Stochastic modelling of temperature for pricing weather derivatives

Abstract

We employ the modified Ornstein-Uhlenbeck model with a seasonal mean and stochastic volatility process to model the daily average temperature (DAT) of Bono region in Ghana. The study findings show that the daily average temperature in the Bono region reverts to a temperature of approximately 26° C at a rate of 18.72% with maximum and minimum temperatures of 32.67° C and 19.75° C, respectively. Although the Bono region is in the middle belt of Ghana, it experiences warm temperatures and experiences dry seasons relatively more than wet seasons in the number of years considered in our analysis. The findings from the study are relevant in the pricing of weather derivatives with temperature as the underlying variable in the financial and agricultural sector. Furthermore, it would assist in the development and design of tailored agriculture insurance models by incorporating the dynamics of temperature.

Keywords

• Stochastic modelling
• agricultural risk management
• forecasting
• weather derivatives
• weather index insurance