Predictions of future weather conditions play an important role in pricing weather derivatives. In many instances, the dates for which we require predictions are well beyond the point where physical forecasts have any skill. Under these circumstances, predictions are generated from statistical...

This paper examines the quantification of uncertainty in weather derivatives pricing. The focus is on the propagation of a posterior distribution on uncertain model parameters through to relevant payoff statistics, summarizing the uncertainty using variance based credible intervals for any given...

Published methods for the pricing of weather derivatives are based on classical statistics, in that the predictions of the distributions of weather indices that they use are based on best estimates of model parameters. It is likely that such methods do not accurately capture the true uncertainty...

We derive closed-form expressions for the expected payoff of weather derivatives contracts for a t distributed weather index. There are three common situations in which t distributions might serve as a reasonable model for weather indices: first, some weather variables may be t distributed; second...

Many common weather indices are very close to being normally distributed, and it may be reasonable to assume they are exactly normally distributed for the purpose of pricing weather derivatives. Given that assumption, how should the indices be modelled? We use the expected out-of-sample...

The normal distribution is commonly used to predict weather indices when pricing weather derivatives. The standard method for making such predictions involves calculating an unbiased estimator for the population variance. The variance of the prediction (the predictive variance) is then the...

Weather derivative pricing for US locations can potentially be improved through the judicious use of seasonal forecasts. However, the number of El Nino and La Nina events that appear in the historical record is small and for many locations the signals are weak. We run some simulation-based tests...