Journal of Energy Markets

On the modeling of temperature dynamics for pricing weather-related products

Zografia Anastasiadou and Brenda López-Cabrera


Weather constitutes an important macroeconomic risk that affects a wide range of industries, among them agriculture, energy and tourism. Companies in these sectors are naturally concerned about unfavorable weather conditions and much attention is paid to the development of risk management tools that deal with weather perils. We present a time series approach for modeling temperature dynamics, which is of special relevance for the pricing of weather/energy derivatives and weather insurance products. A seasonal mean least absolute shrinkage and selection operator-type technique based on a multiplicative structure of Fourier and generalized autoregressive conditional heteroscedasticity (GARCH) terms in volatility is proposed. The model describes the stylized facts of temperature: seasonality, intertemporal correlations and the heteroscedastic behavior of residuals. The application to European temperature data indicates that the multiplicative model for seasonal variance performs better in terms of out-of-sample forecast than other models proposed in the literature for modeling temperature dynamics.

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to View our subscription options

You need to sign in to use this feature. If you don’t have a account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here