A study on the pricing of weather derivatives considering risky market prices

As an emerging financial tool, weather derivatives have essential application prospects in agriculture, tourism, and other industries. However, there have been problems such as neglect of market risks and inaccurate pricing. Based on the traditional O-U model, the present paper combines the rate of time-varying mean reversion, the time-varying temperature volatility, and the market price of risk to construct a temperature prediction model. We 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. The numerical results show that the market price of risk can play a corrective role in pricing. Considering the market price of risk performs better in most scenarios for our O-U model. The conclusions provide theoretical guidance and practical reference for pricing agricultural weather derivatives and forming risk hedging mechanisms. © 2022 Systems Engineering Society of China. All rights reserved.