A Study On The Pricing Of Weather Derivatives Considering Risky Market Prices

In recent years,global climate change has intensified,and extreme weather events have occurred frequently.Especially in 2022,many places around the world have experienced extremely high temperature weather,which has only happened once in the past 60 years.Water resources and power supply are insufficient in many places around the world.The severe weather has caused huge economic losses.Weather risk has also aroused widespread concern.Weather derivatives are a new type of financial derivatives that can help companies or institutions reduce losses caused by weather risks,and their pricing research has attracted the attention of scholars.At present,the stochastic process model represented by the O-U model is the most widely used in academic research on the pricing of weather derivatives.However,there are common problems such as inconsistent time-varying parameters and market risk prices being ignored.These problems will affect the pricing accuracy of the weather derivatives and bring additional risks of economic losses to relevant traders.Considering the above deficiencies,this paper conducts research on the pricing of weather derivatives based on the O-U model.Firstly,we considered the time-varying parameter in the model as parameters that varies month by month,which reduces their interference effect on the pricing results.At the same time,we further introduced the risky market prices based on the time-varying O-U model,so that the pricing results fully reflect the attitude of market participants towards risk.In the empirical part,this paper employ the temperature data of the past ten years to conduct pricing research on the weather derivatives of crops.The offered model is also combined with rice,corn,and other crops with a critical impact on life.A comparison was conducted about the pricing results between the proposed model,the traditional time-varying O-U,and ARMA time series models.This study draws the following conclusions:(1)The empirical results show that the pricing accuracy of the proposed model surpasses the pricing results of the traditional time-varying O-U model and the ARMA time series model in terms of futures pricing;in terms of option pricing,the pricing accuracy of the proposed model has completely surpassed the pricing results of the traditional time-varying O-U model and the ARMA time series model,which reflects the impact of market participants’ attitudes on the pricing of crop weather derivatives,which also reflects the rationality of the existence of market risk prices.(2)There are certain differences in the attitudes of market participants to different market risks in different regions,agricultural products and execution prices.The risky market price can adjust the pricing deviation caused by the change of execution price to a certain extent.In the context of the upcoming launch of weather derivatives in our country,our study provides theoretical guidance and practical reference for pricing agricultural weather derivatives and forming risk hedging mechanisms,and provides a new pricing option for the seller of weather derivatives with a reasonable and effective price.At the same time,the proposed model is improved by combining the time-varying coefficient of the O-U model and the risky market price,which provides a new method for relevant researchers.