Weather Derivative Pricing and the Impact of El Nino on Us Temperature: The Statistics of Optimal Categorical Predictions

Abstract

Seasonal forecasts of US temperature have the potential to improve weather derivative pricing. One way to produce such forecasts is to divide the range of possible Pacific ocean surface temperatures into three categories and look at the US temperatures that occur for each category. Unfortunately this approach is hampered by weak signals and lack of data. We perform a statistical analysis of this problem and derive expressions for optimal forecasts that take into account the weakness of the signal and the small sample sizes.

Keywords: weather derivatives, ENSO, El Nino, La Nina, seasonal forecasts

JEL Classification: G12, G13