A critical view on temperature modelling for application in weather derivatives markets

In this paper we present a stochastic model for daily average temperature. The model contains seasonality, a low-order autoregressive component and a variance describing the heteroskedastic residuals. The model is estimated on daily average temperature records from Stockholm (Sweden). By comparing the proposed model with the popular model of Campbell and Diebold (2005), we point out some important issues to be addressed when modelling the temperature for application in weather derivatives market.

► We present a stochastic model for daily average temperature, containing seasonality, a low-order autoregressive component and a variance describing the heteroskedastic residuals. ► We compare the proposed model with the popular model of Campbell and Diebold (2005). ► Some important issues to be addressed when modelling the temperature for application in weather derivatives market are pointed out.