivatives to make up for the losses.In recent years,although the research program on meteorological insurance in China has improved,there are still many shortcomings,which are slightly inferior to those in foreign countries.Due to the characteristics of China's national conditions,it is necessary to combine the status quo of China's economic development,and to develop weather insurance products that have the characteristics of China and can continue to carry forward and innovate,and in the traditional meteorological insurance pricing,the manipulation of the model presents a clear limit,not Be applicable.Therefore,compared with the foreign Cao-Wei model,the multi-temperature probability model proposed in this paper is more suitable for the study of meteorological insurance,and through the research of this paper,it proves that meteorological insurance has the effect and effect of good transfer risk.of.Based on the research on meteorological insurance,this paper studies the weather derivatives,but compared with meteorological insurance,weather derivatives have more advantages and advantages,and it can respond more flexibly to various weather risks.The paper mainly adopts the method of comparing the multi-temperature probability model with the Cao-Wei model,and the calculation results can support the conclusion that the multi-model has better fitting.The multi-temperature probability model shows a better fitting effect,indicating its accuracy and applicability in meteorological insurance pricing.And the multi-temperature probability model also shows its advantages in the pricing of weather derivatives.It is more flexible than the Cao-Wei model to deal with different scenarios,and the calculated standard deviation is smaller.In order to improve the accuracy of the calculation,this paper uses the Monte Carlo simulation method to simulate the temperature data repeatedly and repeatedly,so that it can respond more flexibly to various scenarios.Based on the research of two kinds of transfer weather risk tools,this paper also conducts in-depth research on the management of weather risk.The specific application scenario is that after the insurance company takes over the weather risks that other enterprises need to bear,it may itself Some methods will hedge the risk,and weather derivatives will constrain the weather hazard.Insurance companies can use the purchase or sale of weather derivatives,and operate the options to hedge the risks.The research in this paper is It proves that this approach and method is extremely effective.